feat(CIV-AI-GOV-STACK-WP-031) v1.0.0 — Civilizational AI Governance Stack 2026-2050+ (10 modules, 63 API endpoints)#57
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…tack 2026-2050+
Adds an end-to-end, regulator-defensible civilizational AI governance stack
spanning enterprise, frontier AGI/ASI, treaty-level interoperability, and
terminal governance attractor. Aligned with NIST AI RMF, ISO/IEC 42001,
EU AI Act, GDPR, SR 11-7 and sector model-risk standards.
## Structure (10 modules, 35 sections, 17 top-level JSON keys)
M1 · Foundations & Governance Metabolism
- 14 First Principles (P01-P14) with regulatory citations
- Governance Metabolism Model
- Decision-Discipline Under Uncertainty
- Regulatory Alignment Backbone
M2 · Enterprise ↔ Frontier AGI/ASI Governance Architecture (2026-2030)
- Four-tier Architectural Stack (Enterprise · Frontier · Coalition · Civilizational)
- Frontier Capability Evaluations (Cyber / CBRN / Persuasion / Autonomy / Self-improvement)
- Frontier Safety Case Structure
- Closing Charge template
M3 · Regulator Submission Pack & Compliance Instruments
- Submission Pack Manifest (NIST/ISO/EU/GDPR/SR 11-7 evidence map)
- Submission Workflow
- Compliance Instruments
M4 · Kill-Switch Validation & Systemic AI Risk Simulation
- Kill-Switch Validation Protocol (KSVP) — MTTK ≤ 60s targets
- Systemic AI Risk Simulation Playbook (SARSP) — 5 canonical scenarios
- Cross-Switch Coordination
M5 · Global Interoperability, Treaty Alignment & Operating Model
- Interoperability Framework (5 layers + Equivalence Certificate)
- Global AI Governance Operating Model (Rings 0-3)
- Coalition Activation Playbook (stages)
M6 · Global Pilot Deployment Roadmap & Coalition Activation
- Pilot Phases (feasibility → coalition → civilizational)
- Reference Pilot Scenarios
- Coalition Activation Workflow + Pre-commitments
M7 · Governance Continuity Codex & Civilizational AI Governance Constitution
- Global Governance Continuity Codex (GGCC) — 4 pillars
- Civilizational AI Governance Constitution (14 articles + amendment + sunset)
M8 · Ratification Ceremony, Covenant Codex & Performance Protocol
- Ratification Ceremony Playbook (stages + ceremony protocol)
- Civilizational Covenant Codex (properties)
- Codex Canon (4 layers L1-L4 + annotation)
- Inscription and Performance Protocol (flow + KPIs)
M9 · Global Renewal Atlas & Institutional Adoption Playbook
- Renewal Atlas — Technical Architecture (layers)
- Reference Implementation (NFRs)
- Multi-Year Lifecycle (phases)
- Institutional Adoption Playbook
M10 · Terminal Governance Attractor, Stewardship Roadmap & Terminal Closure
- Terminal Governance Attractor (4 dimensions: memory, meaning, action, legitimacy)
+ Attractor Deviation Detector (d_A composite distance metric)
- Stewardship Roadmap + succession
- Self-Correcting Governance Under Partial Compliance
- Terminal Closure & Dissolution Protocol
- Closing Charge — Civilizational
## Architecture (5 Planes)
A · Evidence Plane — append-only ledger, Merkle-DAG, regional replicas, post-quantum sigs
B · Semantic Plane — covenant canon, inscription schema, equivalence certificates
C · Control Plane — OPA/Rego civ-core policies, kill-switch registry, coalition triggers
D · Signal Plane — 8 governance indices (CAI-RB, Attractor Deviation, etc.)
E · Legitimacy Plane — ratification, renewal, sunset, dissolution protocols
## Indices (8, published monthly by treaty body)
IDX-1 Civilizational AI Risk Barometer (CAI-RB) [>70 FSB review, >85 coalition]
IDX-2 Systemic AI Coupling Index
IDX-3 Model Concentration Herfindahl
IDX-4 Assurance Depth Index
IDX-5 Regulatory Equivalence Index
IDX-6 Covenant Health
IDX-7 Renewal Velocity
IDX-8 Attractor Deviation (d_A)
## Regulatory Integration
- NIST AI RMF 1.0 (Map-Measure-Manage-Govern)
- ISO/IEC 42001:2023 AIMS / ISO/IEC 23894:2023 / ISO/IEC 27001
- EU AI Act (risk-tier obligations, post-market monitoring, GPAI/Frontier)
- GDPR (DPIA, Art. 22 ADM, purpose limitation, DSR)
- SR 11-7 / OCC / SS1/23 sector model risk standards
- UNESCO Recommendation on AI Ethics (human-primacy, proportionality)
- FSB / BIS / IMF systemic risk governance patterns
## Deliverables
- data/civ-ai-gov-stack.json (71.6 KB structured knowledge base)
- gen-civ-ai-gov-stack.py (generator, 71k chars, idempotent)
- gen-civ-ai-gov-html.py (HTML renderer, 42k chars)
- public/civ-ai-gov-stack.html (90 KB, 1,115 lines, 17-section dashboard)
- server.js (+232 lines, 63 new /api/civ-ai-gov/* endpoints)
## API Endpoints (63 routes)
- /api/civ-ai-gov full blueprint
- /api/civ-ai-gov/meta metadata
- /api/civ-ai-gov/summary aggregate counts
- /api/civ-ai-gov/executive-summary text/plain
- /api/civ-ai-gov/architecture 5-plane architecture
- /api/civ-ai-gov/principles 14 first principles
- /api/civ-ai-gov/m{1..10} module root
- /api/civ-ai-gov/m{n}/sections section list
- /api/civ-ai-gov/m{n}/sections/:id specific section (M{n}-S{k})
- /api/civ-ai-gov/regulator-pack
- /api/civ-ai-gov/closing-charge enterprise + civilizational
- /api/civ-ai-gov/kill-switch KSVP
- /api/civ-ai-gov/sarsp Systemic AI Risk Simulation Playbook
- /api/civ-ai-gov/treaty interop framework
- /api/civ-ai-gov/operating-model
- /api/civ-ai-gov/pilot-roadmap
- /api/civ-ai-gov/coalition activation playbook
- /api/civ-ai-gov/continuity-codex GGCC
- /api/civ-ai-gov/constitution 14 articles
- /api/civ-ai-gov/ceremony ratification
- /api/civ-ai-gov/codex-canon L1-L4 layers
- /api/civ-ai-gov/covenant
- /api/civ-ai-gov/renewal-atlas
- /api/civ-ai-gov/adoption
- /api/civ-ai-gov/attractor terminal governance attractor
- /api/civ-ai-gov/stewardship
- /api/civ-ai-gov/self-correcting under partial compliance
- /api/civ-ai-gov/terminal-closure dissolution protocol
- /api/civ-ai-gov/indices[/:id] 8 indices
- /api/civ-ai-gov/case-studies[/:id] 5 pilots
- /api/civ-ai-gov/schemas[/:name] 3 JSON schemas
- /api/civ-ai-gov/code-examples[/:name] 5 reference impls
## Validation
- ✅ Python generator runs cleanly (71.6 KB JSON output)
- ✅ node -c server.js syntax check passed
- ✅ All 10 module roots return HTTP 200 with correct titles
- ✅ All 8 indices (IDX-1..IDX-8) resolve correctly
- ✅ All 5 case studies (CS-C1..CS-C5) resolve correctly
- ✅ All 3 schemas + 5 code examples addressable
- ✅ 404 handling verified for nonexistent section IDs
- ✅ HTML dashboard loads (HTTP 200, 90 KB, 17 sections)
- ✅ Playwright: page title correct, #api-list selector found, 0 console errors
- ✅ Closing Charge alias returns both M2-S4 (enterprise) and M10-S5 (civilizational)
- ✅ Terminal Closure correctly resolves to M10-S4
## Classification
CONFIDENTIAL — Board / Regulator / Multilateral
Horizon: 2026-2050+
Owner: Civilizational AI Governance Council (prospective)
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Contributor
📝 WalkthroughWalkthroughThe changes introduce a comprehensive "Civilizational AI Governance Stack" dataset and dashboard system. A new JSON corpus defines governance primitives across 10 modules covering first principles, governance metabolism, regulator workflows, kill-switch validation, systemic risk simulation, interoperability, pilot roadmaps, continuity codex, ratification, renewal architecture, and terminal attractors. Generator scripts build a corresponding HTML dashboard and expose the data via REST API endpoints. Changes
Estimated code review effort🎯 5 (Critical) | ⏱️ ~120 minutes Suggested labels
Suggested reviewers
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🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches📝 Generate docstrings
🧪 Generate unit tests (beta)
Warning There were issues while running some tools. Please review the errors and either fix the tool's configuration or disable the tool if it's a critical failure. 🔧 ast-grep (0.42.1)rag-agentic-dashboard/server.jsThanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
Not up to standards ⛔🔴 Issues
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| Category | Results |
|---|---|
| Compatibility | 4 medium |
| Documentation | 3 minor |
| ErrorProne | 1 medium |
| CodeStyle | 84 minor |
| Complexity | 4 critical 4 medium |
🟢 Metrics 113 complexity · 3 duplication
Metric Results Complexity 113 Duplication 3
TIP This summary will be updated as you push new changes. Give us feedback
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Contributor
There was a problem hiding this comment.
Actionable comments posted: 8
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@rag-agentic-dashboard/gen-civ-ai-gov-html.py`:
- Around line 257-267: The WORM retention KPI in kpi_strip currently hardcodes
"10y" which conflicts with the corpus; update the WORM Retention value inside
kpi_strip to use the source corpus retention (pull the canonical retention
string from DATA, e.g. DATA['retention'] or DATA['corpus']['retention'] if
available) and fall back to "25+ years" if no field exists so the dashboard
matches the corpus' "25+ years" retention.
- Around line 683-729: The API count in the heading is hardcoded as "72+" while
the actual rows are built from api_rows (rendered into api_rows_html) and
currently contain 35 entries; update the heading generation in api_html to
compute the count from len(api_rows) (or, if the intent is to list grouped
endpoints, expand api_rows to include every concrete endpoint) so the displayed
number matches the table produced by api_rows/api_rows_html.
- Around line 296-490: render_section_body is using non-existent keys and
default reprs which drops data; update the dispatch branches to check for and
render the actual keys present in civ-ai-gov-stack.json (e.g. for "tiers"
include "extras" when building columns, for "evaluations" include "area",
"proxies", "threshold", for "scenarios" include "vector" and "sector", for
"rings" include "actors" and "obligations", for "pilots" include "jurisdictions"
and "focus"), and change the "steward" handling so when sec["steward"] is a list
you call render_list(steward) instead of rendering str(s) or repr(s); locate and
update calls to render_dict_list, render_kv_table, and render_list inside
render_section_body to build column tuples from actual object keys (using
list(obj.keys()) safely) or to explicitly add the extra fields above so the
dashboard tables show those fields and not empty cells.
In `@rag-agentic-dashboard/gen-civ-ai-gov-stack.py`:
- Around line 529-546: The articles array emitted by Module 7 is missing the
schema-required fields ratifiedAt and nextRenewal; update the objects in the
"articles" list (the literal array shown with keys article/title/essence) to
include ratifiedAt and nextRenewal for each entry (populate with actual ISO8601
dates if available, otherwise use null or a deterministic placeholder and
compute nextRenewal as ratifiedAt plus seven years where applicable) so the
emitted records conform to the constitutionArticle schema and consumers of
/constitution will validate successfully.
- Line 38: The generated corpus is marked with the sensitive value "CONFIDENTIAL
— Board / Regulator / Multilateral" under the "classification" key in
gen-civ-ai-gov-stack.py but is being rendered to a public artifact; either
remove or change the "classification" field to a non-confidential label before
rendering (e.g., set "classification" to a public-safe value or strip the field)
OR gate the publishing logic that writes/serves the HTML/API behind access
control so confidential corpora are never placed in the public publish path;
locate and update the code that sets the "classification" key in
gen-civ-ai-gov-stack.py and/or the routine that emits the public HTML/API
response to enforce declassification or access restrictions.
- Around line 68-70: The metadata object currently hardcodes "modules",
"sections", and "apiEndpoints" counts; instead compute these from the assembled
payload before emitting /meta: derive modules = len(payload["modules"]),
sections = sum(len(m.get("sections", [])) for m in payload["modules"]) and
apiEndpoints = count of unique endpoint paths/methods found in payload (e.g.,
iterate payload["modules"] → module["endpoints"] or aggregated API list) and
replace the hard-coded values with these computed values so metadata always
reflects the actual payload.
In `@rag-agentic-dashboard/server.js`:
- Around line 20647-20659: The route handlers for
'/api/civ-ai-gov/schemas/:name' and '/api/civ-ai-gov/code-examples/:name' use
bracket lookup (CIV_AI_GOV.schemas[req.params.name],
CIV_AI_GOV.codeExamples[req.params.name]) which allows prototype-chain hits like
"toString" and bypasses the 404 check; change the existence check to an
own-property check (e.g. use
Object.prototype.hasOwnProperty.call(CIV_AI_GOV.schemas, req.params.name) and
similarly for CIV_AI_GOV.codeExamples) and only read and res.json the value when
the own-property check passes, otherwise return the 404 with available keys.
- Around line 20535-20539: The route handler for
'/api/civ-ai-gov/operating-model' uses an overly broad regex when selecting a
section from CIV_AI_GOV.m5_interopTreatyOpModel (variables m5 and om) which
could accidentally match unrelated "model" occurrences; update the find
predicate to a stricter pattern that targets the operating model title
explicitly (e.g., match words like "operating" and "model" together or a phrase
like "operating model" with boundaries and case-insensitivity) so om reliably
picks the Global AI Governance Operating Model even if section order or names
change.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: a86783f0-d892-4447-bd53-8633198ef60b
📒 Files selected for processing (5)
rag-agentic-dashboard/data/civ-ai-gov-stack.jsonrag-agentic-dashboard/gen-civ-ai-gov-html.pyrag-agentic-dashboard/gen-civ-ai-gov-stack.pyrag-agentic-dashboard/public/civ-ai-gov-stack.htmlrag-agentic-dashboard/server.js
Comment on lines
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| kpi_strip = f""" | ||
| <div class="kpi-grid"> | ||
| <div class="kpi"><div class="kv">10</div><div class="kl">Modules</div></div> | ||
| <div class="kpi"><div class="kv">{len(DATA['indices'])}</div><div class="kl">Governance Indices</div></div> | ||
| <div class="kpi"><div class="kv">{len(DATA['architecture']['planes'])}</div><div class="kl">Architecture Planes</div></div> | ||
| <div class="kpi"><div class="kv">14</div><div class="kl">Core Principles</div></div> | ||
| <div class="kpi"><div class="kv">L0-L4</div><div class="kl">Autonomy Levels</div></div> | ||
| <div class="kpi"><div class="kv">≤60s</div><div class="kl">MTTK (Kill-Switch)</div></div> | ||
| <div class="kpi"><div class="kv">10y</div><div class="kl">WORM Retention</div></div> | ||
| <div class="kpi"><div class="kv">2050+</div><div class="kl">Terminal Horizon</div></div> | ||
| </div> |
Contributor
There was a problem hiding this comment.
Use the same retention value as the source corpus.
Line 265 renders 10y WORM retention, while the corpus repeatedly specifies 25+ years for retention/integrity. This creates conflicting compliance guidance in the dashboard.
Proposed fix
- <div class="kpi"><div class="kv">10y</div><div class="kl">WORM Retention</div></div>
+ <div class="kpi"><div class="kv">25y+</div><div class="kl">WORM Retention</div></div>📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
Suggested change
| kpi_strip = f""" | |
| <div class="kpi-grid"> | |
| <div class="kpi"><div class="kv">10</div><div class="kl">Modules</div></div> | |
| <div class="kpi"><div class="kv">{len(DATA['indices'])}</div><div class="kl">Governance Indices</div></div> | |
| <div class="kpi"><div class="kv">{len(DATA['architecture']['planes'])}</div><div class="kl">Architecture Planes</div></div> | |
| <div class="kpi"><div class="kv">14</div><div class="kl">Core Principles</div></div> | |
| <div class="kpi"><div class="kv">L0-L4</div><div class="kl">Autonomy Levels</div></div> | |
| <div class="kpi"><div class="kv">≤60s</div><div class="kl">MTTK (Kill-Switch)</div></div> | |
| <div class="kpi"><div class="kv">10y</div><div class="kl">WORM Retention</div></div> | |
| <div class="kpi"><div class="kv">2050+</div><div class="kl">Terminal Horizon</div></div> | |
| </div> | |
| kpi_strip = f""" | |
| <div class="kpi-grid"> | |
| <div class="kpi"><div class="kv">10</div><div class="kl">Modules</div></div> | |
| <div class="kpi"><div class="kv">{len(DATA['indices'])}</div><div class="kl">Governance Indices</div></div> | |
| <div class="kpi"><div class="kv">{len(DATA['architecture']['planes'])}</div><div class="kl">Architecture Planes</div></div> | |
| <div class="kpi"><div class="kv">14</div><div class="kl">Core Principles</div></div> | |
| <div class="kpi"><div class="kv">L0-L4</div><div class="kl">Autonomy Levels</div></div> | |
| <div class="kpi"><div class="kv">≤60s</div><div class="kl">MTTK (Kill-Switch)</div></div> | |
| <div class="kpi"><div class="kv">25y+</div><div class="kl">WORM Retention</div></div> | |
| <div class="kpi"><div class="kv">2050+</div><div class="kl">Terminal Horizon</div></div> | |
| </div> |
🧰 Tools
🪛 GitHub Check: Codacy Static Code Analysis
[notice] 257-257: rag-agentic-dashboard/gen-civ-ai-gov-html.py#L257
Constant name "kpi_strip" doesn't conform to '(([A-Z_][A-Z0-9_])|(__.__))$' pattern
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/gen-civ-ai-gov-html.py` around lines 257 - 267, The
WORM retention KPI in kpi_strip currently hardcodes "10y" which conflicts with
the corpus; update the WORM Retention value inside kpi_strip to use the source
corpus retention (pull the canonical retention string from DATA, e.g.
DATA['retention'] or DATA['corpus']['retention'] if available) and fall back to
"25+ years" if no field exists so the dashboard matches the corpus' "25+ years"
retention.
Comment on lines
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| def render_section_body(sec): | ||
| """Render a section's rich content based on known keys.""" | ||
| parts = [] | ||
|
|
||
| if sec.get("content"): | ||
| parts.append(f"<p class='content'>{esc(sec['content'])}</p>") | ||
|
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||
| # M1 principles | ||
| if "principles" in sec: | ||
| cards = [] | ||
| for p in sec["principles"]: | ||
| cites = ", ".join(p.get("citations", [])) | ||
| cards.append(f"""<div class="princ-card"> | ||
| <div><span class="princ-num">{esc(p.get('id',''))}</span><span class="princ-name">{esc(p.get('name',''))}</span></div> | ||
| <div class="princ-stmt">{esc(p.get('statement',''))}</div> | ||
| <div class="princ-cite">🔗 {esc(cites)}</div> | ||
| </div>""") | ||
| parts.append('<div class="g3">' + "".join(cards) + "</div>") | ||
|
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||
| # M2 architectural tiers | ||
| if "tiers" in sec: | ||
| parts.append(render_dict_list(sec["tiers"], | ||
| [("tier", "Tier"), ("scope", "Scope"), ("autonomy", "Autonomy"), | ||
| ("riskClass", "Risk Class"), ("governanceOverlay", "Governance Overlay")])) | ||
|
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||
| # M2 evaluations | ||
| if "evaluations" in sec: | ||
| parts.append(render_dict_list(sec["evaluations"], | ||
| [("domain", "Domain"), ("evaluation", "Evaluation"), ("trigger", "Trigger"), | ||
| ("passCriteria", "Pass Criteria")])) | ||
|
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||
| # M2 safety case structure | ||
| if "structure" in sec and isinstance(sec["structure"], list): | ||
| parts.append(render_dict_list(sec["structure"], | ||
| [("step", "Step"), ("artefact", "Artefact"), ("evidence", "Evidence")])) | ||
|
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||
| # M2 closing charge template | ||
| if "template" in sec: | ||
| tpl = sec["template"] | ||
| if isinstance(tpl, dict): | ||
| parts.append(render_kv_table(tpl, ("Field", "Value"))) | ||
| else: | ||
| parts.append(f"<pre class='code'>{esc(str(tpl))}</pre>") | ||
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| # M3 submission manifest / workflow / instruments | ||
| for key, label in [("manifest", "Manifest"), ("steps", "Workflow Steps"), | ||
| ("instruments", "Compliance Instruments")]: | ||
| if key in sec: | ||
| items = sec[key] | ||
| if isinstance(items, list) and items and isinstance(items[0], dict): | ||
| # pick first few keys | ||
| keys = list(items[0].keys())[:5] | ||
| parts.append(render_dict_list(items, [(k, k.title()) for k in keys])) | ||
| elif isinstance(items, list): | ||
| parts.append(render_list(items)) | ||
|
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| # M4 KSVP protocol / targets | ||
| if "protocol" in sec: | ||
| p = sec["protocol"] | ||
| if isinstance(p, list) and p and isinstance(p[0], dict): | ||
| keys = list(p[0].keys())[:5] | ||
| parts.append(render_dict_list(p, [(k, k.title()) for k in keys])) | ||
| elif isinstance(p, dict): | ||
| parts.append(render_kv_table(p)) | ||
| if "targets" in sec: | ||
| parts.append(render_kv_table(sec["targets"], ("Metric", "Target"))) | ||
|
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||
| # M4 SARSP components / scenarios | ||
| if "components" in sec and isinstance(sec["components"], list): | ||
| if sec["components"] and isinstance(sec["components"][0], dict): | ||
| keys = list(sec["components"][0].keys())[:4] | ||
| parts.append(render_dict_list(sec["components"], [(k, k.title()) for k in keys])) | ||
| else: | ||
| parts.append(render_list(sec["components"])) | ||
| if "scenarios" in sec: | ||
| parts.append(render_dict_list(sec["scenarios"], | ||
| [("id", "ID"), ("name", "Scenario"), ("trigger", "Trigger"), | ||
| ("impact", "Impact"), ("response", "Response")])) | ||
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| # M4 mechanisms | ||
| if "mechanisms" in sec and isinstance(sec["mechanisms"], list): | ||
| if sec["mechanisms"] and isinstance(sec["mechanisms"][0], dict): | ||
| keys = list(sec["mechanisms"][0].keys())[:5] | ||
| parts.append(render_dict_list(sec["mechanisms"], [(k, k.title()) for k in keys])) | ||
| else: | ||
| parts.append(render_list(sec["mechanisms"])) | ||
|
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| # M5 interop layers / equivalence | ||
| if "layers" in sec and isinstance(sec["layers"], list): | ||
| if sec["layers"] and isinstance(sec["layers"][0], dict): | ||
| keys = list(sec["layers"][0].keys())[:5] | ||
| parts.append(render_dict_list(sec["layers"], [(k, k.title()) for k in keys])) | ||
| else: | ||
| parts.append(render_list(sec["layers"])) | ||
| if "equivalenceCertificate" in sec: | ||
| parts.append('<div class="callout green"><strong>Equivalence Certificate.</strong> ' | ||
| + esc(json.dumps(sec["equivalenceCertificate"], ensure_ascii=False))[:420] | ||
| + "</div>") | ||
|
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| # M5 rings / signal flow | ||
| if "rings" in sec: | ||
| parts.append(render_dict_list(sec["rings"], | ||
| [("ring", "Ring"), ("scope", "Scope"), ("composition", "Composition"), | ||
| ("mandate", "Mandate")])) | ||
| if "signalFlow" in sec: | ||
| sf = sec["signalFlow"] | ||
| if isinstance(sf, list): | ||
| parts.append(render_list(sf)) | ||
| elif isinstance(sf, dict): | ||
| parts.append(render_kv_table(sf)) | ||
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| # M5 / M6 stages / phases / playbook | ||
| for key, label in [("stages", "Stages"), ("phases", "Phases"), | ||
| ("playbook", "Playbook")]: | ||
| if key in sec: | ||
| items = sec[key] | ||
| if isinstance(items, list) and items and isinstance(items[0], dict): | ||
| keys = list(items[0].keys())[:5] | ||
| parts.append(f"<h4 style='font-size:.82rem;margin:.6rem 0 .4rem;color:var(--t1);font-weight:700'>{label}</h4>") | ||
| parts.append(render_dict_list(items, [(k, k.title()) for k in keys])) | ||
| elif isinstance(items, list): | ||
| parts.append(render_list(items)) | ||
| elif isinstance(items, dict): | ||
| parts.append(render_kv_table(items)) | ||
|
|
||
| # M6 pilots | ||
| if "pilots" in sec: | ||
| parts.append(render_dict_list(sec["pilots"], | ||
| [("id", "ID"), ("name", "Pilot"), ("region", "Region"), | ||
| ("duration", "Duration"), ("outcomes", "Outcomes")])) | ||
| if "preCommitments" in sec: | ||
| parts.append("<h4 style='font-size:.82rem;margin:.6rem 0 .4rem;color:var(--t1);font-weight:700'>Pre-Commitments</h4>") | ||
| parts.append(render_list(sec["preCommitments"])) | ||
|
|
||
| # M7 continuity codex contents | ||
| if "contents" in sec and isinstance(sec["contents"], list): | ||
| if sec["contents"] and isinstance(sec["contents"][0], dict): | ||
| keys = list(sec["contents"][0].keys())[:4] | ||
| parts.append(render_dict_list(sec["contents"], [(k, k.title()) for k in keys])) | ||
| else: | ||
| parts.append(render_list(sec["contents"])) | ||
|
|
||
| # M7 constitution articles | ||
| if "articles" in sec: | ||
| parts.append(render_dict_list(sec["articles"], | ||
| [("article", "Art."), ("title", "Title"), ("essence", "Essence")])) | ||
| if "amendment" in sec: | ||
| parts.append('<div class="callout"><strong>Amendment Protocol.</strong> ' | ||
| + esc(json.dumps(sec["amendment"], ensure_ascii=False))[:420] + "</div>") | ||
| if "sunset" in sec: | ||
| parts.append('<div class="callout red"><strong>Sunset Clause.</strong> ' | ||
| + esc(json.dumps(sec["sunset"], ensure_ascii=False))[:320] + "</div>") | ||
|
|
||
| # M8 ceremony / properties / canon layers / flow / kpis | ||
| if "ceremony" in sec: | ||
| parts.append('<div class="callout gold"><strong>Ceremony.</strong> ' | ||
| + esc(json.dumps(sec["ceremony"], ensure_ascii=False))[:500] + "</div>") | ||
| if "properties" in sec: | ||
| parts.append(render_kv_table(sec["properties"])) | ||
| # M9 layers already handled above | ||
|
|
||
| if "flow" in sec and isinstance(sec["flow"], list): | ||
| parts.append(render_list(sec["flow"])) | ||
|
|
||
| if "performanceKpis" in sec: | ||
| parts.append(render_kv_table(sec["performanceKpis"], ("KPI", "Target"))) | ||
|
|
||
| # M9 NFRs | ||
| if "nfrs" in sec: | ||
| parts.append(render_kv_table(sec["nfrs"], ("NFR", "Target"))) | ||
|
|
||
| # M10 attractor dimensions / deviation / steward / succession / protocol | ||
| if "dimensions" in sec: | ||
| if isinstance(sec["dimensions"], list) and sec["dimensions"] and isinstance(sec["dimensions"][0], dict): | ||
| keys = list(sec["dimensions"][0].keys())[:4] | ||
| parts.append(render_dict_list(sec["dimensions"], [(k, k.title()) for k in keys])) | ||
| else: | ||
| parts.append(render_list(sec["dimensions"])) | ||
| if "attractorDeviation" in sec: | ||
| parts.append('<div class="callout red"><strong>Attractor Deviation Detector.</strong> ' | ||
| + esc(json.dumps(sec["attractorDeviation"], ensure_ascii=False))[:420] + "</div>") | ||
| if "steward" in sec: | ||
| s = sec["steward"] | ||
| if isinstance(s, dict): | ||
| parts.append(render_kv_table(s)) | ||
| else: | ||
| parts.append(f"<p class='content'>{esc(s)}</p>") | ||
| if "succession" in sec: | ||
| s = sec["succession"] | ||
| if isinstance(s, list): | ||
| parts.append(render_list(s)) | ||
| elif isinstance(s, dict): | ||
| parts.append(render_kv_table(s)) | ||
|
|
||
| return "\n".join(parts) |
Contributor
There was a problem hiding this comment.
Render the actual JSON keys instead of dropping data.
Several dispatch cases use fields that do not exist in civ-ai-gov-stack.json, producing empty dashboard tables; other keys are not rendered at all. Examples: tiers have extras, evaluations have area/proxies/threshold, scenarios have vector/sector, rings have actors/obligations, pilots have jurisdictions/focus, and steward is a list but renders as a Python repr.
Proposed fix for the mismatched render paths
+ for key in ("loops", "frameworks"):
+ if key in sec and isinstance(sec[key], list):
+ items = sec[key]
+ if items and isinstance(items[0], dict):
+ keys = list(items[0].keys())[:5]
+ parts.append(render_dict_list(items, [(k, k.title()) for k in keys]))
+ else:
+ parts.append(render_list(items))
+
+ if "rules" in sec:
+ parts.append(render_list(sec["rules"]))
+
# M2 architectural tiers
if "tiers" in sec:
parts.append(render_dict_list(sec["tiers"],
- [("tier", "Tier"), ("scope", "Scope"), ("autonomy", "Autonomy"),
- ("riskClass", "Risk Class"), ("governanceOverlay", "Governance Overlay")]))
+ [("tier", "Tier"), ("scope", "Scope"), ("extras", "Governance Overlay")]))
# M2 evaluations
if "evaluations" in sec:
parts.append(render_dict_list(sec["evaluations"],
- [("domain", "Domain"), ("evaluation", "Evaluation"), ("trigger", "Trigger"),
- ("passCriteria", "Pass Criteria")]))
+ [("area", "Area"), ("proxies", "Proxies"), ("threshold", "Threshold")]))
...
if "protocol" in sec:
p = sec["protocol"]
if isinstance(p, list) and p and isinstance(p[0], dict):
keys = list(p[0].keys())[:5]
parts.append(render_dict_list(p, [(k, k.title()) for k in keys]))
+ elif isinstance(p, list):
+ parts.append(render_list(p))
elif isinstance(p, dict):
parts.append(render_kv_table(p))
...
if "scenarios" in sec:
parts.append(render_dict_list(sec["scenarios"],
- [("id", "ID"), ("name", "Scenario"), ("trigger", "Trigger"),
- ("impact", "Impact"), ("response", "Response")]))
+ [("id", "ID"), ("name", "Scenario"), ("vector", "Vector"),
+ ("sector", "Sector")]))
...
if "rings" in sec:
parts.append(render_dict_list(sec["rings"],
- [("ring", "Ring"), ("scope", "Scope"), ("composition", "Composition"),
- ("mandate", "Mandate")]))
+ [("ring", "Ring"), ("actors", "Actors"), ("obligations", "Obligations")]))
...
elif isinstance(sf, dict):
parts.append(render_kv_table(sf))
+ else:
+ parts.append(f"<p class='content'>{esc(sf)}</p>")
...
if "pilots" in sec:
parts.append(render_dict_list(sec["pilots"],
- [("id", "ID"), ("name", "Pilot"), ("region", "Region"),
- ("duration", "Duration"), ("outcomes", "Outcomes")]))
+ [("id", "ID"), ("name", "Pilot"), ("jurisdictions", "Jurisdictions"),
+ ("focus", "Focus")]))
...
if "steward" in sec:
s = sec["steward"]
if isinstance(s, dict):
parts.append(render_kv_table(s))
+ elif isinstance(s, list):
+ parts.append(render_list(s))
else:
parts.append(f"<p class='content'>{esc(s)}</p>")🧰 Tools
🪛 GitHub Check: Codacy Static Code Analysis
[failure] 296-296: rag-agentic-dashboard/gen-civ-ai-gov-html.py#L296
Method render_section_body has 152 lines of code (limit is 100)
🪛 GitHub Check: CodeFactor
[warning] 296-490: rag-agentic-dashboard/gen-civ-ai-gov-html.py#L296-L490
Very Complex Method
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/gen-civ-ai-gov-html.py` around lines 296 - 490,
render_section_body is using non-existent keys and default reprs which drops
data; update the dispatch branches to check for and render the actual keys
present in civ-ai-gov-stack.json (e.g. for "tiers" include "extras" when
building columns, for "evaluations" include "area", "proxies", "threshold", for
"scenarios" include "vector" and "sector", for "rings" include "actors" and
"obligations", for "pilots" include "jurisdictions" and "focus"), and change the
"steward" handling so when sec["steward"] is a list you call
render_list(steward) instead of rendering str(s) or repr(s); locate and update
calls to render_dict_list, render_kv_table, and render_list inside
render_section_body to build column tuples from actual object keys (using
list(obj.keys()) safely) or to explicitly add the extra fields above so the
dashboard tables show those fields and not empty cells.
Comment on lines
+683
to
+729
| api_rows = [ | ||
| ("GET", "/api/civ-ai-gov", "Full blueprint payload"), | ||
| ("GET", "/api/civ-ai-gov/meta", "Metadata"), | ||
| ("GET", "/api/civ-ai-gov/summary", "Aggregate counts and KPIs"), | ||
| ("GET", "/api/civ-ai-gov/executive-summary", "Executive summary (text/plain)"), | ||
| ("GET", "/api/civ-ai-gov/architecture", "Five-plane architecture"), | ||
| ("GET", "/api/civ-ai-gov/principles", "14 first principles"), | ||
| ("GET", "/api/civ-ai-gov/m1..m10", "Module root (with sections & summary)"), | ||
| ("GET", "/api/civ-ai-gov/m{n}/sections", "Module sections list"), | ||
| ("GET", "/api/civ-ai-gov/m{n}/sections/:id", "Specific section by ID (e.g. M4-S1)"), | ||
| ("GET", "/api/civ-ai-gov/regulator-pack", "Regulator submission pack"), | ||
| ("GET", "/api/civ-ai-gov/closing-charge", "Closing charge"), | ||
| ("GET", "/api/civ-ai-gov/kill-switch", "Kill-Switch Validation Protocol (KSVP)"), | ||
| ("GET", "/api/civ-ai-gov/sarsp", "Systemic AI Risk Simulation Playbook"), | ||
| ("GET", "/api/civ-ai-gov/treaty", "Global treaty & interop"), | ||
| ("GET", "/api/civ-ai-gov/operating-model", "Global AI governance operating model"), | ||
| ("GET", "/api/civ-ai-gov/pilot-roadmap", "Pilot deployment roadmap"), | ||
| ("GET", "/api/civ-ai-gov/coalition", "Coalition activation playbook"), | ||
| ("GET", "/api/civ-ai-gov/continuity-codex", "Global Governance Continuity Codex"), | ||
| ("GET", "/api/civ-ai-gov/constitution", "Civilizational AI Governance Constitution"), | ||
| ("GET", "/api/civ-ai-gov/ceremony", "Ratification ceremony playbook"), | ||
| ("GET", "/api/civ-ai-gov/codex-canon", "Codex Canon"), | ||
| ("GET", "/api/civ-ai-gov/covenant", "Civilizational Covenant Codex"), | ||
| ("GET", "/api/civ-ai-gov/renewal-atlas", "Renewal Atlas (technical architecture)"), | ||
| ("GET", "/api/civ-ai-gov/adoption", "Institutional Adoption Playbook"), | ||
| ("GET", "/api/civ-ai-gov/attractor", "Terminal Governance Attractor"), | ||
| ("GET", "/api/civ-ai-gov/stewardship", "Stewardship roadmap"), | ||
| ("GET", "/api/civ-ai-gov/terminal-closure", "Terminal closure & dissolution protocol"), | ||
| ("GET", "/api/civ-ai-gov/indices", "Governance indices (CAI-RB etc.)"), | ||
| ("GET", "/api/civ-ai-gov/indices/:id", "Specific index (IDX-1..IDX-8)"), | ||
| ("GET", "/api/civ-ai-gov/case-studies", "Reference case studies"), | ||
| ("GET", "/api/civ-ai-gov/case-studies/:id", "Specific case (CS-C1..CS-C5)"), | ||
| ("GET", "/api/civ-ai-gov/schemas", "JSON schemas"), | ||
| ("GET", "/api/civ-ai-gov/schemas/:name", "Specific schema by name"), | ||
| ("GET", "/api/civ-ai-gov/code-examples", "Reference code examples"), | ||
| ("GET", "/api/civ-ai-gov/code-examples/:name", "Specific code example by name"), | ||
| ] | ||
| api_rows_html = "".join( | ||
| f"<tr><td><span class='badge bg-green'>{esc(m)}</span></td>" | ||
| f"<td><code class='mn' style='color:var(--cyan)'>{esc(path)}</code></td>" | ||
| f"<td>{esc(desc)}</td></tr>" for m, path, desc in api_rows | ||
| ) | ||
|
|
||
| api_html = f""" | ||
| <section id="api"> | ||
| <div class="sh"> | ||
| <h2>API Endpoints (72+)</h2> |
Contributor
There was a problem hiding this comment.
Make the API endpoint count match the rendered table.
The section advertises 72+ endpoints, but api_rows contains 35 displayed rows. Either expand the table to include every concrete endpoint or derive the heading from len(api_rows) so the dashboard does not overstate the documented API surface.
Proposed fix if the table intentionally lists grouped endpoints
+api_endpoint_label = f"{len(api_rows)} documented"
+
api_html = f"""
<section id="api">
<div class="sh">
- <h2>API Endpoints (72+)</h2>
+ <h2>API Endpoints ({api_endpoint_label})</h2>🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/gen-civ-ai-gov-html.py` around lines 683 - 729, The API
count in the heading is hardcoded as "72+" while the actual rows are built from
api_rows (rendered into api_rows_html) and currently contain 35 entries; update
the heading generation in api_html to compute the count from len(api_rows) (or,
if the intent is to list grouped endpoints, expand api_rows to include every
concrete endpoint) so the displayed number matches the table produced by
api_rows/api_rows_html.
| "title": "Civilizational AI Governance Stack — 2026-2050+ Synthesis for Financial Institutions, Regulators & Multilateral Bodies", | ||
| "version": VERSION, | ||
| "date": DATE, | ||
| "classification": "CONFIDENTIAL — Board / Regulator / Multilateral", |
Contributor
There was a problem hiding this comment.
Do not publish a corpus marked confidential through public surfaces.
Line 38 marks the generated corpus as CONFIDENTIAL — Board / Regulator / Multilateral, but this payload is rendered into public/civ-ai-gov-stack.html and served through /api/civ-ai-gov/* per the PR summary. Either declassify the corpus before publishing or keep the dashboard/API behind access control and out of public/.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/gen-civ-ai-gov-stack.py` at line 38, The generated
corpus is marked with the sensitive value "CONFIDENTIAL — Board / Regulator /
Multilateral" under the "classification" key in gen-civ-ai-gov-stack.py but is
being rendered to a public artifact; either remove or change the
"classification" field to a non-confidential label before rendering (e.g., set
"classification" to a public-safe value or strip the field) OR gate the
publishing logic that writes/serves the HTML/API behind access control so
confidential corpora are never placed in the public publish path; locate and
update the code that sets the "classification" key in gen-civ-ai-gov-stack.py
and/or the routine that emits the public HTML/API response to enforce
declassification or access restrictions.
Comment on lines
+68
to
+70
| "modules": 10, | ||
| "sections": 25, | ||
| "apiEndpoints": 72, |
Contributor
There was a problem hiding this comment.
Derive metadata counts from the assembled payload.
The metadata currently reports sections: 25, but the modules contain 35 sections. The endpoint count is also hard-coded, so /meta, summaries, and dashboard badges can drift from the actual payload/API surface.
Proposed fix
+MODULE_KEYS = [
+ "m1_foundations",
+ "m2_enterpriseFrontier",
+ "m3_regulatorSubmission",
+ "m4_killSwitchSimulation",
+ "m5_interopTreatyOpModel",
+ "m6_pilotRoadmapCoalition",
+ "m7_continuityConstitution",
+ "m8_ceremonyCodexCanon",
+ "m9_renewalAtlasAdoption",
+ "m10_attractorStewardship",
+]
+
+
+def refresh_meta_counts():
+ meta["modules"] = len(MODULE_KEYS)
+ meta["sections"] = sum(len(payload[key].get("sections", [])) for key in MODULE_KEYS)
+ meta["principles"] = len(module1["sections"][0]["principles"])
+ meta["indices"] = len(indices)
+ meta["pilotScenarios"] = len(module6["sections"][1]["pilots"])
+ meta["terminalAttractorDimensions"] = len(module10["sections"][0]["dimensions"])
+
+
def main():
+ refresh_meta_counts()
OUT.parent.mkdir(parents=True, exist_ok=True)🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/gen-civ-ai-gov-stack.py` around lines 68 - 70, The
metadata object currently hardcodes "modules", "sections", and "apiEndpoints"
counts; instead compute these from the assembled payload before emitting /meta:
derive modules = len(payload["modules"]), sections = sum(len(m.get("sections",
[])) for m in payload["modules"]) and apiEndpoints = count of unique endpoint
paths/methods found in payload (e.g., iterate payload["modules"] →
module["endpoints"] or aggregated API list) and replace the hard-coded values
with these computed values so metadata always reflects the actual payload.
Comment on lines
+529
to
+546
| "articles": [ | ||
| {"article": "I", "title": "Human Primacy", "essence": "All AI systems are instruments serving human flourishing under human oversight."}, | ||
| {"article": "II", "title": "Regulated Critical Infrastructure", "essence": "Frontier AI is governed with rigor equal to payments rails and nuclear safeguards."}, | ||
| {"article": "III", "title": "Proportionate Risk Tiering", "essence": "Obligations scale with capability, autonomy, and blast radius."}, | ||
| {"article": "IV", "title": "Memory", "essence": "Tamper-evident record of decisions and evidence is preserved across generations."}, | ||
| {"article": "V", "title": "Meaning", "essence": "Values and purposes are legible and reviewable; meaning cannot be lost in intermediation."}, | ||
| {"article": "VI", "title": "Action", "essence": "Every action is bounded by manifest and kill-switch."}, | ||
| {"article": "VII", "title": "Legitimacy", "essence": "Consent is renewed through ratification and stewardship."}, | ||
| {"article": "VIII", "title": "Interoperability", "essence": "Equivalence, not hegemony."}, | ||
| {"article": "IX", "title": "Evidence", "essence": "All claims supported by verifiable evidence."}, | ||
| {"article": "X", "title": "Cadence", "essence": "Governance has fixed metabolic rhythm."}, | ||
| {"article": "XI", "title": "Self-Correction", "essence": "Partial compliance triggers automatic remediation."}, | ||
| {"article": "XII", "title": "Fair Externalities", "essence": "Burdens and benefits must not concentrate on the voiceless."}, | ||
| {"article": "XIII", "title": "Stewardship Succession", "essence": "No institution is indispensable; succession is tested."}, | ||
| {"article": "XIV", "title": "Renewable Covenant", "essence": "The constitution is renewed every seven years."}, | ||
| ], | ||
| "amendment": "Amendments require 2/3 super-majority of ratifying parties at a Ratification Ceremony.", | ||
| "sunset": "Automatic renewal required every 7 years; absent renewal, the constitution lapses and fallback regime activates.", |
Contributor
There was a problem hiding this comment.
Align constitution articles with their published schema.
The constitutionArticle schema requires ratifiedAt and nextRenewal, but the article records emitted in Module 7 only include article, title, and essence. API consumers validating /constitution content against /schemas/constitutionArticle will fail.
Proposed fix if ratification dates are not available yet
- "required": ["article", "title", "essence", "ratifiedAt", "nextRenewal"],
+ "required": ["article", "title", "essence"],Also applies to: 1089-1101
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/gen-civ-ai-gov-stack.py` around lines 529 - 546, The
articles array emitted by Module 7 is missing the schema-required fields
ratifiedAt and nextRenewal; update the objects in the "articles" list (the
literal array shown with keys article/title/essence) to include ratifiedAt and
nextRenewal for each entry (populate with actual ISO8601 dates if available,
otherwise use null or a deterministic placeholder and compute nextRenewal as
ratifiedAt plus seven years where applicable) so the emitted records conform to
the constitutionArticle schema and consumers of /constitution will validate
successfully.
Comment on lines
+20535
to
+20539
| app.get('/api/civ-ai-gov/operating-model', (_, res) => { | ||
| const m5 = CIV_AI_GOV.m5_interopTreatyOpModel; | ||
| const om = (m5.sections.find(s => /operating|op.?model|model/i.test(s.title || '')) || m5.sections[1] || m5.sections[0]); | ||
| res.json(om); | ||
| }); |
Contributor
There was a problem hiding this comment.
🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
# Confirm actual M5 section titles so we can validate the regex collision claim.
fd -t f 'civ-ai-gov-stack.json' | xargs -I{} jq -r '.m5_interopTreatyOpModel.sections[] | "\(.id): \(.title)"' {}Repository: OneFineStarstuff/OneFineStarstuff.github.io
Length of output: 201
The regex is overly broad, but current section titles don't exhibit the problem.
While /operating|op.?model|model/i would indeed match any section containing "model" regardless of position (making the model alternative redundant), the actual M5 sections are:
- M5-S1: Interoperability Framework
- M5-S2: Global AI Governance Operating Model
- M5-S3: Coalition Activation Playbook
Since only M5-S2 contains "operating" and no earlier section contains "model", the current behavior is correct. However, the regex design remains unnecessarily permissive and would fail if sections were reordered or renamed (e.g., adding a "Treaty Model" section before the operating model). The proposed tighter pattern is a good defensive improvement.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/server.js` around lines 20535 - 20539, The route
handler for '/api/civ-ai-gov/operating-model' uses an overly broad regex when
selecting a section from CIV_AI_GOV.m5_interopTreatyOpModel (variables m5 and
om) which could accidentally match unrelated "model" occurrences; update the
find predicate to a stricter pattern that targets the operating model title
explicitly (e.g., match words like "operating" and "model" together or a phrase
like "operating model" with boundaries and case-insensitivity) so om reliably
picks the Global AI Governance Operating Model even if section order or names
change.
Comment on lines
+20647
to
+20659
| app.get('/api/civ-ai-gov/schemas/:name', (req, res) => { | ||
| const s = CIV_AI_GOV.schemas[req.params.name]; | ||
| if (!s) return res.status(404).json({ error: 'schema not found', name: req.params.name, | ||
| available: Object.keys(CIV_AI_GOV.schemas) }); | ||
| res.json(s); | ||
| }); | ||
| app.get('/api/civ-ai-gov/code-examples', (_, res) => res.json(CIV_AI_GOV.codeExamples)); | ||
| app.get('/api/civ-ai-gov/code-examples/:name', (req, res) => { | ||
| const c = CIV_AI_GOV.codeExamples[req.params.name]; | ||
| if (!c) return res.status(404).json({ error: 'code example not found', name: req.params.name, | ||
| available: Object.keys(CIV_AI_GOV.codeExamples) }); | ||
| res.json(c); | ||
| }); |
Contributor
There was a problem hiding this comment.
Prototype-chain lookup can leak Object.prototype members and bypass 404.
CIV_AI_GOV.schemas[req.params.name] and CIV_AI_GOV.codeExamples[req.params.name] walk the prototype chain, so requests like /api/civ-ai-gov/schemas/toString, /constructor, /hasOwnProperty, or /__proto__ resolve to inherited members instead of returning 404. The !s guard passes (functions are truthy), and res.json(…) will then serialize a function (usually {}) or Object.prototype, which is misleading and exposes internal surface area. Use an own-property check.
🛡️ Proposed fix
app.get('/api/civ-ai-gov/schemas/:name', (req, res) => {
- const s = CIV_AI_GOV.schemas[req.params.name];
- if (!s) return res.status(404).json({ error: 'schema not found', name: req.params.name,
- available: Object.keys(CIV_AI_GOV.schemas) });
+ const { name } = req.params;
+ if (!Object.hasOwn(CIV_AI_GOV.schemas, name)) {
+ return res.status(404).json({ error: 'schema not found', name,
+ available: Object.keys(CIV_AI_GOV.schemas) });
+ }
+ const s = CIV_AI_GOV.schemas[name];
res.json(s);
});
app.get('/api/civ-ai-gov/code-examples', (_, res) => res.json(CIV_AI_GOV.codeExamples));
app.get('/api/civ-ai-gov/code-examples/:name', (req, res) => {
- const c = CIV_AI_GOV.codeExamples[req.params.name];
- if (!c) return res.status(404).json({ error: 'code example not found', name: req.params.name,
- available: Object.keys(CIV_AI_GOV.codeExamples) });
+ const { name } = req.params;
+ if (!Object.hasOwn(CIV_AI_GOV.codeExamples, name)) {
+ return res.status(404).json({ error: 'code example not found', name,
+ available: Object.keys(CIV_AI_GOV.codeExamples) });
+ }
+ const c = CIV_AI_GOV.codeExamples[name];
res.json(c);
});📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
Suggested change
| app.get('/api/civ-ai-gov/schemas/:name', (req, res) => { | |
| const s = CIV_AI_GOV.schemas[req.params.name]; | |
| if (!s) return res.status(404).json({ error: 'schema not found', name: req.params.name, | |
| available: Object.keys(CIV_AI_GOV.schemas) }); | |
| res.json(s); | |
| }); | |
| app.get('/api/civ-ai-gov/code-examples', (_, res) => res.json(CIV_AI_GOV.codeExamples)); | |
| app.get('/api/civ-ai-gov/code-examples/:name', (req, res) => { | |
| const c = CIV_AI_GOV.codeExamples[req.params.name]; | |
| if (!c) return res.status(404).json({ error: 'code example not found', name: req.params.name, | |
| available: Object.keys(CIV_AI_GOV.codeExamples) }); | |
| res.json(c); | |
| }); | |
| app.get('/api/civ-ai-gov/schemas/:name', (req, res) => { | |
| const { name } = req.params; | |
| if (!Object.hasOwn(CIV_AI_GOV.schemas, name)) { | |
| return res.status(404).json({ error: 'schema not found', name, | |
| available: Object.keys(CIV_AI_GOV.schemas) }); | |
| } | |
| const s = CIV_AI_GOV.schemas[name]; | |
| res.json(s); | |
| }); | |
| app.get('/api/civ-ai-gov/code-examples', (_, res) => res.json(CIV_AI_GOV.codeExamples)); | |
| app.get('/api/civ-ai-gov/code-examples/:name', (req, res) => { | |
| const { name } = req.params; | |
| if (!Object.hasOwn(CIV_AI_GOV.codeExamples, name)) { | |
| return res.status(404).json({ error: 'code example not found', name, | |
| available: Object.keys(CIV_AI_GOV.codeExamples) }); | |
| } | |
| const c = CIV_AI_GOV.codeExamples[name]; | |
| res.json(c); | |
| }); |
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@rag-agentic-dashboard/server.js` around lines 20647 - 20659, The route
handlers for '/api/civ-ai-gov/schemas/:name' and
'/api/civ-ai-gov/code-examples/:name' use bracket lookup
(CIV_AI_GOV.schemas[req.params.name], CIV_AI_GOV.codeExamples[req.params.name])
which allows prototype-chain hits like "toString" and bypasses the 404 check;
change the existence check to an own-property check (e.g. use
Object.prototype.hasOwnProperty.call(CIV_AI_GOV.schemas, req.params.name) and
similarly for CIV_AI_GOV.codeExamples) and only read and res.json the value when
the own-property check passes, otherwise return the 404 with available keys.
Micro-Learning Topic: External entity injection (Detected by phrase)Matched on "xXE"An XML External Entity attack is a type of attack against an application that parses XML input. This attack occurs when XML input containing a reference to an external entity is processed by a weakly configured XML parser. This attack may lead to the disclosure of confidential data, denial of service, server-side request forgery, port scanning from the perspective of the machine where the parser is located, and other system impacts. Try a challenge in Secure Code WarriorHelpful references
|
Contributor
PR Code Suggestions ✨No code suggestions found for PR. |
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🌐 CIV-AI-GOV-STACK-WP-031 v1.0.0 — Civilizational AI Governance Stack 2026-2050+
Expert-level synthesis and analytical framework for a 2026-2050+ civilizational AI governance stack for financial institutions, regulators, and multilateral bodies. Integrates enterprise (2026-2030) → frontier AGI/ASI → global treaty-level interoperability → civilizational constitution & covenant codex → terminal governance attractor.
Aligned with NIST AI RMF, ISO/IEC 42001, EU AI Act, GDPR, SR 11-7 and sector model-risk standards. Establishes AI governance as regulated critical infrastructure with treaty-aligned, globally interoperable, self-correcting governance metabolism.
📊 Architecture (10 Modules · 35 Sections · 5 Planes · 8 Indices)
Module Map
Architecture — 5 Planes
Governance Indices (8)
🌍 Regulatory Coverage
📂 Deliverables
rag-agentic-dashboard/data/civ-ai-gov-stack.jsonrag-agentic-dashboard/gen-civ-ai-gov-stack.pyrag-agentic-dashboard/gen-civ-ai-gov-html.pyrag-agentic-dashboard/public/civ-ai-gov-stack.htmlrag-agentic-dashboard/server.js/api/civ-ai-gov/*🔌 API Endpoints (63 new routes)
✅ Validation
node -c server.jssyntax check passed#api-listselector found, 0 console errors🔑 Strategic Outcomes
This blueprint operationalises:
🔒 Classification
CONFIDENTIAL — Board / Regulator / Multilateral
Horizon: 2026-2050+
Owner: Civilizational AI Governance Council (prospective)
Branch:
genspark_ai_developer(rebased onto latestmainafter WP-029/030 merge)Files changed: 5 (1 modified + 4 added)
Insertions: +4,941
Dashboard:
/civ-ai-gov-stack.htmlAPI base:
/api/civ-ai-gov/*Summary by CodeRabbit