SKILLEMALL.ai
GitHub ↗ RU Sign in

BD Market Data Skill

This skill provides access to financial market data.

modbender/skill-library-mcp Agent Skills author: modbender MIT 7 files body ≈ 636 tokens Open the sourcegithub.com↗ analyzed 2 d ago

This skill provides access to financial market data.

As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureSoftware developmentPersonal productivitytype 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
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
60
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token src/index.js:2
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const POLYGON_API_KEY = 'QR_W…JCS';
    quoted
  • low Exfiltration exfil-secret-in-url src/index.js:27
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
    const url = `https://api.polygon.io/v2/aggs/ticker/${ticker}/range/1/day/${from}/${to}?adjusted=true&sort=asc&limit=500&apiKey=…
    placeholder

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 47/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (Market Data Skill) differs from the folder (market-data)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 17 steps
  • 100Execution cost. Instruction body is 636 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)
  • +3Description length 52: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 17 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.