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BD eric-compliance-suite

睿观(ERiC) 全功能合规检测套件。集成外观专利(D001)、发明专利(I001)、图形商标(L001)、文本商标+替换词(T001/T002)、版权(C001)、政策合规(P001-P007) 六大检测能力。当用户需要进行任何知识产权合规检测（专利、商标、版权）或电商平台政策合规审查时触发此 skill。

ClawHub Agent Skills author: wteng2286 v1.0.1 MIT-0 9 files body ≈ 2 093 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSecurityInfrastructuretype 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%
90
Quality 40%
80
Run on models
none yet
Process rating
D
43/100
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 · 10

✓ No critical or high findings

Medium and low: 10
  • low Secrets in code secret-high-entropy-token references/copyright-detection.md:151
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2025…kNm"
    quoted
  • low Secrets in code secret-high-entropy-token references/invention-patent.md:221
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2025…cDs"
    quoted
  • low Secrets in code secret-high-entropy-token references/logo-detection.md:197
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2025…tGE"
    quoted
  • low Secrets in code secret-high-entropy-token references/policy-detection.md:71
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2024…590"
    quoted
  • low Secrets in code secret-high-entropy-token references/policy-detection.md:181
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2024…ZHA"
    quoted
  • low Secrets in code secret-high-entropy-token references/policy-detection.md:234
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2024…R7n"
    quoted
  • low Secrets in code secret-high-entropy-token references/policy-detection.md:263
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2025…Y0b"
    quoted
  • low Secrets in code secret-high-entropy-token references/policy-detection.md:292
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2024…uvh"
    quoted
  • low Secrets in code secret-high-entropy-token references/trademark-detection.md:125
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2025…CS7"
    quoted
  • low Secrets in code secret-high-entropy-token references/trademark-detection.md:185
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "request_id": "2024…3wf"
    quoted

Files scanned: 9. 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")

Process rating: all ten parameters 43/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 54 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2093 tokens
  • low 13 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
  • +2Single-language instructions
  • +3Description length 155: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 54 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: suspicious
This appears to be a legitimate ERiC compliance API client, but it needs review because it uploads potentially sensitive product data, can change remote feature-word settings, and auto-installs a Python dependency at runtime.
LLM: suspicious (high) · VirusTotal: · 29 May 2026