Observe

Analyze how Claude Code is being used in this project and suggest new agents or skills that would reduce repetition, improve quality, or handle specialized domains — without duplicating what already exists.

• $ARGUMENTS: optional. Four modes:
  • Omitted — analyze the project's existing patterns and agents to generate suggestions proactively.
  • review — review the existing agent/skill roster for quality and gaps without suggesting new additions.
  • prune — evaluate the project memory file for stale, redundant, or verbose entries and apply a trimmed version.
  • Description of a recurring task — use the description as context when generating suggestions (e.g. "I keep doing X manually").

Step 1: Inventory existing agents and skills

Use the Glob tool to enumerate agents (pattern agents/*.md, path .claude/) and skills (pattern skills/*/SKILL.md, path .claude/).

For each agent/skill found, extract: name, description, tools, purpose.

Step 2: Analyze work patterns

If $ARGUMENTS is prune: skip Steps 2–5 entirely and go to "Mode: Memory Pruning" below.

If $ARGUMENTS is review: skip the git analysis below and go directly to Step 3 (Gap analysis). Use the agent/skill descriptions from Step 1 as the sole input — the goal is to assess quality and coverage of the existing roster, not to look for new patterns in recent work. In Step 5, suppress all "Recommend: New Agent/Skill" sections and output only "Existing Coverage", "Recommend: Enhance Existing", and "No Action Needed" entries.

Otherwise, look for signals of repetitive or specialist work. The first three git commands are independent — run them in parallel:

# --- run these three in parallel ---

# Recent git history — what kinds of changes are common?
git log --oneline -50

# What file types are being worked on?
git log --name-only --pretty="" -30 | sort | uniq -c | sort -rn | head -20

# Commit message patterns — what verbs appear most?
git log --oneline -100 | awk '{print $2}' | sort | uniq -c | sort -rn | head -15

Then use the Read tool on tasks/todo.md and tasks/lessons.md (if they exist) for task history and conversation hints.

If $ARGUMENTS was provided, use it as additional context for the pattern analysis.

Frequency Heuristics

• 3+ occurrences of a pattern in recent history → candidate for automation
• 2+ different projects using the same manual process → cross-project skill
• > 10 minutes of manual work per occurrence → high-value automation target
• Domain-specific knowledge required → candidate for a specialist agent (not just a skill)

Step 3: Gap analysis

For each identified pattern, check:

1. Is it already covered? — search existing agent/skill descriptions for overlap
2. Is it frequent enough? — recurring ≥ 3 times or clearly domain-specialized
3. Would a specialist add quality? — does it require deep domain knowledge?
4. Is it too narrow? — a single-use task doesn't warrant a persistent agent

Thresholds for recommendation:

• New agent: recurring specialist role, complex decision-making, 5+ distinct capabilities
• New skill: workflow orchestration, multi-step process with fixed structure
• No new file needed: one-off or already covered by existing agent

Step 4: Check for duplication

Before recommending anything, run through both the overlap check and the anti-pattern checklist:

For each candidate agent/skill:
- Does any existing agent cover >50% of its scope? → enhance existing instead
- Is the name/description confusingly similar to an existing one? → rename existing

Anti-pattern checklist — reject the candidate if any apply:

1. Role vs task confusion: agents are roles, not tasks. Do not create an agent for every different topic.
2. Near-duplicate: the candidate duplicates an existing agent with a slightly different name. Enhance the existing one instead.
3. Thin wrapper: the candidate skill just calls one agent with fixed args. That is not enough value to justify a new skill file. Exception: skills that add measure-first/measure-after bookends, multi-mode dispatch across 3+ agents, or safety breaks (retry limits, validation gates) justify the wrapper even if only one agent executes for a given invocation.

Step 5: Report

## Agent/Skill Suggestions

### Existing Coverage (no gaps found)
- [agent/skill]: covers [pattern] well — no new file needed

### Recommend: New Agent — [name]
**Trigger**: [what recurring pattern or gap justifies this]
**Gap**: [what existing agents don't cover]
**Scope**: [what it would do — 3-5 bullet points]
**Suggested tools**: [Read, Write, Edit, Bash, etc.]
**Draft description**: "[one-line description for frontmatter]"

### Recommend: New Skill — [name]
**Trigger**: [what repetitive workflow justifies this]
**Gap**: [why existing skills don't cover it]
**Scope**: [what workflow steps it would orchestrate]
**Draft description**: "[one-line description for frontmatter]"

### Recommend: Enhance Existing — [agent/skill name]
**Add**: [specific capability missing from current version]
**Why**: [what recurring task would benefit]

### No Action Needed
[pattern]: already handled by [existing agent/skill]

## Confidence
**Score**: [0.N]
**Gaps**: [e.g., git history too shallow, task files not present, descriptions too generic to compare]
**Refinements**: N passes. [Pass 1: <what improved>. Pass 2: <what improved>.] — omit if 0 passes

Mode: Memory Pruning (prune)

Locate, evaluate, and trim the project memory file.

Find the memory file:

PROJECT="$(git rev-parse --show-toplevel)"
MEMORY_FILE="$HOME/.claude/projects/$(echo "$PROJECT" | sed 's|/|-|g')/memory/MEMORY.md"
echo "$MEMORY_FILE"

Read the memory file with the Read tool. Also read .claude/CLAUDE.md to identify overlap — anything already covered in CLAUDE.md does not need to live in memory.

Evaluate each section against these criteria:

• Drop: content that is no longer accurate (removed features, resolved one-time issues, superseded decisions), or fully duplicated in CLAUDE.md
• Trim: sections still accurate but containing implementation history or rationale no longer needed day-to-day — keep operational facts (what/where), drop the why-it-was-built backstory
• Keep: rules actively applied every session; project-specific facts absent from CLAUDE.md; anything the model needs to act correctly

Apply changes with the Edit tool — targeted replacements for trimmed sections, full section removal for dropped ones.

Print a compact summary:

Pruned MEMORY.md — <date>
  Dropped: N sections — [names]
  Trimmed: N sections — [names]
  Kept:    N sections unchanged
  Saved:   ~N lines

End your response with a ## Confidence block per CLAUDE.md output standards.

• This skill is introspective: it looks at the tooling itself, not just the code

• Run periodically (e.g., monthly) or after noticing repetitive manual work

• Suggestions are proposals — always review before creating new files

• After creating a new agent/skill based on a suggestion, re-run this skill once to confirm the gap is resolved, then stop

• Agent Teams signal tracking: when reviewing patterns, also look for:

  • Skills using --team or team-mode heuristics more/less than expected → flag over/under-use relative to the decision matrix in CLAUDE.md § Agent Teams
  • Security findings appearing in reviews for non-auth code → suggests qa-specialist teammate scope is too broad; narrow it
  • Model tier mismatches (e.g., heavy analysis assigned to sonnet teammates) → flag for tier adjustment

• Follow-up chains:

  • Suggestion accepted for new agent/skill → /manage create to scaffold and register it
  • Suggestion to enhance existing → edit the agent/skill directly, then /sync