Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add athola/claude-night-market --skill agent-expendituregit clone --depth 1 https://github.com/athola/claude-night-marketWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/athola/claude-night-market/agent-expenditure)<a href="https://agentmods.dev/skills/athola/claude-night-market/agent-expenditure"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/agent-expenditure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/athola/claude-night-market/agent-expenditure"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/agent-expenditure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.00641 |
| Opus 5 | $0.00015 | $0.00320 |
| Sonnet 5 | $0.00006 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
agent-expenditure scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Did each agent produce unique findings?
- Was total token expenditure proportional to value?
- Did any agent duplicate another's work?
- 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
- Dispatching 4 or more agents needs an agreed plan first: the roster, each agent's scope, and the output contract it returns. 1-3 agents may dispatch directly.
conserve:token-conservationfor session-level token budgetingconjure:agent-teamsfor 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.mdchecked 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
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 88 lines · 29 tokens per session scan A d5daf7d894e1
agent-expenditure is a skill published in the GitHub repository athola/claude-night-market (337 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 641 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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