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Agent Expenditure

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Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.

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  • Added September 12, 2026
ai-agentsgogit

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Scanned September 12, 2026

npx -y skills add thedixitjain/the-mega-skill-library --skill agent-expenditure --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: agent-expenditure
description: "Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run."
category: ai-agents-and-harness
source_repo: athola/claude-night-market
source_path: "plugins/conserve/skills/agent-expenditure/SKILL.md"
source_url: https://github.com/athola/claude-night-market/blob/HEAD/plugins/conserve/skills/agent-expenditure/SKILL.md
---

# Agent Token Waste Monitoring

## When To Use

- After parallel agent dispatch completes
- When evaluating whether to increase agent count
- During retrospectives on agent-heavy workflows
- When plan-before-large-dispatch rule triggers

## When NOT To Use

- Single-agent workflows (no coordination overhead)
- During active agent execution (post-hoc analysis)
- For token budgeting (use token-conservation instead)

## Brooks's Law for Agents

Dispatching more agents does not always help. Coordination overhead
grows with agent count:

| Agent Count | Expected Overhead | Guidance |
|-------------|-------------------|----------|
| 1-3 | Negligible | Dispatch freely |
| 4-5 | 10-15% | Acceptable; plan first |
| 6-8 | 20-30% | Monitor closely |
| 9+ | 30%+ | Likely counterproductive |

Coordination overhead is measured as shared-file conflicts: concurrent
Read/Write operations on the same file by different agents, as a
percentage of total agent runtime.

## Post-Dispatch Review Checklist

After parallel agent runs, evaluate:

1. Did each agent produce unique findings?
2. Was total token expenditure proportional to value?
3. Did any agent duplicate another's work?
4. Would fewer agents have produced the same result?

If 2+ questions answer no, reduce agent count in future dispatches
of the same type.

## Waste Signals

See `modules/waste-signals.md` for the 5 waste signal categories and
detection criteria.

## Cross-References

- `.claude/rules/plan-before-large-dispatch.md` for the 4+ agent
  planning requirement
- `conserve:token-conservation` for session-level token budgeting
- `conjure:agent-teams` for dispatch coordination

## Exit Criteria

- [ ] All 4 post-dispatch review questions answered with explicit
  yes/no per agent (unique findings, proportional expenditure, no
  duplication, fewer agents sufficient)
- [ ] Waste signals from `modules/waste-signals.md` checked against
  the completed run; any triggered signal named with the category
- [ ] A recommendation is produced: either "reduce agent count to N"
  or "dispatch was efficient" with coordination overhead percentage
- [ ] If 2+ review questions answer no, a concrete agent-count
  reduction is stated for future dispatches of the same type

---

**Source:** [`athola/claude-night-market`](https://github.com/athola/claude-night-market) → `plugins/conserve/skills/agent-expenditure/SKILL.md`

Files in this skill

  • SKILL.md2.8 KB
  • modules/waste-signals.md2.1 KB

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