deepsearch

A structured method for searching a codebase in several passes, moving from broad searches to precise checks. It is designed to build an evidence-based understanding of how code and dependencies connect.

In plain words
What is it for?
Tracing a feature across files, finding every use before a refactor, checking dependency chains, identifying dead code, and investigating breaking changes.
Why use it?
A single text search can miss indirect connections, side effects, or uses hidden behind plugins and dynamic loading.

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/jeremydev87/codingbuddy/deepsearch
Any agent
npx skills add JeremyDev87/codingbuddy --skill deepsearch
Clone the repo
git clone --depth 1 https://github.com/JeremyDev87/codingbuddy

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,734 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 $0.00021 $0.01734
Opus 5 $0.00010 $0.00867
Sonnet 5 $0.00004 $0.00347
Haiku 4.5 $0.00002 $0.00173

Measured 2d ago against content hash f3983ab5649c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deepsearch 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.

packages/rules/.ai-rules/skills/deepsearch/SKILL.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Single-pass searches miss connections. Grep finds strings, not understanding.

Core principle: ALWAYS search in multiple passes with increasing precision. A single query never gives the full picture.

Violating the letter of this process is violating the spirit of thorough search.

The Iron Law

NO CONCLUSIONS WITHOUT CROSS-REFERENCED EVIDENCE FROM MULTIPLE PASSES

If you haven't completed at least Phases 1-3, your understanding is incomplete.

When to Use

Use when simple grep/glob is insufficient:

  • Understanding how a feature works end-to-end
  • Tracing data flow across multiple files/modules
  • Finding all usages and side effects before refactoring
  • Detecting dead code or unused exports
  • Mapping dependency chains
  • Understanding implicit relationships (event emitters, dynamic imports, reflection)
  • Auditing a pattern's usage across the codebase

Use this ESPECIALLY when:

  • Initial search returns too many or too few results
  • You need to understand "everything that touches X"
  • The codebase uses indirection (dependency injection, plugins, event systems)
  • You're about to make a breaking change
  • You need confidence that nothing was missed

Don't use when:

  • You know the exact file and symbol (use direct read)
  • A single grep gives you the complete answer
  • You're looking up a specific API signature

The Four Phases

You MUST complete each phase before drawing conclusions.

Phase 1: Broad Search — Cast a Wide Net

Goal: Discover all potentially relevant files and symbols.

  1. Start with Multiple Search Strategies

    • Search by name: function names, class names, variable names
    • Search by pattern: string literals, error messages, log statements
    • Search by structure: file naming conventions, directory patterns
    • Search by type: imports, exports, type definitions
  2. Use Varied Query Terms

    • Don't stop at the first query term
    • Try synonyms, abbreviations, related concepts
    • Search for both the interface and the implementation
    • Include test files — they reveal intended usage

Read the full file on GitHub · 215 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. 2d ago First seen · 215 lines · 21 tokens per session scan A f3983ab5649c

Subscribe to this mod's changes

deepsearch is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 1,734 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 2026-08-30.

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