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BF tech-insight

选型结论出来后，对最终选定的方案做深度技术拆解——内部架构分析、核心机制、竞争壁垒、风险点。不是介绍文章那种表面描述，是真的去拆它怎么运作。工作流包含：架构拆解、机制分析、壁垒识别、风险评估、演进预测、深度报告。

ClawHub Agent Skills author: vincentlau2046-sudo v1.0.2 MIT-0 35 files · 2 scripts body ≈ 2 418 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 31/100 · Will not run — References files that are not bundled: scripts/drawio-generator.py

ProcedureInfrastructuretype 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
80/100
safety, quality, tests
Safety 60%
98
Quality 40%
54
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: scripts/drawio-generator.py
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token layered-architecture-generator-v2.py:11
    High-entropy token-like string (may be an id, hash or a credential)
    class Laye…V2:
  • low Secrets in code secret-high-entropy-token layered-architecture-generator-v2.py:294
    High-entropy token-like string (may be an id, hash or a credential)
    generator = Laye…rV2(output_dir)

Files scanned: 35. 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: scripts/drawio-generator.py
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: scripts/drawio-generator.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/drawio-generator.py
  • 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 (tech-insight) differs from the folder (technical-insight)
  • 100Steps. 210 steps
  • 100Execution cost. Instruction body is 2418 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)
  • +3Description length 106: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -42 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 210 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

External checks

ClawHub: suspicious
The skill is mostly aligned with technical analysis, but it asks for broad runtime authority and contains unsafe filesystem, credential, and subprocess behavior that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026