codebase-analysis

A structured workflow for examining a software project and producing a codebase analysis report. The report covers the project’s architecture, important files, recurring patterns, and recommended actions.

In plain words
What is it for?
It is for mapping a project, explaining what it does, identifying critical files, and recording findings for later use.
Why use it?
It gives developers a repeatable way to understand an unfamiliar codebase instead of relying on scattered file inspection. It also requires the analysis to be saved or otherwise handled after reporting.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/sequenzia/agent-alchemy/codebase-analysis
Any agent
npx skills add sequenzia/agent-alchemy --skill codebase-analysis
Clone the repo
git clone --depth 1 https://github.com/sequenzia/agent-alchemy

Made for: Claude Code, Codex.

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,228 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00093 $0.03228
Opus 5 $0.00046 $0.01614
Sonnet 5 $0.00019 $0.00646
Haiku 4.5 $0.00009 $0.00323

Measured 2d ago against content hash 193dfe501a3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codebase-analysis 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 2d 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.

claude/core-tools/skills/codebase-analysis/SKILL.md · 277 lines

How it starts

The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codebase Analysis Workflow

Execute a structured 3-phase codebase analysis workflow to gather insights.

CRITICAL: Complete ALL 3 phases. The workflow is not complete until Phase 3: Post-Analysis Actions is finished. After completing each phase, immediately proceed to the next phase without waiting for user prompts.

Phase Overview

  1. Deep Analysis — Explore and synthesize codebase findings via deep-analysis skill
  2. Reporting — Present structured analysis to the user
  3. Post-Analysis Actions — Save, document, or retain analysis insights

Phase 1: Deep Analysis

Goal: Explore the codebase and synthesize findings.

  1. Determine analysis context:

    • If $ARGUMENTS is provided, use it as the analysis context
    • If no arguments, set context to "general codebase understanding"
  2. Check for cached results:

    • Check if .claude/sessions/exploration-cache/manifest.md exists
    • If found, read the manifest and verify: codebase_path matches the current working directory, and timestamp is within the configured cache TTL (default 24 hours)
    • If cache is valid, use AskUserQuestion:
      • Use cached results (show the formatted cache date) — Read cached synthesis from .claude/sessions/exploration-cache/synthesis.md and recon from recon_summary.md. Set CACHE_HIT = true and CACHE_TIMESTAMP to the cache's timestamp. Skip step 3 and proceed directly to step 4.
      • Run fresh analysis — Remove the cache manifest file, set CACHE_HIT = false, and proceed to step 3
    • If no valid cache: set CACHE_HIT = false and proceed to step 3
  3. Run deep-analysis workflow:

    • Read ${CLAUDE_PLUGIN_ROOT}/skills/deep-analysis/SKILL.md and follow its workflow
    • Pass the analysis context from step 1
    • This handles reconnaissance, team planning, approval (auto-approved when skill-invoked), team creation, parallel exploration (code-explorer agents), and synthesis (code-synthesizer agent)
    • After completion, set CACHE_TIMESTAMP = null (fresh results, no prior cache)

Read the full file on GitHub · 277 lines

Files

What ships with it

2 files 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.

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. 2d ago First seen · 277 lines · 93 tokens per session scan A 193dfe501a3a

Subscribe to this mod's changes

codebase-analysis is a skill published in the GitHub repository sequenzia/agent-alchemy (43 stars, last pushed 3mo ago), licensed MIT. It adds 93 tokens to every session and 3,228 once invoked, about $0.0005 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 2026-08-30.

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