debug

odysseus0/symphony · updated Apr 8, 2026

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$npx skills add https://github.com/odysseus0/symphony --skill debug
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summary

elixir/docs/logging.md requires these fields for issue/session lifecycle logs. Use

  • them as your join keys during debugging.
skill.md

Debug

Goals

  • Find why a run is stuck, retrying, or failing.
  • Correlate Linear issue identity to a Codex session quickly.
  • Read the right logs in the right order to isolate root cause.

Log Sources

  • Primary runtime log: log/symphony.log
    • Default comes from SymphonyElixir.LogFile (log/symphony.log).
    • Includes orchestrator, agent runner, and Codex app-server lifecycle logs.
  • Rotated runtime logs: log/symphony.log*
    • Check these when the relevant run is older.

Correlation Keys

  • issue_identifier: human ticket key (example: MT-625)
  • issue_id: Linear UUID (stable internal ID)
  • session_id: Codex thread-turn pair (<thread_id>-<turn_id>)

elixir/docs/logging.md requires these fields for issue/session lifecycle logs. Use them as your join keys during debugging.

Quick Triage (Stuck Run)

  1. Confirm scheduler/worker symptoms for the ticket.
  2. Find recent lines for the ticket (issue_identifier first).
  3. Extract session_id from matching lines.
  4. Trace that session_id across start, stream, completion/failure, and stall handling logs.
  5. Decide class of failure: timeout/stall, app-server startup failure, turn failure, or orchestrator retry loop.

Commands

# 1) Narrow by ticket key (fastest entry point)
rg -n "issue_identifier=MT-625" log/symphony.log*

# 2) If needed, narrow by Linear UUID
rg -n "issue_id=<linear-uuid>" log/symphony.log*

# 3) Pull session IDs seen for that ticket
rg -o "session_id=[^ ;]+" log/symphony.log* | sort -u

# 4) Trace one session end-to-end
rg -n "session_id=<thread>-<turn>" log/symphony.log*

# 5) Focus on stuck/retry signals
rg -n "Issue stalled|scheduling retry|turn_timeout|turn_failed|Codex session failed|Codex session ended with error" log/symphony.log*

Investigation Flow

  1. Locate the ticket slice:
    • Search by issue_identifier=<KEY>.
    • If noise is high, add issue_id=<UUID>.
  2. Establish timeline:
    • Identify first Codex session started ... session_id=....
    • Follow with Codex session completed, ended with error, or worker exit lines.
  3. Classify the problem:
    • Stall loop: Issue stalled ... restarting with backoff.
    • App-server startup: Codex session failed ....
    • Turn execution failure: turn_failed, turn_cancelled, turn_timeout, or ended with error.
    • Worker crash: Agent task exited ... reason=....
  4. Validate scope:
    • Check whether failures are isolated to one issue/session or repeating across multiple tickets.
  5. Capture evidence:
    • Save key log lines with timestamps, issue_identifier, issue_id, and session_id.
    • Record probable root cause and the exact failing stage.

Reading Codex Session Logs

In Symphony, Codex session diagnostics are emitted into log/symphony.log and keyed by session_id. Read them as a lifecycle:

  1. Codex session started ... session_id=...
  2. Session stream/lifecycle events for the same session_id
  3. Terminal event:
    • Codex session completed ..., or
    • Codex session ended with error ..., or
    • Issue stalled ... restarting with backoff

For one specific session investigation, keep the trace narrow:

  1. Capture one session_id for the ticket.
  2. Build a timestamped slice for only that session:
    • rg -n "session_id=<thread>-<turn>" log/symphony.log*
  3. Mark the exact failing stage:
    • Startup failure before stream events (Codex session failed ...).
    • Turn/runtime failure after stream events (turn_* / ended with error).
    • Stall recovery (Issue stalled ... restarting with backoff).
  4. Pair findings with issue_identifier and issue_id from nearby lines to confirm you are not mixing concurrent retries.

Always pair session findings with issue_identifier/issue_id to avoid mixing concurrent runs.

Notes

  • Prefer rg over grep for speed on large logs.
  • Check rotated logs (log/symphony.log*) before concluding data is missing.
  • If required context fields are missing in new log statements, align with elixir/docs/logging.md conventions.
how to use debug

How to use debug on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add debug
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/odysseus0/symphony --skill debug

The skills CLI fetches debug from GitHub repository odysseus0/symphony and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/debug

Reload or restart Cursor to activate debug. Access the skill through slash commands (e.g., /debug) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.425 reviews
  • Ganesh Mohane· Dec 20, 2024

    debug is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sakshi Patil· Nov 11, 2024

    Keeps context tight: debug is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Oct 2, 2024

    debug has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • James Anderson· Sep 13, 2024

    debug reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Rahul Santra· Sep 9, 2024

    debug fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakura Lopez· Sep 1, 2024

    debug has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Pratham Ware· Aug 28, 2024

    Registry listing for debug matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ishan Diallo· Aug 20, 2024

    Keeps context tight: debug is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Fatima Kim· Aug 4, 2024

    I recommend debug for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kabir Martinez· Jul 23, 2024

    debug fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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