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bolt

Optimizing frontend (re-render, memoization, lazy loading) and backend (N+1, indexing, caching, async) performance, plus continuous auto-tuning loops for GC/threadpool/cache/worker settings.

Quality

74%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./bolt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%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 strongly structured, information-dense skill body with an excellent validated workflow (PROFILE→VERIFY gates) and mostly concrete guidance. Its weaknesses are redundancy — a 30-line duplicated metadata comment, memoization rules repeated in four places, and stats-heavy padding — and a progressive-disclosure design whose entire reference layer is missing from the delivered bundle.

Suggestions

Delete or externalize the CAPABILITIES_SUMMARY/COLLABORATION_PATTERNS HTML comment (lines 6–35): it duplicates the body's Trigger Guidance, Collaboration, and Boundaries sections verbatim and costs ~30 lines of tokens per load.

Consolidate the React Compiler / manual-memoization rules, currently repeated in Trigger Guidance, Core Contract, the Never list, and Performance Domains, into the single Core Contract statement with one-line pointers elsewhere; likewise trim case-study statistics to the actionable rule.

Ship the referenced files: the body points to 15+ `reference/*.md` and `_common/*.md` files that are absent from the bundle, leaving the progressive-disclosure layer dangling; alternatively inline the few critical details and cut the pointers.

DimensionReasoningScore

Conciseness

The tables carry dense, non-obvious signal (thresholds, tool names, library sizes), but ~30 lines of HTML-comment metadata (CAPABILITIES_SUMMARY/COLLABORATION_PATTERNS) duplicate body content wholesale, the React Compiler/memoization rules repeat across four sections (Trigger Guidance, Core Contract, Never list, Performance Domains), and marketing stats ("12% faster initial loads", "Ray-Ban case study: 43% LCP improvement, 2× conversion rate") pad the prose. Mostly efficient but needs significant tightening; not 2 since it never explains concepts Claude already knows.

3 / 5

Actionability

Concrete, executable-direction guidance throughout: "`Promise.all` / parallel route loaders", "yield via `scheduler.yield()` (preferred over `setTimeout(0)`)", "`fetchpriority=\"high\"` + `loading=\"eager\"`", explicit gates (LCP ≤ 2.5s, break tasks > 50ms) and specific tools. As an instruction-only skill this is mostly actionable with minor gaps; not 5 because inline snippets like `lazy(→import('./pages/X'))` are shorthand and complete examples are deferred to reference files.

4 / 5

Workflow Clarity

The PROFILE → SELECT → OPTIMIZE → VERIFY → PRESENT table gives each phase a required action, key rule, and read-reference, with explicit validation checkpoints and feedback loops: "No captured baseline metric → STOP and profile first", "Must beat baseline — if it does not, revert and reselect", and lint+test before PR. This matches the anchor-5 example of clear sequencing with explicit validation and error-recovery loops.

5 / 5

Progressive Disclosure

References are one level deep and clearly signaled (Reference Map table, per-section "Full details → `reference/...`"), but the provided bundle contains no reference files at all — every one of the 15+ `reference/*.md` and `_common/*.md` paths is unverifiable/dangling — and deep content (CWV case studies, Speculation Rules detail, DB metrics) is inlined alongside that layer. The in-text structure exceeds anchor 3, but the absent reference layer is more than the "minor organization gaps" of anchor 4.

3 / 5

Total

15

/

20

Passed

Description

66%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.

A specific, jargon-appropriate description with good concrete actions and a distinct niche, but it omits any "Use when..." trigger clause, which both caps completeness and weakens its discoverability. It also under-represents the skill's actual scope (bundle, Core Web Vitals, memory, network) while claiming an auto-tuning capability the body does not cover.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user mentions slow pages, re-renders, N+1 queries, Core Web Vitals, bundle size, lazy loading, or performance profiling" — this would lift completeness from 3 to 5.

Align claimed scope with the body's real domains: add bundle-size reduction, Core Web Vitals (LCP/INP/CLS), memory footprint, and network delivery, and drop or substantiate the "continuous auto-tuning loops for GC/threadpool/cache/worker settings" claim, which the body never addresses.

Add a few user-natural synonyms such as "bundle size", "profiling", and "slow queries" to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "re-render, memoization, lazy loading", "N+1, indexing, caching, async", "GC/threadpool/cache/worker settings" — but coverage has gaps: the skill body's bundle-size, Core Web Vitals, memory-footprint, and network domains are absent, and the auto-tuning claim is not reflected in the body. Not a 5 (comprehensive coverage); clearly above 3 (only 1-2 actions).

4 / 5

Completeness

The "what" is specific and clear, but there is no "Use when..." clause or equivalent explicit trigger guidance anywhere in the description, which caps completeness at 3 per the judging guidelines. Not 2, because the "what" is concrete rather than vague.

3 / 5

Trigger Term Quality

Natural developer phrasings users would actually say ("N+1", "memoization", "lazy loading", "caching", "indexing") are present, but common variations like "bundle size", "Core Web Vitals", "profiling", "slow query", or "performance" are missing. Fits anchor 4 (good keyword coverage, a few natural terms missing) rather than 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

A clear performance-optimization niche with distinct technical triggers (N+1, memoization, GC/threadpool tuning), carrying only minor overlap risk with a dedicated database-tuning skill ("N+1, indexing"). Fits "mostly distinct; minor overlap risk" better than 5's "minimal conflict risk".

4 / 5

Total

15

/

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

simota/agent-skills

Path

bolt/SKILL.md

Reviewed

Table of Contents

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