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BF financial-audit-domain

财报排雷审计分析知识参考库（领域负载物）。覆盖偿债能力、经营资产质量、长期资产质量、负债权益结构、收入盈利质量、现金流质量六大排雷域，含50项核心指标与5条舞弊红线。仅适用于A股非金融类上市公司。触发词：财报排雷、财务排雷、财务报表分析、财务造假识别、A股排雷。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 11 files body ≈ 2 402 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

财报排雷审计分析知识参考库（领域负载物）。覆盖偿债能力、经营资产质量、长期资产质量、负债权益结构、收入盈利质量、现金流质量六大排雷域，含50项核心指标与5条舞弊红线。仅适用于A股非金融类上市公司。触发词：财报排雷、财务排雷、财务报表分析、财务造假识别、A股排雷。

As a process F 35/100 · Will not run — References files that are not bundled: references/exemplars/

AnalyzerAI and agentstype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/exemplars/
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: 11. 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: references/exemplars/

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/exemplars/
  • 0Tools and files. 1 referenced file(s) missing: references/exemplars/
  • 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
  • 100Steps. 87 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2402 tokens
  • 100Running it twice. No mutating operations
  • low 10 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)
  • +3Output format is not stated: the model decides each time
  • -214 emoji in the instructions: noise for the model
  • -36 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 131: enough signal without eating the budget
  • +4Structure: 41 headings
  • +3Step-by-step instructions: 87 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

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

External checks

ClawHub: suspicious
This skill is mostly aligned with financial report analysis, but it expands into automatic dependency installation and execution behavior without a clear approval step.
LLM: suspicious (medium) · VirusTotal: · 6 Jun 2026