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generate-docs.py learns the agent-launcher domain (5 hardcoded maps extended); regenerated docs tree: 343 skill pages / 96 agent pages / 122 command pages (561 total). mkdocs.yml nav gains the Agent Launcher skill section (7 pages), 4 cs-agent-* agent entries, and 8 /cs:* command entries; all nav targets verified to exist. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012FwXG6TqCXKZQvF4iD69cv
63 lines
2.8 KiB
Markdown
63 lines
2.8 KiB
Markdown
---
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title: "/cs-grill-pm — Slash Command for AI Coding Agents"
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description: "Matt Pocock-style interrogation of a delivery plan against the PM canon (Kanban Guide 2025, Vacanti, DORA 2025, EBM, Klein, GitLab async-first). One. Slash command for Claude Code, Codex CLI, Gemini CLI."
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---
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# /cs-grill-pm
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<div class="page-meta" markdown>
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<span class="meta-badge">:material-console: Slash Command</span>
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<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/2-claude-skills/tree/main/project-management/commands/cs-grill-pm.md">Source</a></span>
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</div>
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Interrogate this plan — do not execute anything yet:
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**$ARGUMENTS**
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Five rules (preserved from Matt Pocock, MIT): one question per turn · always give a
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recommended answer · explore the workspace before asking · walk the decision tree
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depth-first · track answered questions and their dependencies.
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## Decision tree
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- **Branch 1 — Outcome**: "What single observable outcome means DONE, and which command
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proves it? Recommended: a named artifact + a command that exits 0 against it. Canon:
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agent-harness verifier's law."
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- **Branch 2 — Measurement**: "Are you measuring flow before forecasting? Recommended:
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run `jira_snapshot_bridge.py --to flow` first — WIP, throughput, cycle time, age.
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Canon: Kanban Guide (May 2025) four mandatory measures."
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- **Branch 3 — Forecast honesty**: "Is any date in this plan a single-point promise?
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Recommended: replace with Monte Carlo p50/p85 ranges; refuse forecasts on < 10
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completed items. Canon: Vacanti, *When Will It Be Done?*"
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- **Branch 4 — Ownership**: "For every task an agent will execute: who is the human owner
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and who reviews? Recommended: name both now; `delivery_loop_gate.py` will refuse the
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plan otherwise. Canon: Linear agents model; Atlassian Rovo audit discipline."
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- **Branch 5 — Risk**: "Have you run a pre-mortem on this plan? Recommended: 30 minutes,
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'it's six months later and this failed — why?'; convert top clusters to owned risks.
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Canon: Klein, HBR 2007."
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- **Branch 6 — Budgets**: "What are the retry and iteration caps, and who reviews
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escalations? Recommended: 3 attempts/task, 12 iterations/goal, a named human. Canon:
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loop-library terminal states."
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Per-turn output format:
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```
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Q[i]/[total]: [precise question]
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Recommended: [answer + canon-cited rationale]
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(Confirm, or override?)
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```
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## Stop conditions
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- All branches resolved → invoke `/cs:pm` (question) or `/cs:pm-loop` (goal) with the
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locked decisions inlined.
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- User says "stop grilling, just run it" → run with unresolved branches flagged in the
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digest.
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- Abandoned → save the partial grill to `pm-grill-{timestamp}.md`.
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## Distinct from
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- `engineering/grill-me` — generic plan interrogation. This grills against the PM canon.
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- `/cs:pm` — routes; this refuses to route until decisions are locked.
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