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BC memory-distiller

记忆蒸馏器是面向 AI Agent 日志的智能压缩系统，针对日志膨胀、关键信息丢失、压缩后难回溯、 不同内容需不同策略四大痛点而设计。核心能力包括：分类型差异化压缩策略（事件/教训/待办/成长四类不同粒度）、 压缩溯源链（每个摘要条目保留原始段落定位标记，可一键回溯）、混合提取引擎（关键词匹配+兜底提取+混合模式）、 压缩质量评估器（压缩比/信息保留率/可读性/溯源覆盖率四维指标）、古文压缩四原则、多语言混合处理. 借鉴古文压缩哲学，把冗长原始日志蒸馏为高密度结构化摘要，实现 4-8 倍压缩比且零关键事件损失. 适用于 Agent 每日日志归档、长会话上下文压缩、项目复盘提炼、决策推理蒸馏等场景.

ClawHub Agent Skills author: 天轰穿 v1.0.2 MIT-0 2 files body ≈ 2 123 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceAI and agentsInfrastructuretype 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%
100
Quality 40%
65
Run on models
none yet
Process rating
C
53/100
Has gaps
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 · 0

✓ No critical or high findings

Files scanned: 2. 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")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "suggested_price"
  • note frontmatter-key unknown frontmatter key "pricing_tier"
  • note frontmatter-key unknown frontmatter key "pricing_model"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 32 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2123 tokens
  • 100Running it twice. No mutating operations

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
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 302: enough signal without eating the budget
  • +4Structure: 36 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (8 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: clean
This skill is a memory-log compression guide that uses local file reads and simple file maintenance commands in ways that match its stated purpose.
LLM: benign (high) · VirusTotal: · 24 Jul 2026