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BF flights

Search flights via Google Flights. Find nonstop/connecting flights, filter by time and cabin class, get booking links. Supports city names (NYC, London, Tokyo) with automatic multi-airport search. No API key required.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 890 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Search flights via Google Flights.

As a process F 44/100 · Will not run — References files that are not bundled: scripts/flights-search

IntegrationSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
99
Quality 40%
69
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: scripts/flights-search
Tools and files w 18
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:14
    Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
    - **[uv](https://docs.astral.sh/uv/)** (recommended) — install with `curl -LsSf https://astral.sh/uv/install.sh | sh`
    quoted

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: scripts/flights-search

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: scripts/flights-search
  • 0Tools and files. 1 referenced file(s) missing: scripts/flights-search
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (flights) differs from the folder (flights-search)
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 11 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 890 tokens
  • 100Running it twice. No mutating operations

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 217: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 11 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.