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BD fastfish-lite

fastfish 开源精简版。提供公众号格式整理、敏感词检测（本地）、每日热点、本地 HTML 预览。热点推送需至少配置一个渠道的 env。无微信发布/授权，需商业版。通过 system.run 调用 CLI。

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 317 tokens Open the sourcegithub.com↗ analyzed 3 d ago

fastfish 开源精简版。提供公众号格式整理、敏感词检测（本地）、每日热点、本地 HTML 预览。热点推送需至少配置一个渠道的 env。无微信发布/授权，需商业版。通过 system.run 调用 CLI。

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

IntegrationTelegramGitHubSlackDiscordSoftware developmentWriting and documentstype 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%
98
Quality 40%
67
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration read-dotenv SKILL.md:30
    Reads a .env file (quoted — discussed, not commanded)
    4. 配置：`copy .env.example .env`（可选；热点推送需配置 Webhook，见 metadata.credentials）
    quoted
  • low Exfiltration read-dotenv SKILL.md:52
    Reads a .env file (security demo / example; quoted — discussed, not commanded)
    - 禁止执行会输出 .env 内容的命令（如 `cat .env`、`type .env`、`Get-Content .env`）
    demoquoted

Files scanned: 1. 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. 6 mutating operations with no state check
  • 60Tools and files. Uses tools (git, python) that frontmatter does not declare
  • 100Steps. 35 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1317 tokens

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 105: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (4 code blocks)

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