一键导入
review-perf
Performance review. Detects project type and dispatches compute and/or web performance reviewers. Advisory only — no changes made.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Performance review. Detects project type and dispatches compute and/or web performance reviewers. Advisory only — no changes made.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Autonomous technical lead. Takes commander's intent and drives a project to completion through an OODA loop over implementation, refactoring, review, and bug-hunting skills. Has broad authority — creates tickets, commits, invokes any skill — and only escalates via andon cord for irreversible actions, public releases, or genuinely blocking decisions. User acts as product owner; skill acts as tech lead.
Cuts a project release. Discovers the project's release procedure (Makefile target, RELEASING.md, CI workflow, etc.) and offers to capture it durably if missing. Always invokes /review-release as preflight, proposes a version bump from CHANGELOG, then presents an exact command plan for operator confirmation before executing step-by-step. Halts on first failure rather than attempting rollback.
Pre-release readiness review. Scans for debug artifacts, version mismatches, changelog gaps, git hygiene issues, breaking changes, and license compliance. Runs tests and build verification. Presents consolidated findings for human review before release.
Proactive bug-hunting workflow. Assesses codebase risk through complexity, coverage, and structural analysis, then spawns focused investigators that write reproducing tests to validate suspected bugs. Thoroughness over speed. Advisory only — produces findings and proposes tickets; does not implement fixes.
Autonomous bug-elimination loop. Iteratively invokes /bug-hunt and /implement-batch until findings converge below an operator-specified severity floor. At termination, runs /review-test scoped to the run's new reproducing tests and fixes quality issues above the floor. Auto-approves /bug-hunt and /review-test ticket proposals; pulls the andon cord on contested findings, repeated implementation failure, hard-cap exhaustion, or breaking-change proposals. Optional /refactor finisher.
Autonomous comprehensive refactoring. Three-phase pipeline — Phase 1 /refactor (tactical, loops internally to convergence) → Phase 2 loop of /review-arch + /implement-batch until architectural findings converge below a severity floor (default HIGH+) → Phase 3 /refactor (catches tactical issues introduced by restructuring). Auto-approves /review-arch ticket proposals; pulls the andon cord on contested findings, breaking-change proposals, repeated implementation failure, or Phase-2 hard-cap exhaustion (5 architectural iterations).
| name | review-perf |
| description | Performance review. Detects project type and dispatches compute and/or web performance reviewers. Advisory only — no changes made. |
| model | opus |
Advisory-only performance review. Detects whether the project contains web content, non-web source code, or both, and dispatches the appropriate performance reviewer(s). No changes are made.
Measure, don't guess. Performance intuitions are unreliable. The reviewers identify structural issues and recommend what to measure, not just what to optimize.
Two domains, one workflow. Compute performance (algorithms, memory, CPU) and web performance (network latency, caching, asset delivery) are fundamentally different disciplines. This skill dispatches the right specialist(s) for the project rather than applying one lens to everything.
Diagnostic, not therapeutic. This skill identifies performance problems and recommends fixes. It does not implement them. Ask for changes directly after reviewing the findings, or use /implement with the review as context.
┌──────────────────────────────────────────────────────┐
│ PERFORMANCE REVIEW │
├──────────────────────────────────────────────────────┤
│ 1. Detect project type (web, non-web, or both) │
│ 2. Determine scope │
│ 3. Dispatch performance reviewer(s) │
│ 4. Present consolidated report │
└──────────────────────────────────────────────────────┘
Scan the project for source files to determine what performance domains apply.
Web indicators (any of these → dispatch web reviewer):
| Indicator | Signal |
|---|---|
.html, .htm, .jsx, .tsx, .vue, .svelte | Strong |
package.json with web framework (react, vue, next, nuxt, astro, etc.) | Strong |
webpack.config.*, vite.config.*, next.config.* | Strong |
.css, .scss, .less files (more than a few) | Moderate |
_headers, _redirects, vercel.json, netlify.toml | Moderate |
Service worker files (sw.js, service-worker.js) | Strong |
Non-web indicators (any of these → dispatch compute reviewer):
| Indicator | Signal |
|---|---|
.go, .rs, .c, .cpp, .java, .py, .rb, .zig source files | Strong |
Existing benchmarks (*_bench*, Benchmark in test files, criterion) | Strong |
| Database query code (SQL files, ORM usage) | Moderate |
| Data processing pipelines (ETL, batch processing) | Moderate |
| CLI tool entry points | Moderate |
Full-stack projects will have both indicators — dispatch both reviewers.
If neither is detected: Report "No performance-relevant source code detected in this project." and abort.
Present detected project type and ask the user:
Detected project characteristics:
- Web content: [Yes — N files / No]
- Source code: [Yes — N files in Go, Python, etc. / No]
Performance domains to review:
- [x] Web performance (caching, assets, loading strategy)
- [x] Compute performance (algorithms, memory, benchmarks)
What should I review?
- Both domains (default)
- Web performance only
- Compute performance only
- Specific directory/scope
Accept the user's selection. Default: all applicable domains, entire project.
Spawn the applicable reviewer(s) in parallel.
Web performance reviewer (if web content detected and not excluded):
Spawn a swe-web-perf-reviewer agent:
Review this project for web performance issues.
Scope: [scope]
Read all relevant files (HTML, CSS, JS, build configs, server configs)
and perform your full audit:
1. Detect tooling and environment (build tools, monitoring, server config)
2. Audit across all categories: caching, asset delivery, critical path,
resource loading, images, JavaScript cost, CSS efficiency, network
overhead, Core Web Vitals risk factors
3. Classify every issue by severity (CRITICAL / HIGH / LOW)
Produce your standard output format with summary, issues by severity,
caching assessment, asset delivery assessment, and tooling recommendations.
Compute performance reviewer (if non-web source detected and not excluded):
Spawn a swe-perf-reviewer agent:
Review this project for computational performance issues.
Scope: [scope]
Read all source files within scope and perform your full review:
1. Scan for performance-critical code, existing benchmarks, and profiling
infrastructure
2. Assess benchmark coverage and quality
3. Identify optimization opportunities (algorithmic, memory, I/O,
concurrency)
4. Check for performance regressions and missing regression detection
Produce your standard output format with findings organized by priority.
Collect all agent responses. Present a consolidated report:
## Performance Review
Scope: [what was reviewed]
Domains reviewed: [Web / Compute / Both]
### Web Performance
[web reviewer findings — or "Not applicable" if no web content]
Issues: N (X critical, Y high, Z low)
[merged findings by severity]
---
### Compute Performance
[compute reviewer findings — or "Not applicable" if no non-web source]
Issues: N (X critical, Y high, Z low)
[merged findings by severity]
---
### Cross-Cutting Concerns
[Your synthesis — issues that span both domains. For example:
- Server-side rendering that is both a compute bottleneck and a web loading issue
- API response times that are both an algorithmic problem and a network latency problem
- Database queries that affect both backend throughput and frontend time-to-interactive
If no cross-cutting concerns, omit this section.]
### Suggested Next Steps
[Based on findings:
- If critical/high issues found: recommend fixing them, noting which
domain each belongs to
- If no significant issues: "No significant performance issues found"
- If missing tooling: recommend specific tools (Lighthouse, benchmarking
frameworks, profiling tools)]
The cross-cutting section is your synthesis. Don't just concatenate the two reviewer outputs — look for issues that span both domains.
Abort:
Do NOT abort: