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BF vercel-optimize

Audit deployed Vercel apps for cost and performance issues using metrics, project config, code scans, and version-aware recommendations.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 80 files body ≈ 4 300 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Audit deployed Vercel apps for cost and performance issues using metrics, project config, code scans, and version-aware recommendations.

As a process F 59/100 · Will not run — References files that are not bundled: references/doctrine.md, references/voice.md, references/observability-plus.md

AnalyzerInfrastructureData and analyticsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
97
Quality 40%
73
Run on models
none yet
Process rating
F
59/100
Will not run
References files that are not bundled: references/doctrine.md, references/voice.md, references/observability-plus.md
Tools and files w 18
0
When it triggers w 12
20
Result and completion w 14
40
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token lib/extract-claims.mjs:122
    High-entropy token-like string (may be an id, hash or a credential)
    if (ment…tch(rec)) {
  • low Secrets in code secret-high-entropy-token lib/extract-claims.mjs:375
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    function ment…tch(rec) {
    quoted

A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/doctrine.md
  • warning missing-ref reference to a missing file: references/voice.md
  • warning missing-ref reference to a missing file: references/observability-plus.md
  • warning missing-ref reference to a missing file: references/recommendations.md
  • warning missing-ref reference to a missing file: references/verification.md
  • warning missing-ref reference to a missing file: references/scoring.md
  • warning missing-ref reference to a missing file: references/scanner-patterns.md
  • warning missing-ref reference to a missing file: scripts/gate-investigations.mjs
  • note frontmatter-key unknown frontmatter key "risk"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "date_added"

Process rating: all ten parameters 59/100

Will not run. References files that are not bundled: references/doctrine.md, references/voice.md, references/observability-plus.md
  • 0Tools and files. 8 referenced file(s) missing: references/doctrine.md, references/voice.md, references/observability-plus.md
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4300 tokens
  • 100Steps. 64 steps
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 136: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 64 items
  • +4Has examples (16 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.