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BD douyin-chat-insight

分析用户自备的群聊/私聊导出（含抖音群），生成单页会话价值报告（硬事实、矛盾、需求原话、动作）。零 IM 登录、不强制云 Key。触发：douyin-chat-insight、抖音聊天转知识库、群聊洞察、chat export insight。

ClawHub Agent Skills author: tars1230 v0.2.1 MIT-0 50 files body ≈ 491 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

分析用户自备的群聊/私聊导出（含抖音群），生成单页会话价值报告（硬事实、矛盾、需求原话、动作）。零 IM 登录、不强制云 Key。触发：douyin-chat-insight、抖音聊天转知识库、群聊洞察、chat export insight。

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsSoftware developmenttype 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
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
74
Run on models
none yet
Process rating
D
46/100
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token README.md:5
    High-entropy token-like string (may be an id, hash or a credential)
    [![GitHub](https://img.shields.io/badge/GitH…230%2Fdo…ack)](https://github.com/tars1230/douyin-chat-insight)

Files scanned: 43. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 491 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)
  • +3Output format is not stated: the model decides each time
  • -39 of 12 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 122: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (2 of 13)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill is a local chat-export analysis tool with disclosed file access and report output, with limited optional environment checks but no evidence of exfiltration or hidden automation.
LLM: benign (high) · VirusTotal: · 5 Aug 2026