---
name: Cost Tracking
slug: cost-tracking
category: Data
description: Cost Tracking shows engagement spend and return on investment for a pentest run. Use it to review which agents spent the most and whether the work produced findings worth the cost.
github: "https://github.com/H-mmer/pentest-agents/tree/main/.claude/skills/cost"
language: Python
stars: 804
forks: 156
install: "npx degit https://github.com/H-mmer/pentest-agents/tree/main/.claude/skills/cost ~/.claude/skills/cost"
installs_to: ~/.claude/skills/cost
source_path: .claude/skills/cost/SKILL.md
collection_size: 25
category_size: 668
collection_url: "https://dirskills.com/collections/H-mmer/pentest-agents"
added: 2026-08-22T05:22:34.078Z
last_synced: 2026-08-22T05:22:34.078Z
canonical_url: "https://dirskills.com/skills/cost-tracking"
---

# Cost Tracking

Cost Tracking shows engagement spend and return on investment for a pentest run. Use it to review which agents spent the most and whether the work produced findings worth the cost.

**Install:**

```bash
npx degit https://github.com/H-mmer/pentest-agents/tree/main/.claude/skills/cost ~/.claude/skills/cost
```

## README

Show engagement cost data.

Run these in sequence:
1. `uv run python3 $CLAUDE_PROJECT_DIR/tools/cost.py summary`
2. `uv run python3 $CLAUDE_PROJECT_DIR/tools/cost.py roi`
3. Provide analysis: which agents consumed the most, whether the spend is justified by findings.

## Top-Tier ROI Review

Cost review is a hunting control, not accounting trivia.

- Segment spend by phase: recon, ranking, hunting, validation, reporting, rework.
- Flag any agent class with high spend and low durable output: no new surface, no killed hypotheses, no confirmed evidence.
- Compare spend to expected value: bounty range, report probability, duplicate risk, and remaining proof work.
- Recommend one concrete budget move: continue, pivot class, reduce parallelism, raise min-score, skip noisy targets, or run a focused chain pass.
- Treat repeated false positives as a training signal. Link the spend spike to `/learn`, `/brain`, or rules updates.