squid-plan

name	squid-plan
description	Turn a raw feature spec into an approved Tasks Plan — grill the spec, have the Product Architect groom draft tasks (+ optional ADR and glossary additions), then run ONE human gate that decides everything touching the repo: tasks + storage, ADR, glossary, worktree, and which build to run.
disable-model-invocation	true
argument-hint	<feature-spec | path/to/spec.md | tracker-ref>

Plan — feature spec → per-task files (+ optional ADR, + worktree)

Anchor a feature in shared understanding and prior decisions, then produce the artifact /squid-implement-night consumes. Nothing touches the repo until the human gate.

$ARGUMENTS is the raw feature spec — free-form text, a path to a spec file, or a tracker reference.

You are the orchestrator — a MANAGER. You drive the grilling, launch the Product Architect (PA), offer another grilling round and present the final plan, run the single human gate, set up the workspace, write the approved artifacts, and kick off the chosen build. You do NOT groom, write code, or implement anything yourself.

Read AGENTS.md first to confirm the active tracker mode (file → tasks/<NNN>-<slug>.md files; gh → one GitHub Issue per task).

Input: raw feature spec. Output: decided at the human gate — by default one tasks/<NNN>-<slug>.md per atomic task (status: pending, feature: <slug>; or one GitHub Issue per task) + optional applied glossary additions + an optional new ADR under docs/adr/ + branch feat/{slug} (in a new worktree or the current tree), then optionally the chosen build (/squid-implement-night or an /squid-implement-task loop). This is exactly what the downstream pipeline consumes.

---

Step 0 — Resolve the feature spec

If $ARGUMENTS is empty, ask the human for the feature (free-form, path, or tracker ref). Otherwise resolve it: cat a spec file, load a tracker record, or use free-form text. Surface the resolved spec back in one paragraph.

---

Step 1 — Grill the spec (Human ↔ /squid-grilling)

Before grooming, sharpen the raw spec with the human. Invoke the squid-grilling skill — interview the human relentlessly, one question at a time with a recommended answer, until scope, edge cases, non-goals, constraints, and any decisions that warrant an ADR are clear. Anchor the questions in what already exists: read docs/adr/ (settled decisions — don't re-open them) and docs/glossary.md (use its terms; flag any the spec uses differently) when present, and use the context7 plugin for authoritative library/API facts. Anything answerable by reading the codebase or those sources — explore instead of asking. The output is a grilled spec; carry it into Step 2.

---

Step 2 — PA grooms → DRAFTS the plan (no writes yet)

Launch ONE Product Architect. It drafts everything and hands it back as its final message — it writes nothing to disk; the orchestrator writes the approved artifacts into the chosen workspace in Step 5.

Agent(
  subagent_type="squid:product-architect",
  prompt="""Feature-level grooming. Read AGENTS.md first. Follow your feature-grooming role.
  Feature (grilled): {grilled spec from Step 1}.
  Decompose into atomic, independently-shippable tasks, numbered (NNN) in dependency order. For EACH task, draft the
  FULL tasks/<NNN>-<slug>.md content (`feature: {slug}`, `status: pending`) per the tracker-workflow spec.
  Also draft: (a) any new docs/glossary.md terms, and (b) IF the feature warrants non-obvious architectural decisions,
  ONE proposed ADR for the WHOLE feature per your ADR rule.
  DO NOT WRITE ANYTHING TO DISK — hand everything back as drafts; the human approves and the orchestrator writes them.
  Use the context7 plugin for authoritative library/API usage wherever the feature touches an external framework.
  Return: (1) the ordered task files with their full content, (2) the glossary additions (or 'none'), (3) the proposed
  ADR draft (or 'none')."""
)

Verify before the gate: the drafts are atomic, ordered by NNN in dependency order, and each has acceptance criteria. Re-launch the PA with the gap as feedback if not.

---

Step 3 — Offer another grilling round, then output the final plan (Human ↔ /squid-grilling)

Before /squid-plan moves toward implementation, give the human one explicit chance to sharpen further — then lock and show the final plan.

Ask once with AskUserQuestion: "Another grilling round to sharpen this, or is the plan final?" → More grilling / It's final.

• More grilling → re-invoke the squid-grilling skill on the points the drafts left open, feed the sharpened spec back to the PA (Step 2), and return here. Repeat until the human picks It's final. Keep it to genuinely-open questions — good: "should deleting an Order cascade to its line-items?"; bad: re-opening a settled choice like "maybe switch datastores after all" (that's a fresh /squid-plan, not another round).
• It's final → output the final plan in full so the human reads exactly what will be built before anything is written: every task (NNN — title, scope, acceptance criteria, out-of-scope), the glossary additions, and the proposed ADR. This is the human's last look before tasks are created — render it complete, not a teaser.

Why this step: catching a wrong-shaped plan on screen costs one more grilling round; catching it after tasks, a branch, and a build already exist costs the whole downstream pipeline.

---

Step 4 — HUMAN GATE (blocking)

This is the only gate, and it is mandatory. It decides everything that touches the repo. Recap the decision inputs, then ask:

Feature: {title}
Tasks ({N}):
  1. {NNN-slug} — {title}
  2. ...
Glossary additions: {M new terms, or "none"}
Proposed ADR: {ADR-NNNN "title" — 1-line summary, or "none"}
Task storage (project default): {file → local tasks/*.md | gh → GitHub Issues}   ← from AGENTS.md TRACKER_MODE

Then ask with AskUserQuestion. The decisions come in two back-to-back asks — still ONE gate, with no repo writes between them: Part 2 only matters once the plan is approved, and AskUserQuestion caps at four questions per call.

Part 1 — the plan and its artifacts (ask together, then act on Q1):

1. Approve the plan? — write these {N} tasks? → Approve / Edit / Cancel
2. Store the tasks where? — → Local files (tasks/<NNN>-<slug>.md, committed to the repo) / GitHub Issues (one issue per task). Pre-select the project default (AGENTS.md TRACKER_MODE) and mark it Recommended.
3. Create the ADR? — write the proposed ADR to docs/adr/? → Create / Skip (omit this question entirely if no ADR was proposed)
4. Update the glossary? — apply the {M} drafted term(s) to docs/glossary.md? → Apply / Skip (omit this question entirely if the PA drafted no glossary additions)

• Cancel → stop and discard the drafts; nothing has been written or branched. Do not ask Part 2.
• Edit → ask what to add / remove / reorder / re-split; re-launch the PA (Step 2); loop back to this gate.
• Approve → ask Part 2, then go to Step 5 carrying every answer.

Part 2 — workspace and build (only on Approve):

5. Workspace? — where should branch feat/{slug} live? → New worktree (isolated ../{repo}-{slug} dir) / Current working tree (branch in place)
6. Build now? — what runs after setup? → /squid-implement-night (end-to-end to a validated PR) / /squid-implement-task loop (build + commit the tasks only, no review/CI) / Stop after planning

---

Step 5 — Execute the decisions (only after the final plan + Approve)

Do these in order.

A. Set up the workspace (Q5).

• New worktree:

  git rev-parse --abbrev-ref HEAD          # expect main; if not, ask the human how to proceed
  git pull
  WORKTREE_PATH="$(git rev-parse --show-toplevel)/../$(basename $(git rev-parse --show-toplevel))-{slug}"
  git worktree add -b feat/{slug} "$WORKTREE_PATH" main
  

  If it already exists (re-running after an abort): tell the human, ask reuse (r) / recreate (d) — default reuse.
• Current working tree:

  git pull
  git switch -c feat/{slug}                # if already on a feat/* branch, reuse it instead
  

  WORKTREE_PATH = the repo root.

B. Write the approved artifacts into the workspace. Write to absolute paths under $WORKTREE_PATH (for a new worktree the orchestrator's cwd is still the main repo — do NOT write the tasks into main):

• Tasks (Q2). Local files → one $WORKTREE_PATH/tasks/<NNN>-<slug>.md per task (status: pending) from the Step 2 drafts. GitHub Issues → gh issue create one issue per task from the same drafts, in NNN order (titles NNN — {slug}, body = the groomed spec). The chosen mode is this feature's tracker for the rest of the pipeline; if it differs from AGENTS.md TRACKER_MODE, it's a one-off override for this plan — don't rewrite AGENTS.md.
• Glossary (Q4). If Apply: apply the drafted additions to $WORKTREE_PATH/docs/glossary.md. If Skip (or none were drafted): discard them.
• ADR (Q3). If Create: write $WORKTREE_PATH/docs/adr/NNNN-<slug>.md (Status: Accepted) from the ADR draft. If Skip: discard the draft.
• Verify: in Local files mode, ls "$WORKTREE_PATH/tasks" lists every expected file, each with status: pending + acceptance criteria; in GitHub Issues mode, gh issue list shows one issue per task. If anything is missing, write it now — do not hand off an empty plan.

C. Kick off the build (Q6).

• /squid-implement-night → invoke /squid-implement-night with: feature {slug}, Working directory: $WORKTREE_PATH.
• /squid-implement-task loop → invoke /squid-implement-task with: the feature's pending tasks (tasks/<NNN>-*.md, status: pending), Working directory: $WORKTREE_PATH.
• Stop after planning → hand off and stop:

  Plan approved. {N} tasks in tasks/ (status: pending) on `feat/{slug}` ({worktree at $WORKTREE_PATH | current working tree}).
  Next: run `/squid-implement-night` (builds every pending task to a validated PR), or `/squid-implement-task` for individual tasks.
  

/squid-plan ends here.

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Notes

• Task-file shape: see the tracker-workflow spec (squid-scaffold/specs/tracker-workflow.md); ADR rules live in the product-architect agent contract.