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BD yotta-logs

元史 —— 跨智能体的历史会话 / 记忆日志检索技能：零依赖检索 / 分析 JSONL、JSON、SQLite、Markdown 多格式会话与记忆文件，回溯旧对话与父会话上下文，为跨会话追溯提供原始日志依据。触发：用户问起先前聊过的内容 / 父会话 / 历史上下文、要查以前说过的结论、跨会话回溯某次讨论、需要从会话日志或记忆文件定位某段决策时。边界：仅读取本机自己的会话日志 / 记忆文件；不修改、不删除；只查本地不联网上传。

ClawHub Agent Skills author: YottaMeta v0.3.1 MIT-0 17 files · 1 script body ≈ 686 tokens Open the sourceclawhub.ai↗ analyzed 29 h ago

元史 —— 跨智能体的历史会话 / 记忆日志检索技能：零依赖检索 / 分析 JSONL、JSON、SQLite、Markdown 多格式会话与记忆文件，回溯旧对话与父会话上下文，为跨会话追溯提供原始日志依据。触发：用户问起先前聊过的内容 / 父会话 /…

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentstype 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%
93
Quality 40%
74
Run on models
none yet
Process rating
D
48/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Secrets in code medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Secrets in code secret-private-key scripts/test_yotta_logs.py:185
    Private key material (key header without key body; test fixture / example file; quoted — discussed, not commanded)
    "-----BEGIN PRIVATE KEY----- …"))
    header onlyfixturequoted
  • low Secrets in code secret-aws-key scripts/test_yotta_logs.py:167
    AWS access key ID (placeholder value)
    check("redact AKIA", "AKIA" not in YL.redact("AKIA…DEF"))
    placeholder
  • low Secrets in code secret-high-entropy-token scripts/test_yotta_logs.py:178
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    "***" in YL.redact("abcd…FGH"))
    placeholder

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")

Process rating: all ten parameters 48/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 686 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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 2 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 214: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

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

External checks

ClawHub: suspicious
The skill appears purpose-built for local log retrieval, but it needs Review because it searches sensitive cross-agent history and its default redaction can miss secrets embedded in URLs.
LLM: suspicious (high) · 13 Sept 2026