Debugger for stalled or failing processes that correlates log data to specific tickets and sessions.
Install
mkdir -p .claude/skills/debug-joosure && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/18257" && unzip -o skill.zip -d .claude/skills/debug-joosure && rm skill.zipInstalls to .claude/skills/debug-joosure
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Investigate stuck runs and execution failures by tracing Symphony and CodexKey capabilities
- →Find reasons for stuck runs
- →Correlate Linear issue identity to Codex session
- →Trace `session_id` across logs
- →Identify timeout/stall failures
- →Classify app-server startup failures
- →Capture evidence with log lines
How it works
This skill investigates execution failures by searching primary and rotated Symphony and Codex logs. It uses `issue_identifier`, `issue_id`, and `session_id` to trace the lifecycle of a run and classify the failure.
Inputs & outputs
When to use debug
- →Debug stuck runs
- →Investigate process failure
- →Trace execution logs
About this skill
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.Observability.LogFile(log/symphony.log). - Includes orchestrator, agent runner, and Codex app-server lifecycle logs.
- Default comes from
- 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)
- Confirm scheduler/worker symptoms for the ticket.
- Find recent lines for the ticket (
issue_identifierfirst). - Extract
session_idfrom matching lines. - Trace that
session_idacross start, stream, completion/failure, and stall handling logs. - Decide class of failure: timeout/stall, app-server startup failure, turn failure, or orchestrator retry loop.
Long-Running Service Checks
When verifying that the main Symphony service stays resident, do not treat a
background process launched from a transient tool shell as authoritative. For
example, nohup ./bin/symphony ... & inside exec_command may disappear when
that tool shell returns because the execution environment cleans up child
processes. That is not evidence that Symphony exited because the queue was
empty.
Use one of these verification modes instead:
- Run
./bin/symphony ...in a foreground long-running tool session and observe at least two or three poll cycles before stopping it explicitly. - For real daemon behavior, use a real process supervisor such as launchd, systemd, Docker/release runner, tmux, or screen.
Acceptable evidence for a healthy empty-queue resident service:
- the dashboard/API port remains listening when configured
log/symphony.log*continues to recordpoll_cycle_completed status=okcandidate_count=0still leads to laterpoll_cycle_startedevents
If a background process vanishes after the parent tool shell exits, first
classify it as a launch-method artifact. Only investigate supervisor or child
lifecycle failure after finding service-level evidence such as
service_stopped, child crash logs, a nonzero foreground exit, or missing
follow-up poll cycles while the parent shell is still alive.
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
- Locate the ticket slice:
- Search by
issue_identifier=<KEY>. - If noise is high, add
issue_id=<UUID>.
- Search by
- Establish timeline:
- Identify first
Codex session started ... session_id=.... - Follow with
Codex session completed,ended with error, or worker exit lines.
- Identify first
- 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, orended with error. - Worker crash:
Agent task exited ... reason=....
- Stall loop:
- Validate scope:
- Check whether failures are isolated to one issue/session or repeating across multiple tickets.
- Capture evidence:
- Save key log lines with timestamps,
issue_identifier,issue_id, andsession_id. - Record probable root cause and the exact failing stage.
- Save key log lines with timestamps,
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:
Codex session started ... session_id=...- Session stream/lifecycle events for the same
session_id - Terminal event:
Codex session completed ..., orCodex session ended with error ..., orIssue stalled ... restarting with backoff
For one specific session investigation, keep the trace narrow:
- Capture one
session_idfor the ticket. - Build a timestamped slice for only that session:
rg -n "session_id=<thread>-<turn>" log/symphony.log*
- 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).
- Startup failure before stream events (
- Pair findings with
issue_identifierandissue_idfrom 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
rgovergrepfor 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.mdconventions.
When not to use it
- →When the run is not stuck, retrying, or failing
- →When log sources like `log/symphony.log` are unavailable
- →When `issue_identifier`, `issue_id`, or `session_id` are not present in logs
Limitations
- →Requires specific log fields (`issue_identifier`, `issue_id`, `session_id`) to be present
- →Relies on `log/symphony.log` and its rotated versions
- →Does not provide solutions, only identifies the problem
How it compares
This skill provides a structured approach to debugging by correlating specific identifiers across different log sources to pinpoint the exact failure stage, unlike a general log review.
Compared to similar skills
debug side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| debug (this skill) | 0 | 1mo | Review | Intermediate |
| github-actions-lookup | 0 | 3mo | Review | Intermediate |
| service-mesh-observability | 5 | 2mo | No flags | Advanced |
| gh-fix-ci | 12 | 5mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
github-actions-lookup
matthieumarshall
Look up GitHub Actions run results for login-page CI/CD pipeline and collect failure details including logs, job outcomes, and diagnostics. Use when: investigating CI failures on main or add_security_standards branches, debugging workflow issues, checking latest PR build status, or collecting build
service-mesh-observability
wshobson
Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.
gh-fix-ci
openai
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
langsmith-observability
davila7
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.
error-diagnostics-smart-debug
sickn33
Use when working with error diagnostics smart debug
debugging-toolkit-smart-debug
sickn33
Use when working with debugging toolkit smart debug