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Trace Debuger
by
gakkiismywife
· GitHub ↗
· v0.2.1
461
Downloads
1
Stars
0
Active Installs
3
Versions
Install in OpenClaw
/install trace-debuger
Description
End-to-end trace debugging from trace_id. Fetch Jaeger trace and Elasticsearch logs, analyze possible bugs (optionally with local repository context), and ge...
Usage Guidance
Before installing or running this skill: (1) Understand it will read any files under the provided repo_path and send logs+code to an external 'codex' tool invoked by subprocess — confirm what 'codex' does and where it sends data. (2) The skill metadata does not declare the 'codex' CLI as a required binary or any auth variables for ES/Jaeger — expect manual setup or failures. (3) Avoid providing paths to sensitive repositories; run first in a sandbox or VM with limited network access. (4) If you need to use it with private Jaeger/ES, verify how credentials are supplied and that you trust the external analysis service. (5) Consider inspecting or running the included script locally to confirm behavior (and remove or change the hard-coded example repo_path) before granting it access to real data.
Capability Analysis
Type: OpenClaw Skill
Name: trace-debuger
Version: 0.2.1
The skill performs trace debugging by fetching data from Jaeger and Elasticsearch and analyzing local source code. It exhibits high-risk behaviors including recursive file system traversal and reading of local files within a user-defined 'repo_path' (scripts/trace_debuger.py), and it executes an external binary 'codex' via subprocess.run to perform analysis. While these actions align with the stated purpose of debugging code, the broad file access and execution of external commands represent a significant attack surface, especially given the hardcoded default path '/Users/noodles/...' which suggests unvetted development code.
Capability Assessment
Purpose & Capability
The name/description (trace debugging via Jaeger + Elasticsearch + optional repository context) matches the script's behavior. However, the SKILL.md and script expect an external 'codex' analysis step (runs a codex CLI/subprocess) and access to local repository files, yet the registry metadata declares no required binaries or environment variables. The default repo_path in SKILL.md points to a specific absolute user path (/Users/noodles/...) which is unusual for a generic skill and may be a leftover from development.
Instruction Scope
SKILL.md instructs the agent to run the included Python script, fetch traces from jaeger_url and logs from es_url, and optionally scan a local repo. It also mandates that the generated Markdown file be sent to the user as ONE chat message with a strict caption format and then deleted locally. That strict single-message upload + deletion step could be used to obfuscate data transfer and reduces auditability. The instructions instruct running 'codex exec' (or equivalent) against repository and logs, which will send code/log data to an external tool/service.
Install Mechanism
There is no install spec (instruction-only), which minimizes disk writes. However, the runtime flow relies on an external CLI ('codex') invoked via subprocess. The skill metadata does not declare this required binary—this mismatch is a practical omission (the skill will fail or behave differently if codex is not present).
Credentials
The skill declares no required environment variables, but it will access network endpoints (jaeger_url, es_url) and arbitrary local files under the provided repo_path. If the codex CLI sends data to an external service, analysis results and repository contents could leave the host. The default absolute repo_path is a red flag (points to a particular user's Desktop). No authentication handling for ES/Jaeger is declared (these services often require credentials), so users might supply credentials ad hoc or the script might be run against local, unauthenticated endpoints.
Persistence & Privilege
The skill does not request permanent presence (always:false) and does not modify other skill configs. It writes a local Markdown file and explicitly instructs deletion afterwards; the deletion behavior itself is not privileged but combined with the one-message upload requirement reduces leftover artifacts for inspection.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install trace-debuger - After installation, invoke the skill by name or use
/trace-debuger - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.2.1
Enforce single-message delivery: markdown report as file attachment + strict summary format with real filename.
v0.2.0
Integrate Codex log+code analysis, remove local rule-based bug analysis, keep fixed response format and chat file delivery workflow.
v0.1.0
Initial release: Jaeger+ES trace debugging with markdown report, fixed reply format, repo-path default, code-line evidence via caller mapping.
Metadata
Frequently Asked Questions
What is Trace Debuger?
End-to-end trace debugging from trace_id. Fetch Jaeger trace and Elasticsearch logs, analyze possible bugs (optionally with local repository context), and ge... It is an AI Agent Skill for Claude Code / OpenClaw, with 461 downloads so far.
How do I install Trace Debuger?
Run "/install trace-debuger" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Trace Debuger free?
Yes, Trace Debuger is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Trace Debuger support?
Trace Debuger is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Trace Debuger?
It is built and maintained by gakkiismywife (@gakkiismywife); the current version is v0.2.1.
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