analyze

analyze is a skill for Claude Code from pablocaeg/claude-army. It costs 29 tokens per session (735 once invoked), scanned A, original, MIT.

A project-analysis tool that examines a codebase, its development setup, coding patterns, tests, and pull-request history. A pull request is a proposed code change submitted for review.

In plain words
What is it for?
Use it to identify the tech stack, build and test commands, lint rules, directory patterns, extension mechanisms, continuous-integration setup, and review practices.
Why use it?
It gathers the project context needed before creating coding agents, so those agents can follow the repository’s actual conventions instead of guessed ones.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the claude-army plugin — 3 skills shipped together

Good fit Use it to identify the tech stack, build and test commands, lint rules, directory patterns, extension mechanisms, continuous-integration setup, and review practices.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pablocaeg/claude-army/analyze
Install

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.

Any agent
npx skills add pablocaeg/claude-army --skill analyze
Clone the repo
git clone --depth 1 https://github.com/pablocaeg/claude-army

Made for: Claude Code.

Or install claude-army, the plugin that ships this one along with the rest of its 3 skills.

Wrote 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.

agentmods badge for analyze

README.md
[![agentmods](https://agentmods.dev/badge/skills/pablocaeg/claude-army/analyze.svg)](https://agentmods.dev/skills/pablocaeg/claude-army/analyze)
Your own site
<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>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 735 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 8d ago against content hash 518190ab6369, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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.

skills/analyze/SKILL.md · 100 lines

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]

Read the full file on GitHub · 100 lines

Changes

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.

  1. 8d ago First seen · 100 lines · 29 tokens per session scan A 518190ab6369

Subscribe to this mod's changes

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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