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choosenobody

Agent Routing Waste Audit

by choosenobody · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install agent-routing-waste-audit
Description
Paste an agent job, cron, routing, or run summary and get an immediate read-only audit of possible routing, retry, fallback, or model-assignment waste. Progr...
README (SKILL.md)

Agent Routing Waste Audit

Overview

A 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.

Activation

Activate when a user types:

audit agent routing waste

Also activate for questions about:

  • whether a task used an overpowered model
  • whether retry loops burned tokens silently
  • whether fallback chains escalated cost without recovery
  • whether sub-agents were assigned to unnecessarily strong models
  • whether local/cloud model split was unclear or wasteful
  • whether a scheduled agent job still justifies its model tier

Do Not Use For

  • Recurring OpenClaw job waste with no routing question → use waste-audit instead
  • Full provider or API key configuration → not this skill's scope
  • Auto-fixing or auto-disabling anything → read-only by design
  • Financial, legal, or security advice → not this skill's scope

Start Here

Paste any one of these:

hermes cron list

or

  • an OpenClaw job list
  • an agent run summary
  • a LiteLLM / OpenRouter usage summary
  • a PilotDeck routing / session summary
  • a redacted JSON / CSV / log snippet

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.

Evidence Depth Levels

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.

Hermes Cron List Parser

When the input is raw hermes cron list output, the skill parses this block structure:

\x3Cjob_id> [active|paused|completed]
    Name:      \x3Cname>
    Schedule:  \x3Ccron expression>
    Repeat:    \x3C∞|number>
    Next run:  \x3CISO timestamp>
    Deliver:   \x3Ctarget>
    Last run:  \x3CISO timestamp>  \x3Cok|error|...>

Extract these fields:

  • job_id
  • state (active / paused / completed)
  • name
  • schedule (cron expression)
  • repeat (∞ or a number)
  • next_run (ISO timestamp)
  • delivery_target
  • last_run_time
  • last_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 \x3C1 Low
Unknown / natural language Mark: schedule parse uncertain

Output Structure


Initial Finding

One concise sentence. Example: "One high-priority audit candidate found."


Top Routing / Waste Candidate

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

Lower-Priority Candidates

Only include if there are meaningful candidates below the top one. For each:

  • Name + ID
  • Why it is lower priority
  • Estimated frequency

Missing Evidence

Short list only. Do not overwhelm the user. Example:

  • model / provider used
  • whether LLM is invoked every run
  • token usage for normal runs
  • whether normal "ok" outputs are useful

Suggested Manual Check

One conservative next check. No edits. Example:

Inspect whether hermes-health-watchdog can become script-first — LLM-only-on-anomaly — instead of running an LLM on every scheduled tick when last run was "ok".


Copy-Paste Prompt for Your Agent

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: \x3Cname / identifier>
Flagged because: \x3Cwhat triggered the flag — schedule frequency, model tier, retry pattern, etc.>
Evidence depth so far: \x3CLevel 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.

NEEDS INFO

Only output NEEDS INFO when:

  • input cannot be parsed at all (no identifiable job / run / session)
  • no schedule, model, retry, fallback, task, or recurrence signal exists
  • the user asks for a final policy decision but provides only a free-text description with no identifiable signals

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.


Safety Boundaries

This skill will not:

  • Edit, disable, delete, or mutate any config, job, or routing policy
  • Switch providers or models automatically
  • Apply hidden optimization or auto-fix behavior
  • Suggest downgrading code review, security, production, wallet, payment, or irreversible-action workflows without explicit human approval
  • Expose secrets or raw private logs
  • Fabricate missing fields or assume unknown values

Relationship to waste-audit

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.


Common Pitfalls

  1. Fabricating missing fields — use "missing" in evidence tables; do not assume model names, token counts, or retry counts
  2. Treating Level 1 as Level 3 — a preliminary finding from a schedule list has lower confidence; be honest about evidence depth
  3. Flagging all candidates as high-priority — rank by frequency and compounding cost; a daily job at 1 run/day is not the same as 288 runs/day
  4. Suggesting changes to production routing without a human review gate — every suggested policy change must include an explicit review step
  5. Running this instead of waste-audit for simple recurring job hygiene — they are siblings; use the right one
  6. Claiming broad native support for platforms not confirmed — parse what you can, label what you cannot

Verification Checklist

  • Input parsed at correct evidence level — Level 1 / 2 / 3 stated explicitly
  • Highest-frequency candidate ranked first
  • Frequency approximation correct for the cron expression (288 for */5, 1 for 0 9 * * *, etc.)
  • NEEDS INFO only when input is truly unparseable or signal-free
  • Missing evidence listed but does not block the preliminary finding
  • Copy-paste prompt instructs do-not-edit clearly
  • Safety boundaries present in output
  • If OpenClaw recurring job input, relationship to waste-audit noted
Usage Guidance
Install only if you want an automated code-review closeout helper. Before using it on private or sensitive diffs, note that fallback reviewers may receive generated diff prompts, and consider `--fallback-reviewer none`, `--no-yolo`, `AUTOREVIEW_YOLO=0`, or `AUTOREVIEW_AUTO_TESTS=0` when you want tighter control over tool access and automatic test execution.
Capability Tags
cryptorequires-walletrequires-sensitive-credentials
Capability Assessment
Purpose & Capability
The skill's capabilities match its stated purpose: running Codex review, optional fallback model reviewers, git diff collection, PR-base discovery, git fetch, and optional static tests for ClawHub code-review closeout.
Instruction Scope
The activation wording is somewhat broad for ClawHub maintainer workflows, but the instructions consistently keep the task to review, verification, tests, and reporting; no unrelated data access or hidden tasking was found.
Install Mechanism
The artifact consists of a SKILL.md and a local Bash helper under the skill directory; no package installer, auto-start hook, or hidden installation behavior was found.
Credentials
The helper can run nested Codex review with bypassed approvals and full-access sandbox by default, and can send generated diffs to configured fallback reviewer CLIs; this is disclosed and has options to disable, but users should understand the local-code and diff-sharing implications.
Persistence & Privilege
No background persistence was found. Output is written to stdout unless an output path or environment variable is supplied, and temporary prompt/output files are cleaned up.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-routing-waste-audit
  3. After installation, invoke the skill by name or use /agent-routing-waste-audit
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
First publish: cross-agent routing waste audit with progressive evidence handling, Level 1-3 depth, and read-only safety boundaries
Metadata
Slug agent-routing-waste-audit
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Agent Routing Waste Audit?

Paste an agent job, cron, routing, or run summary and get an immediate read-only audit of possible routing, retry, fallback, or model-assignment waste. Progr... It is an AI Agent Skill for Claude Code / OpenClaw, with 57 downloads so far.

How do I install Agent Routing Waste Audit?

Run "/install agent-routing-waste-audit" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent Routing Waste Audit free?

Yes, Agent Routing Waste Audit is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agent Routing Waste Audit support?

Agent Routing Waste Audit is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent Routing Waste Audit?

It is built and maintained by choosenobody (@choosenobody); the current version is v1.0.1.

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