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steel-session-debugging

Use this skill when the user provides a failed Steel session ID, failed automation run, timeout, browser error, blocked page, or unexpected result and wants evidence-backed diagnosis from session metadata, browser logs, raw agent logs, semantic traces, replay links, screenshots, network failures, or errors. Do not use for first-pass bot mitigation; collect evidence here, then hand off to steel-reliability for proxy, CAPTCHA, identity, or anti-bot fixes.

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steel-dev/skills
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2026년 6월 3일 11:18
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SKILL.md
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name
steel-session-debugging
description
Use this skill when the user provides a failed Steel session ID, failed automation run, timeout, browser error, blocked page, or unexpected result and wants evidence-backed diagnosis from session metadata, browser logs, raw agent logs, semantic traces, replay links, screenshots, network failures, or errors. Do not use for first-pass bot mitigation; collect evidence here, then hand off to steel-reliability for proxy, CAPTCHA, identity, or anti-bot fixes.
license
MIT
compatibility
claude-code,codex,cursor,opencode,pi
metadata
{"owner":"steel","category":"debug","stage":"beta"}
# Steel Session Debugging ## Skill Boundary Use this skill to explain what happened in a failed Steel session and what to change next. Start from evidence, not guesses. Do not use this skill as the primary place for bot-detection mitigation, proxy strategy, CAPTCHA strategy, login reputation, or retry policy. If the evidence points there, collect enough proof and hand off to `steel-reliability`. ## Setup Check 1. Confirm the user provided a Steel session ID or enough context to identify one. 2. Run `steel doctor --preflight` if CLI auth or API access is uncertain. 3. Prefer Steel CLI diagnostics before raw API calls. 4. Create local artifacts under `.steel-debug/`; do not paste raw logs into chat unless the user asks. ## Investigation Workflow 1. Collect session metadata, browser logs, raw agent logs, semantic agent traces, and viewer/replay links. 2. Redact cookies, bearer tokens, API keys, passwords, form values, and obvious PII before summarizing. 3. Build a timeline: session creation, navigations, actions, waits, console errors, failed requests, CAPTCHA/proxy signals, and final state. 4. Classify the failure using the taxonomy in `references/failure-taxonomy.md`. 5. Produce an evidence-backed diagnosis with a smallest useful verification step. 6. If the fix involves bot detection, proxy, CAPTCHA, identity, pacing, or login persistence, route to `steel-reliability`. ## Output Format ```text Diagnosis: - What happened: - Most likely cause: - Evidence: - What to change: - Verification step: - Confidence: ``` ## Useful Commands ```bash steel --json sessions get <session-id> steel --json sessions logs <session-id> steel --json sessions agent-logs <session-id> steel --json sessions traces <session-id> node scripts/collect-session-debug.mjs <session-id> node scripts/redact-session-debug.mjs .steel-debug/<session-id>/bundle.json node scripts/summarize-session-debug.mjs .steel-debug/<session-id>/redacted-bundle.json ``` ## References - `references/investigation-workflow.md`: detailed collection and timeline process. - `references/log-event-types.md`: how to separate metadata, browser logs, raw agent logs, and traces. - `references/agent-traces.md`: how to read semantic agent trace events. - `references/network-forensics.md`: request failures, redirects, and blocked-page evidence. - `references/replay-and-screenshots.md`: viewer, player, HLS, and screenshot usage. - `references/failure-taxonomy.md`: standard failure classes. - `references/reliability-handoff.md`: when to load `steel-reliability`.
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