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BC stock-copilot-pro

OpenClaw stock analysis skill for US/HK/CN markets. Combines QVeris data sources (THS, Caidazi, Alpha Vantage, Finnhub, X sentiment) for quote, fundamentals, technicals, news radar, morning/evening brief, and actionable investment insights.

modbender/skill-library-mcp Agent Skills author: modbender MIT 45 files body ≈ 3 381 tokens Open the sourcegithub.com↗ analyzed 3 d ago

OpenClaw stock analysis skill for US/HK/CN markets.

As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerMarketingtype 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
85/100
safety, quality, tests
Safety 60%
98
Quality 40%
65
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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 scripts/stock_copilot_pro.mjs:24
    High-entropy token-like string (may be an id, hash or a credential)
    resolveCompanyNameViaQveris as reso…sV2,
  • low Secrets in code secret-high-entropy-token scripts/stock_copilot_pro.mjs:529
    High-entropy token-like string (may be an id, hash or a credential)
    return reso…sV2(companyName, preferredMarket);

Files scanned: 37. 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")
  • note frontmatter-key unknown frontmatter key "env"
  • note frontmatter-key unknown frontmatter key "requirements"
  • note frontmatter-key unknown frontmatter key "credentials"
  • note frontmatter-key unknown frontmatter key "runtime"
  • note frontmatter-key unknown frontmatter key "install"
  • note frontmatter-key unknown frontmatter key "persistence"
  • note frontmatter-key unknown frontmatter key "security"
  • note frontmatter-key unknown frontmatter key "network"
  • note frontmatter-key unknown frontmatter key "auto_invoke"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "examples"

Process rating: all ten parameters 55/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 176 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3381 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 top-level sections: this looks like several domains in one skill

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)
  • -43 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 240: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 176 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.