Audience: a coding agent (Claude Code, Cursor, Codex, etc.) and the non-coding human directing it.
- Human: Adapt
rules/user-context.template.mdfor your project, save it as~/.claude/rules/user-context.md. - Human: Read
workorders/01-scaffold.md, replace the project-specific examples with yours. - Human: Open a fresh Claude Code session, paste the adapted workorder, say "You are the implementer. Follow this workorder. Ask me questions where you need decisions."
- Agent: Reads workorder, asks questions, builds
.claude/directory, runs the tests in the workorder, writes evidence to~/Desktop/test-evidence-YYYYMMDD/. - Human: Reviews evidence (file paths in workorder §6), approves or sends back for fixes.
- Repeat for
workorders/02-skill-content.md(writes the actual SKILL.md content).
What gets built:
~/.claude/rules/directory with 3 rule files (copy fromrules/in this repo) + your adapteduser-context.md~/.claude/hooks/directory with 4 shell scripts (1 keyword-trigger + 3 validators)~/.claude/skills/<your-skill-name>/SKILL.mdplaceholder~/.claude/settings.jsonupdated to register the 4 new hooks (without breaking your existing hooks)
What you (the human) decide during scaffold:
- Skill name (e.g.,
<project>-production-standards, or whatever fits your project) - Trigger keywords for your project's "new agent / upgrade / refactor" terms
- Whether to install globally (
~/.claude/) or per-project (<project>/.claude/) - Names of any
verify-*validation hooks specific to your project's hard rules
Estimated time: agent ~30-45 minutes, human ~5 minutes of decisions + 2 minutes of review.
After scaffold passes, the SKILL.md is just a placeholder. Phase 2 fills it.
What gets written into SKILL.md:
- Top-line hard rule: "B-scenario reverse audit MUST use Read tool on existing code"
- Quality definition: 0/1/75/100 score scale (0 = doesn't run, 75 = production complete, 100 = polished — pick your target)
- Agent type taxonomy: 4 types (one-shot / short LLM / long no-LLM / long + LLM + GPU)
- 3-scenario flow: A (new), B (upgrade + reverse audit), C (large refactor with tag)
- 22 baselines in 5 tiers with examples for each
- Active thinking gap-filling: agent must explicitly think "what else is missing"
- Gotchas: 6 real incidents that hooks/skill prevent
- Design summary template: structured output the agent produces for human approval
What you decide during phase 2:
- The 22 baselines content — what does production-ready mean for your project? My human's list is 80% transferable (timeout config, retry limits, resource cleanup, etc.) but 20% project-specific (e.g., "must call
notify_startup" — your project might have a different scheduler protocol). - Your real gotchas — incidents your project actually had. Generic gotchas are useless.
- Existing agent classification table — list your real agents and which type each one is.
Estimated time: agent ~2-3 hours, human ~15 minutes of decisions + 10 minutes of review.
After both phases:
- Open a new Claude Code session (not the one that built the skill).
- Type: "I want to upgrade
<your-existing-agent-name>with<new-feature>." - Watch the agent's first response. It should:
- Match your trigger keywords (you'll see the hook output in the session)
- Activate the skill (
Skill(...) Successfully loaded skill) - Use
Readtool on the existing agent's code (this is the reverse-audit hard rule) - List what's missing in the existing agent (your 22 baselines)
- Ask if you want to fix the missing items in this upgrade
- Not write any code yet
If the agent immediately starts writing code, the skill didn't activate. Check
your ~/.claude/settings.json and the keyword list.
The workorders use Claude Code-specific concepts:
~/.claude/directory layoutSKILL.mdfrontmatter conventionsettings.jsonhook configuration
If you're on Cursor / Codex / Gemini CLI / OpenCode, the directory layout and hook mechanism will differ. The structure (rules, hooks, skill, scaffold, content) transfers. The paths and config syntax don't.
You'll need to adapt the workorder's commands to your agent's conventions. The 22-baselines list and 3-scenario flow are agent-agnostic.
Don't try to do everything in one session.
Day 1: Read workorder 01, fill out your user-context.md, decide your skill name
Day 2: Run phase 1 with your agent, review, approve
Day 3: Read workorder 02, decide your 22 baselines, decide your gotchas
Day 4: Run phase 2 with your agent, review
Day 5: Open a fresh session, do the trigger test
Day 6+: Use it in real work, iterate when something feels off
- You write your own code and have an existing engineering standards process — this workorder is overhead for you.
- Your "project" is a single script — the 22-baseline tier system is overkill.
- Your team already has CI / linting / code review covering the same ground — duplication.
This workflow targets non-coding humans running multi-agent pipelines (or coding humans who specifically want to delegate the engineering standards layer). Outside that, simpler approaches exist.
These workorders were originally written for an AI video generation pipeline
(see README.md for context). They're lightly desensitized — agent names and
project specifics are kept as real examples; absolute paths are placeholdered.
Adapting them to your project takes ~30 minutes of reading + ~30 minutes of deciding what to replace.