debug-code-task — for Claude Code debug-code-task, intexuraos, community, for Claude Code, ide skills, Extract task ID, env=dev, task_<uuid>, dev.intexuraos.cloud, intexuraos.cloud, uname -n

v1.0.0

このスキルについて

適した場面: Ideal for AI agents that need investigate code-agent task execution by fetching task metadata and logs from firestore. ローカライズされた概要: AI-Native Platform Where Agents Build the Software # Debug Code Task Investigate code-agent task execution by fetching task metadata and logs from Firestore. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

機能

Investigate code-agent task execution by fetching task metadata and logs from Firestore.
Invocation Detection
Input Pattern Action
------------------------------------------------------- -------------------------
https://dev.intexuraos.cloud/#/code-tasks/task Extract task ID, env=dev

# Core Topics

pbuchman pbuchman
[8]
[1]
Updated: 3/8/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
52
Canonical Locale
en
Detected Body Locale
en

適した場面: Ideal for AI agents that need investigate code-agent task execution by fetching task metadata and logs from firestore. ローカライズされた概要: AI-Native Platform Where Agents Build the Software # Debug Code Task Investigate code-agent task execution by fetching task metadata and logs from Firestore. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

このスキルを使用する理由

推奨ポイント: debug-code-task helps agents investigate code-agent task execution by fetching task metadata and logs from firestore. AI-Native Platform Where Agents Build the Software # Debug Code Task Investigate code-agent

おすすめ

適した場面: Ideal for AI agents that need investigate code-agent task execution by fetching task metadata and logs from firestore.

実現可能なユースケース for debug-code-task

ユースケース: Applying Investigate code-agent task execution by fetching task metadata and logs from Firestore
ユースケース: Applying Invocation Detection
ユースケース: Applying Input Pattern Action

! セキュリティと制限

  • 制約事項: Parse the URL. Do NOT fetch it — hash-routed SPA returns only shell HTML.
  • 制約事項: node .claude/skills/debug-code-task/scripts/fetch-task.cjs <taskId --logs-only
  • 制約事項: Present log lines to user. Do NOT analyze or speculate about root cause without evidence from the logs.

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is debug-code-task?

適した場面: Ideal for AI agents that need investigate code-agent task execution by fetching task metadata and logs from firestore. ローカライズされた概要: AI-Native Platform Where Agents Build the Software # Debug Code Task Investigate code-agent task execution by fetching task metadata and logs from Firestore. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install debug-code-task?

Run the command: npx killer-skills add pbuchman/intexuraos/debug-code-task. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for debug-code-task?

Key use cases include: ユースケース: Applying Investigate code-agent task execution by fetching task metadata and logs from Firestore, ユースケース: Applying Invocation Detection, ユースケース: Applying Input Pattern Action.

Which IDEs are compatible with debug-code-task?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for debug-code-task?

制約事項: Parse the URL. Do NOT fetch it — hash-routed SPA returns only shell HTML.. 制約事項: node .claude/skills/debug-code-task/scripts/fetch-task.cjs <taskId --logs-only. 制約事項: Present log lines to user. Do NOT analyze or speculate about root cause without evidence from the logs..

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add pbuchman/intexuraos/debug-code-task. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use debug-code-task immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

debug-code-task

Install debug-code-task, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Debug Code Task

Investigate code-agent task execution by fetching task metadata and logs from Firestore.

Invocation Detection

Input PatternAction
https://dev.intexuraos.cloud/#/code-tasks/task_*Extract task ID, env=dev
https://intexuraos.cloud/#/code-tasks/task_*Extract task ID, env=prod
task_<uuid> + "debug"/"investigate"/"what went wrong"Use task ID directly

Phase 1: Environment Detection

Parse the URL. Do NOT fetch it — hash-routed SPA returns only shell HTML.

Signaldevprod
URLdev.intexuraos.cloudintexuraos.cloud (no dev.)

Run uname -n to confirm current machine.

Phase 2: Fetch Task Document

Extract task ID from URL hash: /#/code-tasks/{taskId} — everything after the last /.

Run from monorepo root (required for firebase-admin module resolution):

bash
1node .claude/skills/debug-code-task/scripts/fetch-task.cjs <taskId>

Print key fields as a summary table: id, status, linearIssueId, workerLocation, agentType, result.summary, error.

Phase 3: Fetch Log Lines

bash
1node .claude/skills/debug-code-task/scripts/fetch-task.cjs <taskId> --logs-only

Use --logs instead to fetch both task document and logs in one call. Pipe through head -N if user wants a subset. Logs are ordered by sequence number. Each line has format: [sequence] HH:MM:SS.mmm [source] message.

Present log lines to user. Do NOT analyze or speculate about root cause without evidence from the logs.

Phase 4: Orchestrator & Container Logs (optional, on request)

Only needed when Firestore logs are insufficient.

The orchestrator runs on the same machine as the worker. Read workerLocation from the task document (Phase 2) to determine which machine.

Orchestrator Logs

Check uname -n vs task's workerLocation. If on a different machine:

  • From mac-dev → SSH to home-dev: ssh home-dev journalctl -u intexuraos-orchestrator@pbuchman --since ... --until ...
  • From home-dev → cannot SSH to mac-dev. Tell the user.
MachineHow orchestrator runsLog command
home-devsystemd (intexuraos-orchestrator@pbuchman)journalctl -u intexuraos-orchestrator@pbuchman --since "<time>" --until "<time>"
mac-devpnpm --filter orchestrator dev in ~/deploy/intexuraos/Terminal output where the dev process is running. Code not auto-deployed on push.

Derive time window from task document createdAt._seconds and completedAt._seconds:

bash
1date -d @<createdAt._seconds> '+%Y-%m-%d %H:%M:%S' # --since (subtract 1 min) 2date -d @<completedAt._seconds> '+%Y-%m-%d %H:%M:%S' # --until (add 1 min)

Docker Container Logs

Containers are named claude-worker-{taskId}:

bash
1docker logs claude-worker-{taskId}

Only available while the container exists (running or exited but not yet removed). If the container is gone, Firestore log lines (Phase 3) are the only source.

Critical Rules

  1. NEVER WebFetch/curl the SPA URL. Data is in Firestore, not the HTML page.
  2. NEVER run node scripts from /tmp. firebase-admin resolves from monorepo node_modules.
  3. NEVER use node -e for scripts with !. Shell escapes ! — use the script file.
  4. NEVER speculate about what went wrong. Present facts from the task document and logs. Let the user drive analysis.
  5. NEVER present partial investigation results. No hedging ("maybe", "possibly", "there are multiple possible causes", "could be"). Fetch ALL evidence (task document, logs, orchestrator logs if needed) before presenting findings. Present a definitive root cause backed by concrete evidence. If evidence is genuinely insufficient, state exactly what is missing and go fetch it — do not guess. Non-negotiable.

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