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BF 资产底牌｜护城河解剖

上市公司护城河深度解剖。对任意上市公司/股票代码/上传资料进行六维竞争壁垒分析（资源、技术、客户认证、规模、产业链卡口、成长空间），输出结构化的资产底牌研究报告。适用于个股研究、财报分析、研报解读、调研纪要分析等场景。

ClawHub Agent Skills author: ambrose2324 v1.0.1 MIT-0 5 files body ≈ 331 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

上市公司护城河深度解剖。对任意上市公司/股票代码/上传资料进行六维竞争壁垒分析（资源、技术、客户认证、规模、产业链卡口、成长空间），输出结构化的资产底牌研究报告。适用于个股研究、财报分析、研报解读、调研纪要分析等场景。

As a process F 31/100 · Will not run — References files that are not bundled: references/analysis-framework.md, references/output-template.md

ProcedureResearchtype 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
79/100
safety, quality, tests
Safety 60%
100
Quality 40%
48
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: references/analysis-framework.md, references/output-template.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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 · 0

✓ No critical or high findings

Files scanned: 0. 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")
  • warning missing-ref reference to a missing file: references/analysis-framework.md
  • warning missing-ref reference to a missing file: references/output-template.md
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "emoji"
  • note frontmatter-key unknown frontmatter key "categories"
  • note frontmatter-key unknown frontmatter key "search_keywords"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: references/analysis-framework.md, references/output-template.md
  • 0Tools and files. 2 referenced file(s) missing: references/analysis-framework.md, references/output-template.md
  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (资产底牌｜护城河解剖) differs from the folder (moat-anatomy)
  • 100Steps. 15 steps
  • 100Execution cost. Instruction body is 331 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 109: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 15 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.

External checks

ClawHub: clean
This is a coherent stock-analysis skill made of markdown instructions and templates, with no code execution or hidden access, though users should avoid uploading sensitive financial documents unless needed.
LLM: benign (high) · VirusTotal: · 5 Jul 2026