agent-error-logger-new
v1.0.0Agent 错误日志工具。记录、检索和分析 Agent 犯过的错误，避免重复踩坑。 支持自动记录任务失败、手动查询错误模式、生成修正建议。
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the provided files and scripts: record_error.py and search_errors.py implement recording and searching error logs stored under workspace/memory. README, USAGE, and SKILL.md all describe the same logging/searching functionality — nothing requests unrelated services or capabilities.
Instruction Scope
SKILL.md instructs the agent to record, query, and proactively check local error logs in workspace/memory. The runtime instructions and example commands reference only local files and the included Python scripts; they do not command the agent to read unrelated system credentials, network endpoints, or external data beyond optional GitHub publishing guidance.
Install Mechanism
There is no install spec — this is instruction/code-only. No remote download or archive extraction occurs. The included create-repo.sh uses the GitHub CLI (gh) if run, which is normal for pushing a repo but is optional and not required for core logging functionality.
Credentials
The skill declares no required environment variables or credentials. Documentation shows optional GitHub push workflows (gh CLI or embedding a PAT in a push URL). That example (embedding a PAT in a git URL) is insecure practice — the scripts do not themselves exfiltrate secrets, but running the push instructions requires GitHub credentials and care.
Persistence & Privilege
always is false and the skill is user-invocable. The skill writes/reads files under workspace/memory (its own data area) which is expected for a logger; it does not request system-wide config changes or alter other skills.
Assessment
This skill appears to do what it claims: keep local markdown error logs and let you search them. Before enabling: (1) Verify the workspace/memory path used by the scripts is acceptable and does not contain sensitive data you wouldn't want aggregated into logs. (2) Do not paste GitHub Personal Access Tokens into command lines or URLs as shown in docs — prefer gh auth login or a credential helper. (3) If you plan to let the agent automatically consult logs before tasks, confirm you are comfortable with the agent reading the workspace/memory files. (4) Review the repository files locally (especially example logs) to ensure no real secrets are present in example content.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.