gentle-pi

Turn Pi from a powerful coding agent into a controlled development harness.

gentle-pi installs el Gentleman in Pi: a senior-architect operating layer for Spec-Driven Development, focused subagents, strict TDD evidence, reviewable work units, safety guards, project/user skill discovery, and bounded native review.

Pi already has strong tools. gentle-pi adds the discipline for using them well, then binds review and delivery decisions to Git-derived evidence instead of agent narration.

gentle-pi is the Pi-native package from the Gentle-AI ecosystem, built by Gentleman Programming: the broader open-source project for turning AI coding agents into disciplined engineering environments with SDD workflows, skills, memory integrations, model routing, and review guardrails across multiple agents.

Follow the project and the community around it:

• GitHub: Gentleman-Programming
• YouTube: Gentleman Programming
• Community Discord: Gentleman Programming

Startup intro collaboration: thanks to @aporcelli for pi-gentle-startup, which inspired the clean-screen startup animation, compact runtime panel, and pink visual treatment.

The problem

Most coding-agent sessions fail for operational reasons, not model reasons:

• the agent jumps into code before requirements are clear;
• architectural decisions disappear into chat history;
• one request quietly becomes a huge multi-area diff;
• tests run late, or not at all;
• reviewers get handed a wall of changes;
• subagents are available, but the parent session has no orchestration discipline;
• project skills exist, but the model forgets to load them.

gentle-pi fixes the workflow around the agent.

What it adds

Capability	What it does
el Gentleman persona	Makes Pi behave like a senior architect and teacher, not a generic chatbot. Spanish responses use Rioplatense voseo by default; neutral mode is saved globally with project overrides.
Configurable startup intro	Adds a rose/text-logo startup intro, compact runtime panel, color presets, and commands to hide or show the decorative parts.
Work routing discipline	Small tasks stay inline. Context-heavy exploration can be delegated. Large or risky changes go through SDD/OpenSpec.
SDD/OpenSpec assets	Installs phase agents and chains for init, onboard, explore, proposal, spec, design, tasks, apply, verify, sync, and archive.
Lazy SDD preflight	Asks once per session for SDD mode, artifact store, PR chaining strategy, and review budget before the first SDD flow.
Subagent orchestration	Keeps one parent session responsible while child agents explore, implement, test, or review with focused context.
Strict TDD support	When project config declares a test command, apply/verify phases must record RED → GREEN → TRIANGULATE → REFACTOR evidence.
Reviewer protection	Surfaces review workload risk before a task turns into an oversized PR.
Per-agent model assignment	Pi-native modal for assigning stronger or cheaper models to specific SDD/custom agents.
Skill discovery registry	Maintains .atl/skill-registry.md from project and user skills so review/comment/PR workflows do not silently miss the right skill.
Skill creation workflow	Provides the gentle-ai-skill-creator/gentle-ai-skill-improver skills, /skill-creation prompt, and packaged style guide for LLM-first skills.
Delivery skills	Includes issue-first PRs, chained PRs, work-unit commits, cognitive docs, comment writing, and Judgment Day review.
Bounded native review	Freezes one candidate, dispatches only controller-selected lenses, records native authority, and reuses the same content-bound receipt at delivery gates.
Verified native runtime	Provisions the exact package-local Gentle AI v2.1.4 binary, verifies pinned archive/binary integrity, and rejects PATH, global, sibling, symlink, and mode fallbacks.
Runtime safety	Blocks destructive shell commands, asks for confirmation for sensitive operations, and blocks direct read/write/edit access to sensitive paths.

Install

pi install npm:gentle-pi

The npm postinstall downloads the exact platform-specific official Gentle AI v2.1.4 archive into this package's private .gentle-ai/v2.1.4/ directory and verifies its pinned SHA-256 before extraction. It never uses PATH or a global gentle-ai installation. For development or offline installs only, set GENTLE_PI_SKIP_GENTLE_AI_INSTALL=1; native review operations then fail closed with an actionable package-local-binary-missing error until the package is reinstalled normally.

Recommended companion packages:

pi install npm:pi-subagents-j0k3r
pi install npm:pi-intercom
pi install npm:gentle-engram
pi install npm:pi-web-access
pi install npm:pi-lens
pi install npm:@juicesharp/rpiv-todo
pi install npm:@juicesharp/rpiv-ask-user-question

Then start Pi in a project:

pi

gentle-pi provides SDD agents as global Pi runtime assets, not per-project setup. The first SDD flow in a session still runs a one-time SDD preflight for preferences; for natural-language requests, el Gentleman decides when SDD is needed and runs the explicit preflight first.

Quick start

/gentle:status          Check package, SDD assets, OpenSpec, and global model config.
/gentle:doctor          Run read-only diagnostics for SDD assets, config, tools, and guards.
/gentle:sdd-preflight   Run or reuse the session SDD preflight explicitly.
/sdd-init                  Create or refresh openspec/config.yaml.
/gentle:models             Assign global model/effort routing to SDD/custom agents.
/gentle:persona            Switch between gentleman and neutral persona modes.
/gentle:banner             Configure startup rose, text logo, and color preset.

Typical flow:

1. Open Pi in your repo.
2. Run /gentle:status.
3. Run /sdd-init once per project, or when test/project capabilities change. This also runs the session SDD preflight.
4. For a substantial change, ask Pi to use SDD. Natural-language requests are classified by the parent agent, not by brittle runtime regexes.
5. Review the phase artifacts instead of trusting floating chat context.

Core workflow

1. Install and inspect. Install gentle-pi, open Pi in the target repository, then run /gentle:status or /gentle:doctor.
2. Plan when risk justifies it. Small work stays direct; substantial work uses SDD with Engram, OpenSpec, or both so requirements and decisions survive compaction.
3. Build with evidence. One focused writer implements the approved scope. When Strict TDD is available, apply and verify preserve RED → GREEN → TRIANGULATE → REFACTOR evidence.
4. Review one candidate. Native START derives and freezes the Git candidate, risk tier, selected lenses, authored-line budget, and correction allowance. Review actors assess that immutable view; they do not grant authority.
5. Deliver the same candidate. FINALIZE records native authority and an approved receipt. Commit, push, PR, and release gates validate that same receipt and live Git target with zero review actors; they never silently reopen review or reset its budget.

Trust what the system can derive, not what an agent claims. Agents analyze the candidate. The package-local Gentle AI runtime owns scope, risk, findings, receipts, and lifecycle gates. This protects against accidental scope and identity drift, not a malicious same-user process that can replace local code or authority. See Gentle AI's review authority threat model and Chapter 21 — Verifiable Trust.

How the harness decides what to do

gentle-pi routes through the smallest safe workflow:

Request shape	Harness
Small, clear, local edit	Inline direct work.
Unknown codebase area or context-heavy investigation	Focused subagent delegation.
Large, ambiguous, architectural, product-facing, or high-review-risk change	SDD/OpenSpec flow.

The goal is not ceremony. The goal is to avoid accidental chaos. Once a task stops being small, delegation is mandatory.

Delegation triggers

gentle-pi keeps the parent session thin and delegates at the narrowest useful point. When the Pi Subagents extension is installed, the preferred runtime is the subagent_* tool family because it runs the user's configured project/global subagent definitions and preserves history/background behavior. Use waiting/task mode when the parent must consume the result and continue the workflow; use background mode only for independent work where parent continuation is not required. If those tools are unavailable, the parent should fall back to Pi's native Agent tool or another available delegation mechanism. The requirement is delegation; the runtime is capability-dependent.

Trigger	Required behavior
Reading 4+ files to understand a flow	Launch scout, context-builder, or the closest read-only mapping subagent.
Touching 2+ non-trivial code files	Delegate one writer; do not continue inline unless delegation is unavailable.
Commit, push, or PR after code changes	Validate the approved receipt and exact typed target with zero actors.
Wrong cwd, worktree/git accident, merge recovery, confusing test/env issue	Stop, preserve the frozen scope, investigate separately, and validate the existing receipt; never launch a fresh review lens or reopen review as incident handling.
Long monolithic session with accumulating complexity, roughly 20 tool calls, 5 exploratory reads, or 2 non-mechanical edits	Pause and delegate the remaining work, or stop and explain the exact blocker.

The intended balanced loop for a bounded bugfix is:

parent git/status + clarify → bind ordinary snapshot/route → one worker writes authorized fixes → targeted proof validation when required → final verification

Review lenses are controller-selected transaction actors, not lifecycle hooks. scout/context-builder save parent context by compressing broad exploration. worker preserves a single writer thread. Commit, push, PR, and release validate receipts with zero actors.

Review actors are dispatched only through parent subagent_run calls in mode: "task". Before execution, the controller verifies every entry, content hash, mode, root, and index in one selected immutable candidate tree per requested lens, then appends one bounded controller-owned block containing only the Git-derived base-to-candidate changed scope. That compact scope groups present paths by exact candidate mode and lists deletions explicitly; it fails closed when the changed scope itself exceeds the dispatch bound. Mixed batches, unselected/missing/stale views, user-supplied candidate-view text, unsafe paths, and non-task dispatches fail closed; lean resources and actor tool allowlists remain unchanged.

Review authority recovery and reset safety

Legacy pre-graph authority is never migrated. gentle_review inspect reports an exact repository-bound destructive reset challenge; only that authorized RESET or RECOVER can quarantine graph-v1 and compact-v2 authority, initialize an empty graph-v1 incarnation, and require fresh review. Interrupted destructive recovery remains blocked until explicit forward recovery. Existing graph-v1 ordinary lineages remain readable, gate-validatable, and exportable but are read-only; Judgment Day remains mutable on graph-v1.

A non-destructive supersession is available only for an eligible, immutable graph-v1 source and an independently approved compact-v2 successor with identical repository, change, target, scope, untracked, policy, ledger, and receipt bindings. First call prepare-supersession, review its exact English challenge, then call supersede only after fresh interactive approval. Headless approval, a changed challenge, a stale binding, unsupported data, or ambiguous authority fails closed and leaves the change resolve-review blocked.

Supersession records are append-only under authority-supersession-v1; they do not rewrite graph-v1 history. An exact retry is idempotent. A divergent retry or conflict fails closed and requires a new operation. RESET/RECOVER stay destructive and never run as a fallback from supersession. Rollback can stop recognizing a record but does not delete it, re-enable graph-v1 mutation, or select another successor.

Pre-commit, pre-push, pre-PR, and release gates revalidate the recovered source, successor, receipt, policy, scope, intended-untracked proof, and live target. Recovery does not grant a new budget or bypass dangerous-command authorization, publication checks, historical graph-v1 receipt validation, or graph export.

reviewer is not an installed subagent name. It is a routing intent. Select the concrete lens by risk profile:

Context	Review lens
Clear naming, structure, maintainability, small refactors	review-readability
Behavior, state, tests, determinism, regressions	review-reliability
Shell/process integration, partial failures, recovery, degraded dependencies	review-resilience
Security, permissions, data exposure/loss, architecture, dependencies	review-risk
Large PR, hot path, or >400 changed lines	Full 4R: review-risk, review-resilience, review-readability, review-reliability

Risk selection is deterministic: documentation/comment/formatting-only changes use zero lenses; every other standard change uses exactly one dominant-risk lens; security/auth/update/payment paths, data-loss or exposure risk, shell/process integration, or more than 400 authored changed lines use the full 4R set. A standard review never accumulates multiple lenses ad hoc.

Bounded review transactions

New ordinary review uses compact gentle_review start -> finalize -> validate.

Native contract pairing is exact: this adapter supports gentle-ai 2.1.4 only from its package-local verified binary and rechecks that version before every native operation. Production native operations resolve an absolute package-owned path and never fall back to PATH or a global executable. Once v2.1.4 has written review authority, rollback MUST preserve every native store and receipt and MUST NOT run a downgraded binary against that repository. Disable the Pi route or roll forward to a compatible authority-aware release instead; deleting authority data or reinstalling an older binary is not a rollback path.

Gentle AI v2.1.4 supports gentle-ai review start --projection staged, and upstream main now documents that focused-index workflow. The current gentle-pi adapter intentionally submits projection: "workspace" and does not expose staged projection yet. Native binary capability is not automatically a Pi adapter contract; package support still requires an adapter update, parity fixtures, and bounded validation.

FINALIZE wrapper input

gentle_review accepts input as a JSON-serialized object string. For initial results, provide review_result.lens_results[]; each selected lens appears exactly once with lens, findings, and non-empty evidence. A clean lens uses findings: []. final_evidence and final_verification_passed are paired: provide both or neither.

{
  "review_result": {
    "lens_results": [
      {
        "lens": "review-reliability",
        "findings": [],
        "evidence": ["complete candidate reviewed"]
      }
    ]
  }
}

This is the Pi wrapper contract, not the native CLI file contract. The native command receives separate --result, --refuter, --validation, and --evidence files from the wrapper.

START derives the complete Git/untracked snapshot, lineage, persisted low | medium | high tier, zero/one/four lenses, authored changed lines, and correction budget min(200, ceil(original_changed_lines / 2)). Generated testdata/golden/** stays in snapshot identity but does not count as authored risk lines.

Every finding requires evidence_class, causal_disposition, and concrete changed-hunk, candidate-created-path, differential-test, or before/after proof. Missing IDs are assigned natively and selected-lens results are canonicalized deterministically.

Actor output is untrusted data and cannot authorize transitions, fixes, receipts, gates, or delivery.

Only severe introduced, behavior-activated, or worsened findings with valid proof enter correction IDs. pre-existing and base-only become follow-ups; unknown, insufficient, malformed, or inconclusive severe claims escalate. WARNING and SUGGESTION are informational.

Deterministic blockers need no refuter. Inferential blockers use exactly one complete read-only refuter batch.

Refuter proof may be independent concrete reproduction evidence; it does not need to duplicate reviewer proof_refs. Invalid, empty, malformed, missing, duplicate, unknown, or inconclusive refuter output escalates without a replacement refuter.

When native IDs are assigned to inferential findings, the first FINALIZE returns their canonical rows and a content-derived request hash without mutation; the second replays identical lens input with that hash and one complete refuter batch.

Ordinary permits up to three failed targeted attempts within the original cumulative budget; each attempt is one correction plus one targeted validator. FINALIZE requires a positive forecast before editing and derives actual correction lines from Git. Initial lenses are never rerun, while frozen findings and genesis scope remain unchanged.

The validator checks original criteria and correction regression only and cannot add scope or findings. Final evidence is hashed during FINALIZE, never at START.

Compact ordinary has five states: reviewing, correction_required, validating, approved, and escalated.

Each validator invocation cannot change claims, add findings, request fixes, launch actors, or request another attempt. Native FINALIZE alone returns correction_required while another bounded attempt remains.

Compact authority uses content-derived CAS under the Git common directory. Exact retries are idempotent; stale/semantic retries, terminal mutation, and same-lineage graph-v1/compact-v2 ambiguity fail closed.

Trust boundary: The local orchestrator and same-user process are trusted to execute selected actors and submit their exact outputs. Native code owns scope, risk, IDs, canonicalization, state, receipts, and gates, and rejects malformed or inconsistent results structurally and causally. Malicious same-user host/process authenticity is a non-goal because that actor can replace the extension or mutate local authority; externally trusted attestation would require a separately privileged signer/service and is not claimed.

Ordinary ends only as approved or escalated.

Judgment Day starts only when explicitly requested and replaces ordinary review for that lineage.

Judgment Day starts with exactly two blind judges and zero refuters.

Judgment Day alone may iterate discovery and scoped re-judgment, for at most two rounds.

Findings surviving round two escalate; no third-round transition exists.

Compact gate validation is read-only. It loads authority and receipt, derives the live target, then reloads authority and rederives target/publication evidence immediately before allow.

Pi also registers one one-shot authorization for the exact command and rederives its full publication target before registration, before bash-time native validation, and again after that validation before allowing the command. For gh pr create, the effective repository follows GitHub CLI precedence (--repo, then GH_REPO, then local inference), and both that source/value and the exact advertised remote head commit are bound and rechecked against reviewed local HEAD. Publication ls-remote probes are shell-free, output-bounded, time-bounded, and cancellation-aware. The complete bash-time publication/native revalidation uses one aggregate bounded deadline combined with Pi's cancellation signal when available. First-push, push destination, exact PR base/head, repository identity, release, and dangerous-command protections remain fail closed. Native pre-push to an existing branch is supported only when the effective push URL and repository identity equal the fetch URL and identity used by the exact <remote>/<destination-branch> selector, and its advertised commit equals the command update's old object. Split fetch/push topology is unsupported because PR #1216 introduced the upstream v2.1.1 --base-ref contract that v2.1.3 inherits unchanged: that contract resolves the selector through fetch-side remote-tracking state, and probing pushurl does not change selector resolution. Pi fails closed before native validation with native-split-fetch-push-unsupported-until-upstream-supports-explicit-push-base. Native pre-PR remains fetch-side and may use advertised remote selectors. Residual gap (separate follow-up): native first-push authorization remains unsupported until Pi has a persisted explicit advertised-base source. A missing destination fails closed with native-first-push-unsupported-until-persisted-advertised-base-exists; Pi never guesses a base from an upstream, default branch, or nearest ancestor.

Native SDD readiness is true only for verify or archive with empty blockers and a published reviewGate.result: "allow"; review/resolve-review, missing gate evidence, and every non-allow or stale result remain blocked. Release from protected main may bypass receipt validation only when the tag targets the current immutable origin/main SHA, required CI for that exact SHA is successful, the remote head is rechecked before tag push, and no fresh risk evidence exists; otherwise release fails closed through native receipt validation. Major and post-incident releases require explicit extraordinary review even when fast-path checks pass.

Dangerous-command safety remains independent and authoritative.

SDD completion adds no review or Judgment Day pass.

Review transactions, validation, and SDD perform no commit, push, PR creation, release, or publication.

review-refuter uses exactly read, grep, and find in a package-managed isolated installation. Project and user overrides may shadow the package asset; gentle-pi preserves those definitions and does not claim their effective permissions are package-compliant.

SDD/OpenSpec flow

init
  ↓
explore → proposal → spec ─┬→ design ─┐
                            └─────────┴→ tasks → apply → verify → sync → archive

The main loop is intentionally file-backed when you choose openspec or both:

planning artifacts                implementation evidence        canonical update
──────────────────                ───────────────────────        ────────────────
proposal/spec/design/tasks   →    apply-progress/verify-report → sync-report → archive-report

For substantial work, the parent session coordinates the flow and each phase writes artifacts. That gives you:

• explicit requirements and non-goals;
• design decisions that survive compaction;
• task plans reviewers can reason about;
• implementation evidence;
• verification reports;
• sync reports that update canonical specs while keeping the change active;
• archive notes for future agents.

OpenSpec artifact model

gentle-pi treats OpenSpec-compatible behavior as part of the harness. You do not need to install the external OpenSpec CLI/package for SDD.

In file-backed modes, canonical accepted behavior lives in openspec/specs/, while active changes carry deltas under openspec/changes/:

openspec/
├── specs/                                      # accepted source of truth
│   └── {domain}/spec.md
└── changes/
    ├── {change}/                              # active work
    │   ├── proposal.md
    │   ├── specs/{domain}/spec.md             # full spec or delta spec
    │   ├── design.md
    │   ├── tasks.md
    │   ├── apply-progress.md
    │   ├── verify-report.md
    │   └── sync-report.md
    └── archive/YYYY-MM-DD-{change}/           # immutable audit trail

Delta flow:

openspec/changes/{change}/specs/{domain}/spec.md
        │
        │  sdd-sync applies ADDED / MODIFIED / REMOVED
        ▼
openspec/specs/{domain}/spec.md
        │
        │  sdd-archive moves the completed change folder
        ▼
openspec/changes/archive/YYYY-MM-DD-{change}/

When a canonical spec already exists, change specs use requirement operation sections:

## ADDED Requirements

## MODIFIED Requirements

## REMOVED Requirements

MODIFIED requirements must include the full requirement block, including still-valid scenarios, because sync replaces the canonical block by requirement name. sdd-sync syncs file-backed deltas into openspec/specs/{domain}/spec.md while keeping the change active; sdd-archive then moves the synced change to openspec/changes/archive/YYYY-MM-DD-{change}/.

Engram-only mode is different by design: Engram is working memory and does not maintain a canonical spec merge layer. Use openspec or both (hybrid file + memory persistence) when you need canonical spec evolution.

SDD preflight and project files

gentle-pi does not require SDD agents to be copied into every project. The package ensures global Pi SDD assets exist under the Pi agent home and treats project-local files only as overrides/debug copies. Slash SDD flows such as /sdd-*, /sdd-init, and the explicit /gentle:sdd-preflight command run a lazy preflight and ask for session-scoped SDD preferences. For natural-language requests, the parent agent decides whether the work should use SDD and must run/reuse /gentle:sdd-preflight before continuing.

~/.pi/agent/agents/sdd-*.md
~/.pi/agent/chains/sdd-*.chain.md
~/.pi/agent/gentle-ai/support/strict-tdd*.md

The preflight choices are reused for later SDD flows in the same session:

• execution mode: interactive or auto;
• artifact store: openspec, or engram/both when callable memory tools are available;
• PR chaining strategy: auto-forecast, ask-always, single-pr-default, or force-chained;
• review budget line threshold.

It does not overwrite existing global assets unless you explicitly run:

/gentle:install-sdd --force

Manual preflight command:

/gentle:sdd-preflight

Skill registry

gentle-pi keeps a local registry at:

.atl/skill-registry.md

The registry scans project and user skill roots, not package-owned skills. It exists to catch workflow skills that are present on disk but not visible in Pi's injected skill list.

It scans common roots such as:

./skills
.opencode/skills
.claude/skills
.gemini/skills
.cursor/skills
.github/skills
.codex/skills
.qwen/skills
.kiro/skills
.openclaw/skills
.pi/skills
.agent/skills
.agents/skills
.atl/skills
~/.pi/agent/skills
~/.config/agents/skills
~/.agents/skills
~/.kimi/skills
~/.config/opencode/skills
~/.config/kilo/skills
~/.claude/skills
~/.gemini/skills
~/.gemini/antigravity/skills
~/.cursor/skills
~/.copilot/skills
~/.codex/skills
~/.codeium/windsurf/skills
~/.qwen/skills
~/.kiro/skills
~/.openclaw/skills

Behavior:

• .atl/ is added to .gitignore when needed;
• the registry refreshes on session start;
• startup refresh is skipped when Pi starts with --no-skills / -ns, --no-skill-registry, or GENTLE_PI_NO_SKILL_REGISTRY=1;
• /skill-registry:refresh forces regeneration;
• a best-effort watcher refreshes when skill files change;
• the registry indexes skill names, full descriptions, scope, and exact SKILL.md paths without copying skill body rules.

Skill discovery is a guardrail, not a workflow router: it helps Pi load the right skill without forcing extra ceremony.

gentle-pi also ships package-owned gentle-ai-skill-creator and gentle-ai-skill-improver skills plus the /skill-creation prompt for creating or updating project skills. Both skills use docs/skill-style-guide.md as their normative style contract. The workflow checks for duplicates, keeps SKILL.md concise, uses one-line trigger-rich frontmatter, and reminds maintainers to refresh the registry after skill changes.

Packaged skills include cognitive-doc-design, comment-writer, gentle-ai-judgment-day, gentle-ai-skill-creator, gentle-ai-skill-improver, and the other delivery/review skills under skills/. SDD init is installed as the packaged sdd-init runtime agent under assets/agents/ and refreshed with the SDD assets.

Compatibility: the package keeps the existing skill folders (skills/branch-pr, skills/judgment-day, skills/skill-creator) but their exported frontmatter names are prefixed to avoid collisions with user/global skills. Treat former package names such as branch-pr, judgment-day, and skill-creator as legacy aliases in prose; runtime skill selection should use gentle-ai-branch-pr, gentle-ai-judgment-day, and gentle-ai-skill-creator.

Delegation contract:

• parent/orchestrator resolves project/user skills from the registry and passes matching paths under ## Skills to load before work;
• SDD subagents still use their assigned executor/phase skill;
• during normal runtime, subagents should not independently discover additional project/user SKILL.md files or the registry;
• fallback loading is degraded self-healing and must be reported via skill_resolution as fallback-registry, fallback-path, or none.

Persona modes

/gentle:persona

Persona	Behavior
gentleman	Senior architect, teacher, direct technical feedback, Rioplatense Spanish/voseo when the user writes Spanish.
neutral	Same discipline, warmer professional language, no regional expression.

Saved globally at:

~/.pi/gentle-ai/persona.json

A project can still override the global default with:

.pi/gentle-ai/persona.json

/gentle:persona writes the global config and updates an existing project override when one is present, so the current project does not stay stale. Run /reload or start a new Pi session after switching persona.

Model and effort assignment

/gentle:models

The modal discovers:

• project agents in .pi/subagents/, .pi/agents/, and .agents/;
• user agents in ~/.pi/agent/subagents/, ~/.pi/agent/agents/, and ~/.agents/;
• built-in agents from pi-subagents-j0k3r when present.

When applying routing, project agents write runtime profiles to .pi/subagents.json; global and built-in agents write profiles to ~/.pi/agent/subagents.json.

Recommended model/effort shape:

Agent kind	Recommended model	Recommended effort (thinking)
Explore, proposal, archive	Fast and cheap is usually enough.	off to low
Spec, design, tasks	Strong reasoning model.	medium to high
Apply	Strong coding and tool-use model.	medium to high
Verify / review	Strong fresh-context model.	high
Tiny utilities	Inherit active/default model unless they bottleneck.	inherit

Saved globally at:

~/.pi/gentle-ai/models.json

Existing project-local .pi/gentle-ai/models.json files are still read as a legacy fallback when no global model config exists, but /gentle:models writes the shared global config.

Inside /gentle:models, press x to export the saved routing to ~/.pi/gentle-ai/models.export.json, or r to restore from that file after confirmation. Export uses a versioned envelope and restore writes the normal models.json shape before applying routing to agents.

Config shape (per agent):

{
  "sdd-design": {
    "model": "anthropic/claude-sonnet-4",
    "thinking": "high"
  },
  "sdd-archive": {
    "model": "openai/gpt-5-mini"
  }
}

Legacy string entries are still accepted and treated as model-only config.

Commands

Command	What it does
/gentle:status	Shows package, SDD asset, OpenSpec, and global model config status.
/gentle:doctor	Runs read-only diagnostics for SDD assets, model/persona config, memory tools, and safety guards.
/gentle:models	Opens global model + effort assignment UI. Press x to export and r to restore saved routing.
/gentle:persona	Switches global persona mode, with project override support.
/gentle:banner	Configures startup banner rose, text logo, and color preset.
/gentle:toggle-rose	Toggles the startup rose.
/gentle:toggle-text-logo	Toggles the startup text logo.
/gentle:banner-color	Selects a startup banner color preset.
/sdd-init	Initializes or refreshes openspec/config.yaml.
/gentle:install-sdd	Repairs missing global SDD runtime assets without overwriting files.
/gentle:install-sdd --force	Force-refreshes installed global SDD assets.
/skill-registry:refresh	Regenerates .atl/skill-registry.md.
/skill-creation	Creates or updates an LLM-first skill using the packaged gentle-ai-skill-creator contract and style guide.

Package-owned global SDD runtime assets are also refreshed automatically on session start when gentle-pi changes. Project-local .pi/agents and .pi/chains remain manual overrides and are never overwritten by startup refresh.

Startup banner settings are global and default to the current pink rose + text logo. Supported color presets are pink, cyan, yellow, and green.

Startup flag:

pi --no-skill-registry

Use it when you want skills available normally but do not want Gentle AI to refresh/watch .atl/skill-registry.md on startup. pi -ns / pi --no-skills also skip the registry startup work because Pi is already disabling skill loading.

Included skills

• gentle-ai — harness discipline for controlled Pi work.
• gentle-ai-branch-pr — issue-first PR preparation.
• gentle-ai-chained-pr — split oversized changes into reviewable PR chains.
• work-unit-commits — commits as reviewable work units.
• gentle-ai-judgment-day — blind dual review, fixes, and re-judgment.
• cognitive-doc-design — documentation that reduces cognitive load.
• comment-writer — concise, warm, postable collaboration comments.
• gentle-ai-issue-creation — issue workflow with checks before creation.
• gentle-ai-skill-creator — create LLM-first skills with valid frontmatter.
• gentle-ai-skill-improver — audit and upgrade existing LLM-first skills.

Memory

gentle-pi does not provide persistent memory by itself.

For memory, install the companion package:

pi install npm:gentle-engram

When memory tools are actually active, el Gentleman can save decisions, bug fixes, discoveries, user prompts, and session summaries across Pi sessions.

Memory contract for SDD delegation:

• parent/orchestrator owns memory retrieval and passes selected context into subagent prompts;
• subagents should not independently search memory during normal runtime unless explicitly instructed to retrieve a specific artifact or observation;
• subagents should save significant discoveries, decisions, bug fixes, and completed SDD phase artifacts before returning when memory tools are available;
• in memory/hybrid mode, SDD artifacts use stable topic keys such as sdd/<change>/proposal, sdd/<change>/spec, sdd/<change>/design, sdd/<change>/tasks, sdd/<change>/apply-progress, and sdd/<change>/verify-report.

Package contents

Path	Purpose
extensions/gentle-ai.ts	Injects identity, orchestrates native review authority and lifecycle gates, refreshes global SDD assets, registers commands, applies model/persona config, and enforces runtime safety.
lib/native-review-cli.ts	Strict package-local adapter for Gentle AI START, FINALIZE, VALIDATE, SDD binding, and status contracts.
lib/review-candidate-view.ts	Builds immutable changed-scope actor views while preserving full-tree, path, mode, symlink, and index integrity.
lib/gentle-ai-binary.ts	Resolves and verifies the confined package-local Gentle AI runtime without global or PATH fallback.
scripts/gentle-ai-installer.mjs	Downloads, verifies, extracts, and atomically promotes the pinned native runtime for six platform targets.
extensions/startup-banner.ts	Shows and configures the startup intro, color presets, compact runtime panel, and collaboration credit.
extensions/sdd-init.ts	Registers /sdd-init for OpenSpec initialization.
extensions/skill-registry.ts	Maintains .atl/skill-registry.md from project/user skills and closes file watchers on shutdown.
assets/orchestrator.md	Parent-session orchestration contract.
assets/agents/	SDD agents installed as global Pi runtime assets.
assets/chains/	SDD chains installed as global Pi runtime assets.
assets/support/	Strict TDD support docs for apply/verify phases.
skills/	Gentle AI delivery and collaboration skills.
prompts/	Gentle-prefixed prompt templates, including /skill-creation.
docs/skill-style-guide.md	Normative style guide used by the packaged skill creation/improvement skills.

Development

Install from this repo:

pi install .

Validate before publishing:

pnpm test
bun build extensions/skill-registry.ts --target=node --format=esm --outfile=/tmp/skill-registry.js
node --experimental-strip-types --check extensions/gentle-ai.ts
node --experimental-strip-types --check extensions/sdd-init.ts
node --experimental-strip-types --check extensions/startup-banner.ts
npm pack --dry-run

Publish npm through GitHub Actions only:

gh workflow run publish.yml --repo Gentleman-Programming/gentle-pi --ref main -f dist-tag=latest
gh run watch <run-id> --repo Gentleman-Programming/gentle-pi --exit-status
npm view gentle-pi@<version> version --registry=https://registry.npmjs.org/
npm dist-tag ls gentle-pi --registry=https://registry.npmjs.org/

Do not run npm publish locally for gentle-pi; the GitHub workflow provides provenance, environment protection, and registry credentials.

Principles

• Human control over agent momentum.
• Concepts before code.
• Artifacts over floating chat context.
• SDD when risk justifies it.
• Strict TDD when tests exist.
• One parent orchestrator, focused subagents.
• Reviewable changes over giant diffs.