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 pablocaeg/claude-army --skill analyzegit clone --depth 1 https://github.com/pablocaeg/claude-armyWrote 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/pablocaeg/claude-army/analyze)<a href="https://agentmods.dev/skills/pablocaeg/claude-army/analyze"><img src="https://agentmods.dev/badge/skills/pablocaeg/claude-army/analyze.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00735 |
| Opus 5 | $0.00015 | $0.00367 |
| Sonnet 5 | $0.00006 | $0.00147 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
analyze 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 8d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze the current project to prepare for agent team creation. Read everything relevant and produce a structured analysis.
Step 1: Project Foundation
Read these files if they exist:
- README.md, CONTRIBUTING.md, CHANGELOG.md
- .github/pull_request_template.md
- .github/ISSUE_TEMPLATE/
Step 2: Tech Stack
Identify:
- Language and version (go.mod, package.json, Cargo.toml, pyproject.toml, etc.)
- Build system and commands
- Linter config with exact rules
- Test framework, assertion library, coverage requirements
- CI/CD workflows (.github/workflows/)
Step 3: Code Patterns
- Map directory structure with Glob
- Read 5-10 key source files for patterns
- Read 5-10 test files for testing conventions
- Identify the extension/plugin/registration pattern (how new features are added)
Step 4: PR Review Analysis
Find the lead reviewer:
gh pr list --state all --limit 100 --json number,reviews --jq '.[].reviews[].author.login' 2>/dev/null | sort | uniq -c | sort -rn | head -5
Find external contributor PRs:
gh pr list --state all --limit 200 --json number,title,state,author --jq '.[] | "\(.number) [\(.state)] \(.author.login): \(.title)"' 2>/dev/null
For each external PR with lead reviewer feedback, extract BOTH:
PR-level reviews:
gh api repos/OWNER/REPO/pulls/NUMBER/reviews --jq '.[] | select(.user.login == "REVIEWER") | .body' 2>/dev/null
Inline code comments:
gh api repos/OWNER/REPO/pulls/NUMBER/comments --jq '.[] | select(.user.login == "REVIEWER") | "FILE: \(.path):\(.line // .original_line)\nCOMMENT: \(.body[:400])"' 2>/dev/null
Analyze at least 15-20 PRs. Rank reviewer patterns by frequency into tiers.
Step 5: Context Folder
Read everything in .context/ if it exists.
Output
Save the analysis to .context/forge-analysis.md with these sections:
# Forge Analysis: [Project Name]
## Tech Stack
[language, build, linter, test framework, CI]
## Code Patterns
[file structure, naming conventions, registration pattern]
## Test Conventions
[package naming, assertion library, fixture patterns, coverage requirement]
## PR Review Patterns
### Lead Reviewer: [name]
### Tier 1 (50%+ of PRs)
[patterns with exact quotes]
### Tier 2 (25-50%)
[patterns with exact quotes]
### Tier 3 (10-25%)
[patterns with exact quotes]
### Things NOT to Flag
[verified false positives]
## PR Format
[title format, body structure, checklist]
## Contribution Type
[what external contributors typically add]
## Build/Generate Commands
[commands that must run before submitting]
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.
- 8d ago First seen · 100 lines · 29 tokens per session scan A 518190ab6369
analyze is a skill published in the GitHub repository pablocaeg/claude-army (2 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 735 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 2026-08-31.
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