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BF multi-group-chat-manager

用户画像+好感度双系统 + 自研液态记忆引擎。零外部依赖（核心），仅 OneBot 采集器使用 requests。画像使用自研 FluidMemory 引擎追踪用户特征，支持艾宾浩斯遗忘曲线衰减+自动关键词匹配强化。好感度基于群规加减分系统，JSON文件+文件锁保护。全配置统一化：config.json 集中管理，热加载不重启。多群聊上下线管理：基于时间戳区间精准扫描。OneBot 采集器+好感度规则引擎，规则文件化管理，支持多群差异化规则，水位线去重，auto/ai 双模式。扫描流水线集成采集→好感度→画像强化三阶段。

ClawHub Agent Skills author: Pig_in_tomb v1.1.5 MIT-0 16 files body ≈ 3 330 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 37/100 · Will not run — References files that are not bundled: scripts/rules/rule_群号.json

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
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
64
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: scripts/rules/rule_群号.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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token README.md:3
    High-entropy token-like string (may be an id, hash or a credential)
    [![GitHub](https://img.shields.io/badge/GitH…357%2Fmu…lue?logo=…)](https://github.com/pppig1357/multi-group-chat-manager)

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: scripts/rules/rule_群号.json
  • note frontmatter-key unknown frontmatter key "repository"

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: scripts/rules/rule_群号.json
  • 0Tools and files. 1 referenced file(s) missing: scripts/rules/rule_群号.json
  • 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. 60 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3330 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • 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
  • -2localhost URLs: will not work for another user
  • -246 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 263: enough signal without eating the budget
  • +4Structure: 50 headings
  • +3Step-by-step instructions: 60 items
  • +4Has examples (25 code blocks)
  • +3All 7 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This skill is a coherent group-chat management tool, but it can collect chat history and build lasting user profiles without strong built-in privacy controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026