SKILLEMALL.ai

BD agent-trace-audit

当用户说『AI刚才干了什么我要查』『agent操作有没有越界』『出事了能回溯吗』『给AI行为留个账本』,或要给 agent 的操作做可审计留痕时使用。把 agent 的动作日志(时间戳/执行者/动作/对象/是否过闸)建成可追溯账本,标出未过闸的越界操作(有籍),输出时间线+违规清单。可运行脚本(trace_audit 审计器)。理论根基:LGD 三律之有籍(全程可追溯)。与 agent-redteam-kit/有门禁互补。触发词:行为留痕、trace audit、操作审计、agent回溯、可追溯、行为账本、审计日志。

ClawHub Hermes author: zhaoxinghua09-cell v1.0.0 MIT-0 7 files body ≈ 468 tokens Open the sourceclawhub.ai analyzed 2 d ago

当用户说『AI刚才干了什么我要查』『agent操作有没有越界』『出事了能回溯吗』『给AI行为留个账本』,或要给 agent 的操作做可审计留痕时使用。把 agent 的动作日志(时间戳/执行者/动作/对象/是否过闸)建成可追溯账本,标出未过闸的越界操作(有籍),输出时间线+违规清单。可运行脚本(traceaudit…

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

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
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.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 261 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "title"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "agent_created"
  • note frontmatter-key unknown frontmatter key "copyright"
  • note frontmatter-key unknown frontmatter key "read_when"
  • note frontmatter-key unknown frontmatter key "homepage"

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 468 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
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 261: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
This is a local log-audit skill, but its mutable install instructions and weak audit handling could mislead users who rely on it for incident review.
LLM: suspicious (medium) · 11 Sept 2026