القائمة
Diagnose and fix performance issues by measuring before optimizing. Establishes baselines, identifies bottlenecks through call graphs and complexity analysis, then confirms improvements with numbers. Use when asked to optimize, speed up, reduce memory usage, or fix slowness.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | debug-performance |
| description | Diagnose and fix performance issues by measuring before optimizing. Establishes baselines, identifies bottlenecks through call graphs and complexity analysis, then confirms improvements with numbers. Use when asked to optimize, speed up, reduce memory usage, or fix slowness. |
| compatibility | Requires tokenlean CLI tools (npm i -g tokenlean) and git |
Find and fix performance bottlenecks by measuring, not guessing.
Measure → Identify → Analyze → Optimize → Confirm
Establish a baseline before touching anything:
tl parallel \
"baseline=tl run '<benchmark or timed command>'" \
"complexity=tl complexity <file>" \
"hotspots=tl hotspots"
Find the actual bottleneck:
tl parallel \
"flow=tl flow <function> <file>" \
"deps=tl deps <file>" \
"symbols=tl symbols <file>"
Understand why it's slow:
tl parallel \
"snippet=tl snippet <function> <file>" \
"related=tl related <file>" \
"scope=tl scope <function> <file>"
Apply the fix based on the bottleneck type:
# Algorithmic change
tl flow <function> <file> # Verify new path is simpler
# Caching opportunity
tl impact <file> # How many callers benefit?
# Reducing I/O
tl deps <file> # Identify unnecessary imports
# Parallelization
tl flow <function> <file> # Confirm no shared state
tl run "<same benchmark>" # Measure improvement — no numbers, no claim
"It's slow" → Do you have a measurement?
├─ Yes (specific operation) → tl flow on that operation
│ → tl snippet on each function in chain
│ → Find the O(n^2) or blocking I/O
├─ Vague ("app is slow") → tl hotspots + tl complexity
│ → Profile top 3 complex files
│ → tl flow on entry points to find hot paths
└─ Memory issue → tl deps on entry point
→ Look for large imports, circular refs
→ tl guard for circular deps
tl complexity > 10 on a function is a red flag for performance problemstl deps for heavy imports that could be lazy-loadedtl flow to confirm the function is on the hot pathtl parallel for all context-gathering steps — they're independentFind duplicate functions and eliminate them so they stay gone. Triage tl dupes output by tier, apply the right consolidation pattern, and lock the win with a duplication-ratchet test. Use when asked to dedupe, remove duplication, consolidate copy-paste, clean up repeated helpers, or act on tl dupes output.
Find duplicate functions in Codex and remove them so they stay gone — triage tl dupes by tier, consolidate the second home (not both copies), and add a duplication-ratchet test to block regressions. Use when deduping, removing copy-paste, consolidating repeated helpers, or acting on tl dupes output.
Git commits, pushes, and GitHub operations using tokenlean. Covers tl push (with multi-file safety guard), tl commit-prep, tl gh (bulk issue/PR/release operations), and when to use tl gh vs gh CLI vs GitHub MCP. Use when committing, pushing, creating/closing/viewing issues, managing PRs, creating releases, or any git/GitHub workflow.
Git commits, pushes, and GitHub operations using tokenlean. Covers tl push (with multi-file safety guard), tl commit-prep, tl gh (bulk issue/PR/release operations). Use when committing, pushing, creating/closing/viewing issues, managing PRs, creating releases, or any git/GitHub workflow.
Add new functionality by understanding existing patterns and dependencies before writing code. Locates where the feature belongs, studies conventions, implements following precedent, then verifies integration. Use when asked to add a feature, flag, endpoint, component, or module.
Thorough code review using token-efficient context gathering. Analyzes PRs, diffs, or staged changes by checking blast radius, complexity, and dependencies before reviewing the actual code. Use when asked to review a PR, review changes, or do a code review.