Pm

Project Manager

GitHub issue lifecycle: brainstorm, create, triage, audit, and review.

Sub-Skills

Usage

/pm                       → Create a new issue (interactive flow)
/pm -quick fix the login  → Create issue with smart defaults
/pm brainstorm caching    → Explore approaches before creating issues
/pm:brainstorm            → Same (alternate syntax)
/pm next                  → Triage: recommend next issue to work on
/pm:next                  → Same (alternate syntax)
/pm update                → Audit: find stale/orphaned issues
/pm:update                → Same (alternate syntax)
/pm review 42             → Review: validate issue #42 against codebase
/pm:review 42             → Same (alternate syntax)

Routing

Parse the first argument:

If routed to a sub-skill, invoke it with Skill and pass remaining arguments. If the first argument is -quick, skip the Ambiguity Check and go directly to the Create Issue Workflow (quick mode is an explicit signal that the user wants fast issue creation, not brainstorming). Otherwise, continue with the Ambiguity Check below.

Ambiguity Check

Before starting the Create Issue Workflow, check for existing specs and assess readiness.

Check for existing specs. Use Glob to find specs in .dev/pm/specs/*.md, then Read the most recent candidates to check topic relevance and status. If multiple specs match, prefer the most recent by date prefix in the filename. If a spec exists that matches the user's topic and its status is Approved, use it as primary context for the Create Issue Workflow — the brainstorming was already completed. Skip the ambiguity check and proceed directly. If the matching spec's status is Draft (or missing), do not bypass ambiguity handling — the brainstorm hasn't been approved yet. Continue with the assessment below.

Assess ambiguity. If no matching Approved spec exists, check for these ambiguity signals:

If two or more signals are present, suggest brainstorming before issue creation:

Question: "This sounds like it could benefit from brainstorming before creating issues —
there are multiple approaches and the scope isn't fully defined yet. Want to explore first?"
Options:
  - Yes, brainstorm first (/pm:brainstorm) — explore approaches and produce a spec
  - No, create the issue directly — I know what I want

If the user chooses brainstorming, invoke /pm:brainstorm with the original request as arguments; otherwise (user chose to proceed directly, or fewer than two signals present), continue with the Create Issue Workflow below.

Do NOT block on this check — it is a recommendation, not a gate. Clear requests like "fix the login crash" or "add a health check label" should flow straight through without asking.

Create Issue Workflow

Create structured GitHub issues optimized for LLM agent execution first, human readability second.

Every issue produced by this skill follows the Agent-Optimized Issue Format — structured sections with consistent headers, machine-parseable acceptance criteria, explicit file paths, verification methods, and clear scope boundaries.

Activation

This skill activates when users want to create work items for an agent team. Recognize these signals:

Arguments

Usage: /pm -quick add a delete button to user profiles

Parse the first argument for -quick. If present, activate quick mode. Everything after the flag is the task description.

Core Workflow

1. Classify → 2. Discover → 3. Challenge → 4. Explore Codebase → 5. Draft → 6. Review → 7. Create

Step 1: Classify Issue Type

Use AskUserQuestion to determine the issue type:

Question: "What type of work is this?"
Options:
  - Bug: Something is broken or behaving incorrectly
  - Feature: New functionality or enhancement to existing behavior
  - Epic: Large initiative requiring 3+ coordinated tasks
  - Refactor: Improve code structure without changing behavior
  - New Project: Build something from scratch (includes tech stack decisions)
  - Chore/Research: Maintenance, dependency updates, spikes, investigations

If the user's initial message already makes the type obvious (e.g., "there's a crash when..."), skip this step and classify automatically. State your classification and proceed.

Step 2: Type-Specific Discovery

Run the question flow for the classified type. See references/WORKFLOWS.md.

Key principles:

• Use AskUserQuestion for structured choices (max 4 questions per call, 2-4 options each)
• Use follow-up conversation for open-ended details
• Batch related questions together to minimize round-trips
• If user says "you decide" or similar, make a reasonable choice and note it as [AGENT-DECIDED: rationale]
• Mark gaps as [NEEDS CLARIFICATION: question] — don't guess on ambiguous requirements
• Never accept vague requirements. Before moving to the next step, critically examine every requirement for specificity. If a user says "add a button", ask: Where? What states? What action? If a user says "fix the bug", ask: What exact behavior? What's expected vs actual? What triggers it? Treat every underspecified detail as a blocker.

Step 3: Requirements Challenge

After discovery, systematically check for underspecified requirements. See the Requirements Challenge Checklist in references/WORKFLOWS.md for the full dimension list.

Default mode (critical):

1. Analyze gathered requirements against the challenge checklist dimensions
2. Identify every gap — placement, states, behavior, edge cases, error handling, accessibility
3. Use AskUserQuestion to probe each gap (batch related questions, max 4 per call)
4. Do NOT proceed to codebase exploration until all critical ambiguities are resolved
5. An agent executing the resulting issue should never need to guess intent

Quick mode (-quick):

1. Analyze gathered requirements against the same checklist dimensions
2. For each gap, propose a smart default with rationale
3. Present all assumptions in a single summary: "Here's what I'll assume: [list]. Confirm or correct?"
4. Proceed after one confirmation round — only block on truly ambiguous requirements where no reasonable default exists
5. Tag every assumed detail in the final issue body with [AGENT-DECIDED: rationale]

Example — "add a delete button to user profiles":

Critical mode:

I need to clarify several details before drafting:

• Where on the profile page should the button go? (header actions, settings section, footer)
• Who can see it? (all users, admins only, own profile only)
• What happens on click? (immediate delete, confirmation dialog, soft delete)
• What are the visual states? (default, hover, disabled, loading)
• What about error handling? (network failure, permission denied)

Quick mode (-quick):

Here's what I'll assume — confirm or correct:

• Placement: profile header action bar, right-aligned
• Visibility: own profile only, admins on any profile
• On click: confirmation dialog → soft delete → redirect to home
• States: default (red outline), hover (red fill), loading (spinner), disabled (greyed, no permission)
• Errors: toast notification with retry option

Step 4: Codebase Exploration

Before drafting, explore the codebase to enrich the issue with concrete details:

1. Discover: Use the Explore agent to survey the codebase for structure, conventions, and relevant areas. For large or unfamiliar codebases, use repomix-explorer (if available) to get a structural overview.
2. Target: Use Glob, Grep, and Read to drill into specific files identified during discovery — find files that need modification, understand current patterns, check for related work (TODOs, existing tests, related components), and verify that proposed changes don't conflict with existing code.

This step is critical — agents executing the issue will perform better with accurate file paths and pattern-aware implementation hints.

Step 5: Draft the Issue

Use the appropriate template from references/TEMPLATES.md.

Agent-first formatting rules:

1. Sections are contracts — every section header means something. Agents parse them.
2. Acceptance criteria are tests — write them as verifiable assertions: VERIFY: [condition]
3. File paths are absolute from repo root — src/auth/login.ts, not "the login file"
4. Approach is sequential — numbered steps an agent follows linearly
5. Scope is explicit — "In Scope" and "Out of Scope" prevent agents from over-engineering
6. Dependencies are linked — Blocked by: #N and Blocks: #N
7. Constraints are non-negotiable — performance targets, backwards compatibility, etc.

Write the draft to a temp file: /tmp/issue-body.md

Step 6: Review

Present the draft to the user with a summary:

• Title
• Type and labels
• Key acceptance criteria
• File scope

Ask: "Ready to create this issue, or want to adjust anything?"

For epics: also present the sub-issue breakdown before creating.

Step 7: Create

Size label selection (before creating the issue):

Applies to: Feature, Epic sub-issue, New Project sub-issue, Refactor. Skips: Epic parent, New Project, Bug, Chore, Research.

Determine the size label deterministically from analysis already gathered in earlier steps.

Features — derive from Step 2 breadth signals and Step 3 structural change detection:

Refactors — use target area from Refactor Flow Round 1, Question 2:

Epic sub-issues — derive from the decomposition table columns (Subsystems and Structural Changes recorded during Round 2 decomposition):

New Project sub-issues — use the same decomposition-based sizing as Epic sub-issues.

size/XL is intentionally excluded — work at that scale is always decomposed into an Epic with independently sized sub-issues.

# With size label (Feature, Epic sub-issue, New Project sub-issue, Refactor):
gh issue create --repo OWNER/REPO \
  --title "<type-prefix>: <description>" \
  --body-file /tmp/issue-body.md \
  --label "<type-label>,<size-label>"

# Without size label (Bug, Epic parent, New Project parent, Chore, Research):
gh issue create --repo OWNER/REPO \
  --title "<type-prefix>: <description>" \
  --body-file /tmp/issue-body.md \
  --label "<type-label>"

Title prefixes by type:

On failure: Save draft to /tmp/issue-draft-{timestamp}.md, report error. On success: Remove the temp file: rm -f /tmp/issue-body.md

For epics and new projects with sub-issues: create the parent issue first, then each sub-issue with Part of #PARENT_NUMBER in its body. After creating each sub-issue, formally link it to the parent via GitHub's Sub-Issues API so the parent's sidebar tracks completion progress:

# Get the sub-issue's REST ID (integer) and link it to the parent
sub_issue_id=$(gh api "repos/OWNER/REPO/issues/SUB_NUMBER" --jq .id)
gh api "repos/OWNER/REPO/issues/PARENT_NUMBER/sub_issues" \
  --method POST -F "sub_issue_id=$sub_issue_id"

Use -F (capital F) for sub_issue_id — the API requires an integer, and -F sends it as a number while lowercase -f would send a string, causing a type error.

If either the sub_issue_id lookup or the POST to /sub_issues fails for a sub-issue (rate limit, plan doesn't support sub-issues, permissions), log the error and continue to the next sub-issue — don't abort the loop. Skip the POST if the ID lookup failed. The Part of #N markdown reference still provides a human-readable cross-reference even if the API link fails.

Clean up /tmp/issue-body.md only after all sub-issue creation and linking attempts have completed, even if some links failed.

Report all created issue URLs to the user.

Quality Checklist

Before creating any issue, verify:

• Title is concise and action-oriented (imperative mood)
• Acceptance criteria are testable — not vague ("improve performance" → "response time < 200ms")
• Implementation hints reference real files found via codebase exploration
• Scope boundaries are explicit (In/Out of Scope sections present and populated)
• Single story: issue contains exactly one independent user journey (not 2+ bundled stories)
• Subsystems: Complexity Hint lists the distinct systems touched (Feature/Sub-Issue only)
• Structural changes: Complexity Hint declares whether structural changes are needed (Feature/Sub-Issue only)
• Dependencies are identified and linked
• No external context required — issue is self-contained
• Uncertainty is marked with [NEEDS CLARIFICATION: ...]
• Agent-decided items are marked with [AGENT-DECIDED: rationale]

Duplicate Check

Before creating, always search for existing issues:

gh issue list --search "keywords" --state all --limit 10

If similar issue exists → inform user, suggest linking instead of duplicating.

Repo Detection

Detect the current repo automatically:

gh repo view --json nameWithOwner -q .nameWithOwner

If not in a git repo or no remote → ask user for the target repo.

Templates & Workflows

• references/WORKFLOWS.md — Type-specific question flows
• references/TEMPLATES.md — Agent-optimized issue templates