perf-profile

!bash "${CLAUDE_SKILL_DIR}/../../hooks/yaml-helper.sh" resolve_config --keys performance.enforce,automation

Resolved above — use as-is. No block → defaults in .claude/docs/config-resolution.md.

Every AskUserQuestion call follows .claude/docs/automation-modes.md (collaborative asks always · guided major-only · autonomous logs and proceeds; automation_always_ask categories always prompt).

Insufficient input — check this before producing any report

If the inputs this skill needs do not exist, the answer is "could not run" — not a filled-in report. Check first, and stop if the check fails.

1. List the inputs this skill reads (data files, prior reports, profiler output, test results, registries, source code).
2. For each, record FOUND or ABSENT — not "assumed present".
3. If any input required for a section is ABSENT, that section is NOT ASSESSED — NO DATA. Do not estimate it, do not infer it from an adjacent artifact, and do not leave a mandated cell to be filled by whoever reads the template next.
4. If every required input is ABSENT, stop and report NOT ASSESSED — NO DATA as the whole verdict, naming what was missing and which skill produces it.

A verdict of NOT ASSESSED is a success. It is the correct, useful answer to "what does the data say?" when there is no data. The failure mode this prevents is specific and has been observed in practice: report templates whose verdict enum had no "could not run" state produced false clean passes — an asset audit returning COMPLIANT on a project with no assets and no standards, and a performance profile reporting ">99% headroom against a 16.67ms budget" with zero profiler data and no budget ever set.

Absence of evidence is never evidence of absence. A scan that finds no matches because there are no files to scan has not verified anything. Say which of the two happened — a reader cannot tell from a green result.

Phase 0: Resolve Budget Enforcement

performance.enforce decides what a budget violation means in this run. It does not change which budgets are measured — performance.target_framerate, frame_budget_ms, draw_call_limit and memory_ceiling_mb are profiled the same way at every level:

Only warn, block and off are recognized. Surface any other value to the user and fall back to warn rather than guessing.

The value is locally overridable (/settings --local performance.enforce=block), so use the resolved block above rather than reading project.yaml — a teammate's stricter local setting is meant to bite on their machine only.

Phase 1: Determine Scope

Read the argument:

• System name → focus profiling on that specific system
• full → run a comprehensive profile across all systems

Phase 2: Load Performance Budgets

Read the committed budgets from config first — they are the project's record of what it agreed to, and design docs are the fallback, not the source:

source "${CLAUDE_PROJECT_DIR:-.}/.claude/hooks/yaml-helper.sh" 2>/dev/null
get_effective_yaml_key performance.target_framerate
get_effective_yaml_key performance.frame_budget_ms
get_effective_yaml_key performance.draw_call_limit
get_effective_yaml_key performance.memory_ceiling_mb

Written as four literal keys rather than a loop over leaf names, deliberately. The dead-settings audit matches the full dotted key, so a loop building performance.$k leaves three of the four spelled nowhere and the audit reports them DEAD while this skill reads them. Spell each key out in full.

Resolve these budgets from project.yaml, not from prose. Phase 0 above states these four budgets "are profiled the same way at every level". Sending the reader to "design docs or CLAUDE.md" instead means a user who set performance.target_framerate: 60 in project.yaml has it ignored by the one skill that profiles against budgets. The keys resolve correctly — this phase has to actually ask for them.

Then fall back to design docs or CLAUDE.md for anything config does not carry:

• Target FPS (e.g., 60fps = 16.67ms frame budget)
• Memory budget (total and per-system)
• Load time targets
• Draw call budgets
• Network bandwidth limits (if multiplayer)

A metric with no committed budget is NOT ASSESSED, not a pass. Do not measure against the template's [16.67ms] placeholder — an unset budget is not a budget that was met, and reporting headroom against a number nobody chose is the exact fabrication this skill's own header warns about.

Phase 3: Analyze Codebase

CPU Profiling Targets:

• _process() / Update() / Tick() functions — list all and estimate cost
• Nested loops over large collections
• String operations in hot paths
• Allocation patterns in per-frame code
• Unoptimized search/sort over game entities
• Expensive physics queries (raycasts, overlaps) every frame

Memory Profiling Targets:

• Large data structures and their growth patterns
• Texture/asset memory footprint estimates
• Object pool vs instantiate/destroy patterns
• Leaked references (objects that should be freed but aren't)
• Cache sizes and eviction policies

Rendering Targets (if applicable):

• Draw call estimates
• Overdraw from overlapping transparent objects
• Shader complexity
• Unoptimized particle systems
• Missing LODs or occlusion culling

I/O Targets:

• Save/load performance
• Asset loading patterns (sync vs async)
• Network message frequency and size

Phase 4: Generate Profiling Report

Write the report to production/polish/[scope]-report-[date].md, asking first per the Collaboration Protocol: "May I write this profiling report to production/polish/[scope]-report-[date].md?" Create the directory if absent.

Name the destination — do not just render the template into the conversation. A profile that lives only in the transcript is gone the moment the session ends, and no two runs can be compared. production/polish/ is the same location /team-polish writes, deliberately: a profile taken by either route belongs in one place, or the comparison this skill exists to enable cannot be made.

If a NOT ASSESSED section survives into the report, keep it in the written file. A profile whose gaps are edited out on the way to disk reads, later, as a complete measurement.

## Performance Profile: [System or Full]
Generated: [Date]

### Performance Budgets
| Metric | Budget | Estimated Current | Status |
|--------|--------|-------------------|--------|
| Frame time | [16.67ms] | [estimate] | [OK/WARNING/OVER] |
| Memory | [target] | [estimate] | [OK/WARNING/OVER] |
| Load time | [target] | [estimate] | [OK/WARNING/OVER] |
| Draw calls | [target] | [estimate] | [OK/WARNING/OVER] |

### Hotspots Identified
| # | Location | Issue | Estimated Impact | Fix Effort |
|---|----------|-------|------------------|------------|

### Optimization Recommendations (Priority Order)
1. **[Title]** — [Description]
   - Location: [file:line]
   - Expected gain: [estimate]
   - Risk: [Low/Med/High]
   - Approach: [How to implement]

### Quick Wins (< 1 hour each)
- [Simple optimization 1]

### Requires Investigation
- [Area that needs actual runtime profiling to confirm impact]

Output the report with a summary: top 3 hotspots, estimated headroom vs budget, and recommended next action.

Phase 5: Scope and Timeline Decision

Activate this phase only if any hotspot has Fix Effort rated M or L.

Present significant-effort items and ask the user to choose for each:

• A) Implement the optimization (proceed with fix now or schedule it)
• B) Reduce feature scope (run /scope-check [feature] to analyze trade-offs)
• C) Accept the performance hit and defer to Polish phase (log as known issue)
• D) Escalate to technical-director for an architectural decision (run /architecture-decision)

If multiple items are deferred to Polish (choice C), record them under ### Deferred to Polish.

This skill is read-only — no files are written. Verdict: COMPLETE — performance profile generated.

Phase 6: Next Steps

• If bottlenecks require architectural change: run /architecture-decision.
• If scope reduction is needed: run /scope-check [feature].
• To schedule optimizations: run /sprint-plan update.

Rules

• Never optimize without measuring first — gut feelings about performance are unreliable
• Recommendations must include estimated impact — "make it faster" is not actionable
• Profile on target hardware, not just development machines
• Static analysis (this skill) identifies candidates; runtime profiling confirms