TraceDecay Dev: Inspecting Automation Cycles

SkillDocs & knowledge

TraceDecay Dev: Use when auditing TraceDecay automation loops, skipped runs, memory-curator/session-reflector/skill-writer output, apply policy, or run artifacts.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the TraceDecay Dev: Inspecting Automation Cycles skill

What this skill tells your AI

The instructions your AI receives, as published by scriptedalchemy/tracedecay in .claude/skills/inspecting-automation-cycles/SKILL.md and read by ahel’s review.

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

  1. Start with tracedecay automation config get to identify enabled tasks, schedules, locks, profile paths, and apply policy.
  2. List recent runs with tracedecay automation runs list --limit 100; group by task and status before opening individual artifacts.
  3. For failures or suspicious skips, open the relevant artifact with tracedecay_automation_run_artifact_view or tracedecay tool automation_run_artifact_view --args ....
  4. Inspect model-managed memory outcomes plus configured managed-skill review queues: tracedecay automation facts list, dashboard telemetry, and tracedecay_skill_list --state pending.
  5. Check adoption evidence: tracedecay analytics diagnostics --all --no-sync, tracedecay sessions search "mcp__tracedecay" --provider all, and managed skill usage counts.

Reading Results

SignalMeaningNext step
scheduler_interval_not_elapsedHealthy throttlingCount only, do not fix.
scheduler_lock_activeAnother run owns the loopCheck age before calling stale.
no_new_session_activityNothing new to processVerify transcript ingest if surprising.
validation_gate artifactMutation passed validationInspect apply-policy state or dashboard artifact.
Many fact proposal recordsInspect validation/apply telemetryUse tracedecay:project-memory.
Active managed skills with zero useAdoption telemetry gapUse 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.

Signals

GitHub stars
73
Forks
5
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
inspecting-automation-cycles
Source
github.com/scriptedalchemy/tracedecay