Install
openclaw skills install agent-routing-waste-auditPaste an agent job, cron, routing, or run summary and get an immediate read-only audit of possible routing, retry, fallback, or model-assignment waste. Progressive evidence handling — thin input produces a preliminary finding, richer input produces a stronger audit.
openclaw skills install agent-routing-waste-auditA cross-agent routing waste audit skill. It inspects pasted run summaries — from Hermes cron lists, OpenClaw job lists, LiteLLM/OpenRouter usage exports, PilotDeck routing sessions, or generic JSON/CSV/log snippets — and produces an immediate read-only audit of possible routing, retry, fallback, or model-assignment waste.
One principle: paste what you have, get a ranked audit immediately. Do not fill a template first.
This skill is a sibling to waste-audit. They are not interchangeable:
waste-audit → recurring OpenClaw job waste (schedule, delivery, token burn)agent-routing-waste-audit → routing decisions within runs (model tier, retry, fallback, sub-agent, local/cloud split)Use waste-audit for OpenClaw recurring job waste. Use this skill when the main question is routing, retry, fallback, sub-agent model choice, or local/cloud split.
This skill is read-only. It does not edit configs, switch providers, disable jobs, or auto-apply routing changes.
Activate when a user types:
audit agent routing waste
Also activate for questions about:
waste-audit insteadPaste any one of these:
hermes cron list
or
The skill will first produce a preliminary audit from whatever is available, then ask for only the next most useful evidence. Do not prepare a structured form before pasting.
The skill operates at three evidence levels. Each level adds weight to findings but none are required upfront.
| Level | What you have | What you get |
|---|---|---|
| Level 1 | Schedule / job list only | Preliminary ranking, highest-frequency candidates flagged |
| Level 2 | Job metadata + prompt summary | Stronger signal on whether the task needs an LLM every run |
| Level 3 | Token usage + retry + fallback + output usefulness | High-confidence audit with policy recommendation |
Do not block on Level 3. Paste what you have now.
When the input is raw hermes cron list output, the skill parses this block structure:
<job_id> [active|paused|completed]
Name: <name>
Schedule: <cron expression>
Repeat: <∞|number>
Next run: <ISO timestamp>
Deliver: <target>
Last run: <ISO timestamp> <ok|error|...>
Extract these fields:
job_idstate (active / paused / completed)nameschedule (cron expression)repeat (∞ or a number)next_run (ISO timestamp)delivery_targetlast_run_timelast_status (ok / error / other)Frequency mapping (approximate runs per day):
| Schedule | Runs/day | Priority |
|---|---|---|
*/5 * * * * | ~288 | High |
*/10 * * * * | ~144 | High |
*/15 * * * * | ~96 | Medium |
*/30 * * * * | ~48 | Medium |
0 * * * * | ~24 | Medium |
0 9 * * * | ~1 | Low |
| Weekly / monthly | <1 | Low |
| Unknown / natural language | — | Mark: schedule parse uncertain |
One concise sentence. Example: "One high-priority audit candidate found."
| Field | Value |
|---|---|
| Name | job / run / session name |
| ID | job_id or run identifier |
| Why flagged | Specific signal: schedule frequency, retry pattern, model tier, fallback chain, etc. |
| Estimated frequency | Approximate runs/day if schedule is available |
| Confidence | High / Medium / Low |
| Evidence depth | Level 1 / 2 / 3 |
Only include if there are meaningful candidates below the top one. For each:
Short list only. Do not overwhelm the user. Example:
One conservative next check. No edits. Example:
Inspect whether
hermes-health-watchdogcan become script-first — LLM-only-on-anomaly — instead of running an LLM on every scheduled tick when last run was "ok".
A bounded prompt for your agent to manually investigate the top candidate only.
Do not include instructions to edit, disable, delete, or mutate anything.
Please inspect this agent run for possible routing waste.
Run: <name / identifier>
Flagged because: <what triggered the flag — schedule frequency, model tier, retry pattern, etc.>
Evidence depth so far: <Level 1 / 2 / 3>
Do not edit, disable, delete, or mutate anything yet.
Inspect and report:
1. whether this is real routing or model-assignment waste
2. whether a normal "ok" run actually needed an LLM
3. whether script-first / anomaly-only / silent-on-ok is a safer policy
4. the safest manual next step, with no changes applied yet
Redact secrets. Do not expose raw private payloads.
Only output NEEDS INFO when:
Do not use NEEDS INFO for missing token counts, model names, or retry counts alone. A parseable cron list with a schedule is audit-eligible at Level 1.
This skill will not:
| waste-audit | agent-routing-waste-audit | |
|---|---|---|
| Focus | Recurring OpenClaw job waste | Routing decisions within runs |
| Input | OpenClaw cron jobs + runs | Any agent runtime: Hermes, OpenClaw, LiteLLM, PilotDeck, etc. |
| Signals | Token burn, delivery silence, error rate | Model tier, retry, fallback, sub-agent, local/cloud |
| Blocking requirement | None — schedule list enough for Level 1 | No token data required for Level 1; at least one parseable job/run/routing signal is required |
Do not run both on the same input without a clear reason. If the input is an OpenClaw cron job and the question is "should this keep running?", use waste-audit. If the question is "was this routed correctly?", use this skill.
"missing" in evidence tables; do not assume model names, token counts, or retry counts*/5, 1 for 0 9 * * *, etc.)NEEDS INFO only when input is truly unparseable or signal-freewaste-audit noted