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腾讯 IMA Wiki 编译——将原始资料系统化组织为结构清晰的Wiki知识体系，并支持标签体系管理与按文件夹层级结构归类。当用户说"建知识库""整理资料库""编译知识库""搭建wiki""知识体系化""把资料整理成wiki""给知识库打标签""按标签分类""标签整理""按文件夹归类""整理散落文件"时触发。不适用于单篇摘要、简单问答、或仅搜索已有知识库内容的场景。

ClawHub Agent Skills author: Victor Shen v1.2.0 MIT-0 18 files body ≈ 2 974 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

腾讯 IMA Wiki…

As a process D 35/100 · Unfinished process — References files that are not bundled: URL

ProcedureSoftware developmentAI and agentsWriting 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
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
35/100
Unfinished process
References files that are not bundled: URL
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: 18. 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: URL
  • note frontmatter-key unknown frontmatter key "last_updated"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: URL
  • 0Tools and files. 1 referenced file(s) missing: URL
  • 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
  • 30Running it twice. 16 mutating operations with no state check
  • 100Steps. 113 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2974 tokens
  • 100Progress reporting. Reports progress
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -219 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +5Description quotes 5 example trigger phrases
  • +3Description length 184: enough signal without eating the budget
  • +4Structure: 50 headings
  • +3Step-by-step instructions: 113 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (13 of 15)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This skill is a disclosed Tencent IMA knowledge-base organizer that can read and edit a user's IMA content, with no artifact evidence of hidden code execution or persistence.
LLM: benign (high) · VirusTotal: · 29 Sept 2026