| name | inspecting-automation-cycles |
| description | TraceDecay Dev: Use when auditing TraceDecay automation loops, skipped runs, memory-curator/session-reflector/skill-writer output, apply policy, or run artifacts. |
TraceDecay Dev: Inspecting Automation Cycles
TraceDecay automation is a loop, not a single artifact: config schedules jobs,
runs produce artifacts, dashboards expose outcomes/telemetry, and usage
analytics prove whether generated output was adopted.
Workflow
- Start with
tracedecay automation config get to identify enabled tasks,
schedules, locks, profile paths, and apply policy.
- List recent runs with
tracedecay automation runs list --limit 100; group
by task and status before opening individual artifacts.
- For failures or suspicious skips, open the relevant artifact with
tracedecay_automation_run_artifact_view or
tracedecay tool automation_run_artifact_view --args ....
- Inspect model-managed memory outcomes plus configured managed-skill review
queues:
tracedecay automation facts list, dashboard telemetry, and
tracedecay_skill_list --state pending.
- Check adoption evidence:
tracedecay analytics diagnostics --all --no-sync,
tracedecay sessions search "mcp__tracedecay" --provider all, and managed
skill usage counts.
Reading Results
| Signal | Meaning | Next step |
|---|
scheduler_interval_not_elapsed | Healthy throttling | Count only, do not fix. |
scheduler_lock_active | Another run owns the loop | Check age before calling stale. |
no_new_session_activity | Nothing new to process | Verify transcript ingest if surprising. |
validation_gate artifact | Mutation passed validation | Inspect apply-policy state or dashboard artifact. |
| Many fact proposal records | Inspect validation/apply telemetry | Use tracedecay:project-memory. |
| Active managed skills with zero use | Adoption telemetry gap | Use tracedecay:diagnosing-analytics. |
Guardrails
- Prefer read-only inspection. Do not mutate fact records.
- Do not approve, reject, delete, or apply managed-skill drafts unless the user
explicitly asked for mutation.
- Do not treat skipped runs as failures until grouped by skip reason and age.
- Avoid parallel
tracedecay_skill_view calls against one profile while
automation may write usage ledgers. If a usage read reports a truncated JSON
or EOF parse error, retry once after tracedecay_skill_list succeeds.
- Do not read
.tracedecay databases directly; use CLI, dashboard APIs, or
MCP tools.
Deliverable
Report task/status counts, the exact run or artifact ids inspected, apply-policy
state, adoption gaps, and the next concrete command for any mutation the user
should choose.
