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BF kaogong-study-tracker

朱批录 · 国考备考追踪 Skill。当用户发来套题成绩、错题截图、备考打卡或复习进度时触发。 核心功能：识别错题截图 → 分类错题原因 → 更新本地记录 → 生成每日总结 → 导出 Excel / 同步飞书。 触发关键词：做了一套题、今天做了、错了几道、帮我分析、备考打卡、行测、申论、 判断推理、资料分析、言语理解、数量关系、错题、复习进度、导出错题本、同步飞书。 只要用户提到做题、错题、备考就触发。图片消息也触发，自动调用多模态模型识别。

ClawHub Agent Skills author: KaguraNanaga v1.0.3 MIT-0 17 files body ≈ 1 267 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 42/100 · Will not run — References files that are not bundled: assets/config.example.json

ProcedureData and analyticsInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: assets/config.example.json
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: 16. 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: assets/config.example.json

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: assets/config.example.json
  • 0Tools and files. 1 referenced file(s) missing: assets/config.example.json
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1267 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
  • -32 of 8 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 223: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 19 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
This study-tracking skill is coherent, but it makes local-only privacy claims while screenshots and records can be sent to model providers, exported with images, or uploaded to Feishu.
LLM: suspicious (high) · VirusTotal: · 29 May 2026