har-debugger

Analyze HAR (.har) files alongside a bug description to identify slow, failed, or abnormal requests, correlate them to symptoms, and produce a concise root-cause report with evidence and next steps.

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Install skill "har-debugger" with this command: npx skills add hynguyenvk-itr/har-debugger-skill/hynguyenvk-itr-har-debugger-skill-har-debugger

HAR Debugger

Overview

Analyze a HAR file plus a bug description to isolate problematic network requests and explain likely causes using only HAR evidence.

Inputs

  • har_file: Path to a .har file on disk.
  • bug_description: Concise description of the bug symptoms.
  • start_time: (optional) ISO timestamp or epoch ms for when the bug started.
  • end_time: (optional) ISO timestamp or epoch ms for when the bug ended.
  • socket_map: (optional) Inline list of socket-to-API mappings in the form <socket-name>: <api-name> to override defaults.

If the user provides raw HAR JSON instead of a file, accept it, but prefer a file path when possible. Use start_time/end_time to limit analysis to the incident window to save tokens.

Workflow

  1. Validate that har_file exists and ends with .har; if missing, ask for the file path.
  2. If start_time/end_time provided, preprocess the HAR using the bundled parser at ./bin/har-parser. Always run the command from the skill directory so the relative path works. If the working directory is different, use the absolute skill path (e.g., /Users/<user-name>/.codex/skills/har-debugger/bin/har-parser).
./bin/har-parser -- --file <har_file> --start "<start_time>" --end "<end_time>" --format har --out output.har

Use output.har for all remaining analysis. Time format must match the parser input, for example 10/02/2026 03:02:00. 3. Parse the HAR JSON and confirm log.entries exists; if missing, ask for a complete HAR. 4. Flatten log.entries into a list of requests. 5. Extract for each entry: request.method, request.url, response.status, response.statusText, time, timings, startedDateTime, response headers (response.headers), and response body when available (response.content.text). 6. If present, capture response header time (e.g., Date header) as the server-reported response time. 7. Compute response received time as startedDateTime + time (milliseconds) to compare client vs server timestamps. 8. Load default socket map from references/socket_map.md and parse each line as <socket-name>: <api-name>. If socket_map input is provided, merge/override defaults with it. 9. If socket mappings exist, prioritize requests whose URL/path matches mapped API names related to the socket events in bug_description. 10. Flag suspicious entries:

  • HTTP status >= 400
  • Timeouts or errors indicated by timings or missing response
  • Long time values (default threshold 3000 ms; adjust if the bug suggests a different baseline)
  1. Match keywords from bug_description to URLs, methods, response content, and status text.
  2. Correlate the most relevant entries to the symptom and infer likely root causes only from HAR evidence plus the bug description.

Output

Provide a concise report that includes:

  • A brief root-cause summary with confidence/uncertainty notes.
  • A list of relevant requests (method, URL, status, time, response received time, response header time, key evidence).
  • Evidence bullets explicitly tied to the bug description.
  • Recommendations for next debugging steps (logs, backend metrics, repro checks).

Constraints

  • Do not fabricate or assume data not present in the HAR.
  • Keep hypotheses grounded in the observed requests and timings.

Source Transparency

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