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android-performance

Gather and interpret Android performance evidence on an adb target using Simpleperf CPU profiles, Perfetto or Compose traces, gfxinfo frame data, dumpsys meminfo snapshots, Java heap dumps, and native allocation traces. Use when asked to profile an Android app flow, find CPU-heavy functions, diagnose jank, capture startup or frame timing evidence, compare before/after performance, explain what code is taking time, or gather memory/leak profiling artifacts.

73

Quality

90%

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SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A dense, command-first skill body with genuinely executable guidance, strong preflight/fallback validation loops, and correct delegation of report generation to bundled scripts. The main improvements are trimming long inline shell scaffolding and splitting per-tool interpretation detail into reference files.

Suggestions

Move the multi-line shell scaffolding (the trace-file stable-size polling loop, the ARTIFACT_DIR setup) into the bundled scripts so SKILL.md keeps one-line invocations, reducing token cost without losing actionability.

Extract the 'Reading Simpleperf' interpretation guide and the Perfetto inspection checklist into references/ files (e.g., references/interpreting-simpleperf.md, referenced one level deep), keeping SKILL.md as the trace-type decision and capture overview.

Consolidate the repeated 'wait until the output file exists and its size is stable' warnings into one stated invariant applied to all trace pulls.

DimensionReasoningScore

Conciseness

Almost every section is commands plus terse, domain-specific caveats (sampled-vs-wall-clock limits, heapprofd buffer health) that Claude would not reliably know, so it is not verbose in the rubric's sense. Not 5 because some blocks could be tightened — e.g., the ~20-line inline file-size polling loop and repeated warnings about pulling stable trace files.

4 / 5

Actionability

Fully executable copy-paste bash for every capture path: simpleperf record/stop/pull, the bundled report scripts with arguments, Perfetto background + flush-wait + pull, gfxinfo reset/framestats, am dumpheap + shark-cli, and a complete heapprofd config. Placeholders (SERIAL, PACKAGE, ARTIFACT_DIR, SKILL_DIR) are all defined, and the '...when supported by the installed Simpleperf' hedges are explicitly justified tool-availability notes, not pseudocode.

5 / 5

Workflow Clarity

The 5-step Core Workflow is sequenced per tool with explicit validation checkpoints and recovery loops: preflight 'dumpsys package ... grep DEBUGGABLE|profileable', the 'Operation not permitted' → Ctrl-C fallback, 'discard that capture' rule for gfxinfo on ANR screens, wait-for-stable-size before pulling traces, and the final Report checklist with caveats and next-step guidance. Not 4: checkpoints are explicit, not implicit.

5 / 5

Progressive Disclosure

Scored against the actual bundle (scripts/simpleperf_hotspots.sh and scripts/heapprofd_reports.sh — both exist and are referenced with full invocation lines and expected outputs), and the cross-skill pointer to ../android-emulator-qa/SKILL.md is clearly signaled. Not 5: the SKILL.md carries ~280 lines with all per-tool interpretation detail inline; the 'Reading Simpleperf' guidance and Perfetto inspection notes are candidates for references/ files, and there is no references/ tier at all.

4 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is a strong example: concrete multi-tool capability list in third person, with an explicit and broadly phrased 'Use when' trigger clause. Only gap is a handful of natural synonyms (slow/laggy app, optimize) that would widen trigger matching.

DimensionReasoningScore

Specificity

Names the domain (Android performance on an adb target) and enumerates multiple concrete evidence types — 'Simpleperf CPU profiles, Perfetto or Compose traces, gfxinfo frame data, dumpsys meminfo snapshots, Java heap dumps, and native allocation traces' — matching the comprehensive-coverage anchor. It does not sit between anchors: score 4 ('minor gaps in coverage') would understate the tool-by-tool enumeration.

5 / 5

Completeness

Explicitly answers both: 'what' is gather and interpret Android performance evidence with a concrete tool list, and 'when' via 'Use when asked to profile an Android app flow, ... diagnose jank, ... or gather memory/leak profiling artifacts.' Matches the anchor example structure exactly; neither half is vague or implied.

5 / 5

Trigger Term Quality

Triggers like 'profile an Android app flow', 'find CPU-heavy functions', 'diagnose jank', 'compare before/after performance', and 'memory/leak profiling' are phrases users naturally say, but a few common variations are missing (e.g., 'app is slow/laggy', 'optimize performance', 'startup time'). Not 5 (no synonym/extension-level coverage such as '.hprof' or 'reduce battery/CPU usage'); clearly above 3 because most natural phrasings are present.

4 / 5

Distinctiveness Conflict Risk

A clear niche (Android device performance profiling via adb tooling) with tool-specific triggers ('Simpleperf', 'gfxinfo', 'jank', 'adb target') that no generic analysis or debugging skill would claim. Minimal overlap risk; not 4 because there is no closely related skill in this space whose triggers it shares.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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