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AC clawtrace-runtime-observatory

AI Runtime Observatory（AI运行时观测系统）— 观察、重建、记录、解释 AI Workflow 在运行时真正做了什么。触发场景：(1) 用户输入 "debug"、"启动debug模式"、"进入debug"、"trace"、"查看workflow"、"查看运行过程"、"查看skill调用"、"runtime trace"；(2) meta.debug_mode = true；(3) 系统自动触发（retry_count 大于等于1、fallback被触发、Critic与Executor严重冲突、Context Integrity失败、data_envelope缺失、nested_skill_detected = true、workflow_integrity = degraded）。只观察、只记录、只解释。绝对禁止修改任何Workflow、data_envelope、previous_output、Skill输出。禁止自动修复、自动执行fallback、自动触发retry、替代Orchestrator决策、伪造日志、猜测不存在的Workflow。

ClawHub Agent Skills author: smallKeyboy v1.0.0 MIT-0 2 files body ≈ 1 148 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentInfrastructuretype 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
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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")

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (clawtrace-runtime-observatory) differs from the folder (smallkeyboy-clawtrace-runtime-observatory)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 96 steps
  • 100Execution cost. Instruction body is 1148 tokens
  • low 13 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 6 example trigger phrases
  • +3Description length 490: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 96 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
This non-executable debugging skill is not malware, but it asks to expose broad internal runtime context and reasoning without enough scoping or redaction.
LLM: suspicious (high) · VirusTotal: · 28 May 2026