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BF optical-comm-investing

AI光通信产业链投资分析框架（自迭代）。基于闷得而蜜160篇专栏+查尔斯大风车15篇长文的系统性整理，支持持续学习新帖自动追加。用于：(1)分析光通信相关股票（光模块/光芯片/PCB/CPO/NPO/OCS概念股），(2)判断技术路线（InP/硅光/TFLN/CPO/NPO/XPO），(3)评估标的质量（九字诀/大西瓜vs小土豆），(4)产业链映射和供应链分析，(5)更新光通信知识/学习闷蜜新帖/查尔斯新文章。触发词：光通信、光模块、CPO、NPO、InP、EML、硅光、TFLN、OCS、光芯片、光互联、闷蜜框架、更新光通信知识、学习闷蜜新帖、查尔斯新文章。

ClawHub Agent Skills author: SeanWeiSean v2.0.0 MIT-0 28 files body ≈ 1 301 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 37/100 · Will not run — References files that are not bundled: references/archive/

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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: references/archive/
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

The same skill appears in 1 more place: ClawHub

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: 28. 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/archive/

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: references/archive/
  • 0Tools and files. 1 referenced file(s) missing: references/archive/
  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Steps. 70 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1301 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 282: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 70 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (4 of 5)

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

External checks

ClawHub: clean
This skill is a disclosed investment-analysis knowledge pack with an optional update workflow, but users should run updates deliberately because they can use a logged-in browser and edit local reference notes.
LLM: benign (high) · VirusTotal: · 29 May 2026