bama
BAMA: Build Any Mac App. Agent skills to research, clone, design, build, optimize, and test native macOS apps with Swift and SwiftUI.
翻译准备中
Portable Agent Skill for evidence-based Android, Linux, and Chromium Perfetto analysis.
翻译准备中
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Portable Agent Skill for evidence-driven Android, Linux, and Chromium Perfetto performance analysis. It packages SmartPerfetto's domain workflows, SQL, capability gates, identity/evidence rules, and deterministic Skill runner without requiring the SmartPerfetto backend, UI, provider runtime, or MCP server. The Android Performance Ecosystem brings its navigation Hub and seven core projects into an optional path from instrumentation and capture to analysis, system knowledge, and reproducible cases. [README 설치·사용 부분 발췌] Install查看完整 README ↗
Portable Agent Skill for evidence-driven Android, Linux, and Chromium Perfetto performance analysis. It packages SmartPerfetto's domain workflows, SQL, capability gates, identity/evidence rules, and deterministic Skill runner without requiring the SmartPerfetto backend, UI, provider runtime, or MCP server.
The Android Performance Ecosystem brings its navigation Hub and seven core projects into an optional path from instrumentation and capture to analysis, system knowledge, and reproducible cases.
| Stage | Project | Purpose | Address |
|---|---|---|---|
| Navigate | Android Performance Ecosystem | Maintain the shared project map, handoff metadata, generated README navigation, and drift checks. | GitHub |
| Instrument | TraceFix | Inject app-side android.os.Trace sections at build time so method work is visible at runtime. | GitHub |
| Capture and measure | Perfetto Tools | Capture repeatable Perfetto traces and collect FPS or Simpleperf measurements. | GitHub |
| Analyze | SmartPerfetto | Investigate traces with an AI-assisted Web UI, CLI, reports, sessions, comparisons, and evidence workflow. | GitHub |
| Agent analysis | Perfetto Skills | Give agents a portable Perfetto analysis Skill for Android, Linux, and Chromium, with selected assets synchronized through pinned workflows. | GitHub |
| Learn | Android Performance Blog | Teach Perfetto and Systrace analysis through articles, system explanations, and case studies. | AndroidPerformance.com · GitHub |
| System knowledge | Android Internal Wiki | An alpha knowledge base for Android mechanisms from App to Framework, Native, and Kernel. | GitHub |
| Reproduce | Trace for Blog (SystraceForBlog) | Provide the Perfetto, Systrace, and related case files used by articles for hands-on reproduction. | GitHub |
These projects are complementary. Pick the smallest surface that matches how you want to work; none is a prerequisite for another.
| Project | Form | Best for | Main boundary | Choose it when |
|---|---|---|---|---|
| SmartPerfetto | Full Web UI, CLI, and backend | End-to-end interactive Android investigations | Managed Skill runtime, reports, sessions, comparisons, and provider integration | You want a complete analysis product |
| Perfetto Skills | Portable standard Agent Skill | Local agents with filesystem and terminal access | Deterministic local runner, evidence contracts, and broad analysis workflows | You want trace analysis inside Codex, Claude Code, or OpenCode |
| Google official Perfetto Skill | Official upstream Agent Skill bundle | Upstream-first trace recording and analysis | Official recording, memory, GPU, and ad-hoc PerfettoSQL guidance | You want the smallest upstream-maintained starting point |
See Google's official Perfetto AI usage guide for the upstream Skill installation and release model.
Yes. skills/perfetto-performance-analysis/SKILL.md follows the
Agent Skills specification, including
standard frontmatter and progressive references. The specification defines the
Skill directory and metadata; it does not prescribe an installer.
The commands below use Vercel Labs' ecosystem skills CLI as the recommended
convenience installer. tools/install.py remains an offline/release-archive
fallback. The official Perfetto Skill is used only as a gap-checking reference;
it is neither an install nor runtime dependency.
The verified CLI version is 1.5.16. Project installs are visible only in the
current project; add -g for a user-level install.
Inspect the repository without installing:
npx [email protected] add Gracker/Perfetto-Skills --list
Install for Codex, Claude Code, and OpenCode in the current project:
npx [email protected] add Gracker/Perfetto-Skills \
--skill perfetto-performance-analysis \
-a codex -a claude-code -a opencode -y
Install globally:
npx [email protected] add Gracker/Perfetto-Skills \
--skill perfetto-performance-analysis \
-a codex -a claude-code -a opencode -g -y
Verify, update, or remove:
npx [email protected] list --json
npx [email protected] update perfetto-performance-analysis
npx [email protected] remove perfetto-performance-analysis -y
For an extracted release archive, run one of:
python3 tools/install.py --client codex
python3 tools/install.py --client claude-code
python3 tools/install.py --client opencode
The fallback never overwrites an install unless --force is explicit. After
installation, refresh the client and ask it to use
$perfetto-performance-analysis on a local .pftrace file.
perfetto-performance-analysis router and 14 workflows.The SQL is not described as "official Perfetto SQL." It is SmartPerfetto SQL executed against a locked official Perfetto runtime. Queries without exact fixtures remain capability-gated or unverified, and cannot support a verified causal conclusion merely because they parse.
Requirements: Python 3.11+ and uv. Normal development downloads the immutable
Perfetto Skills fixture pack
and does not require a SmartPerfetto checkout.
uv sync --extra dev
uv run python tools/verify.py
Use --tier static, --tier unit, or qualified --test targets for scoped
iteration checks; see local verification.
Use uv run python tools/verify.py --offline for the committed real smoke
trace. These checks do not replace the default full gate before push.
SmartPerfetto is needed only for an explicit pinned import review; the
three upstream sync procedures and local SQL red-green workflow are documented
in upstream synchronization.
Generated runtime indexes are sharded by Skill so agents load only the selected workflow/query. See architecture, compatibility, and migration coverage.
Tagged releases contain reproducible .zip and .tar.gz bundles plus
SHA256SUMS. Trace processor executables and trace fixtures are not bundled.
The separately versioned fixture pack is a test asset, not an install/runtime
dependency of the Skill archive.
SmartPerfetto-derived work is AGPL-3.0-or-later; upstream Perfetto material
retains Apache-2.0. See LICENSE and NOTICE.