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AB cuecue-deep-research

Professional AI-powered financial research and analysis tool for market intelligence, industry reports, company analysis, policy impact assessment, competitive analysis, and geopolitical risk evaluation. Delivers comprehensive, data-driven research reports for financial professionals and AI agents. | 专业的 AI 驱动金融研究分析工具,用于市场情报、行业报告、公司分析、政策影响评估、竞品调查和地缘政治风险评估。为金融专业人士和智能体提供全面、数据驱动的研究报告。

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 1 967 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Professional AI-powered financial research and analysis tool for market intelligence, industry reports, company analysis, policy impact assessment…

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

AnalyzerData and analyticstype 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
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "keywords"

    Process rating: all ten parameters 68/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 54 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1967 tokens
    • 100Running it twice. Mutating operations check current state
    • high The skill tells the model to perform an irreversible action with no human approval

    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)
    • -220 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 384: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 54 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.