explore

explore is a skill for Claude Code, Codex from Bidiche49/claude-conf. It costs 18 tokens per session (361 once invoked), scanned A, original, MIT.

A structured codebase exploration workflow for investigating a topic across project files, documentation, and sometimes the web. It breaks the question into focused searches and combines the findings into a report.

In plain words
What is it for?
Exploring how a project works, locating relevant files and patterns, answering technical questions, and giving recommendations when requested.
Why use it?
It reduces unfocused browsing and makes the evidence, gaps, and conclusions easier to review.

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/bidiche49/claude-conf/explore
Any agent
npx skills add Bidiche49/claude-conf --skill explore
Clone the repo
git clone --depth 1 https://github.com/Bidiche49/claude-conf

Made for: Claude Code, Codex.

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 explore

README.md
[![agentmods](https://agentmods.dev/badge/skills/bidiche49/claude-conf/explore.svg)](https://agentmods.dev/skills/bidiche49/claude-conf/explore)
Your own site
<a href="https://agentmods.dev/skills/bidiche49/claude-conf/explore"><img src="https://agentmods.dev/badge/skills/bidiche49/claude-conf/explore.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 361 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 $0.00018 $0.00361
Opus 5 $0.00009 $0.00180
Sonnet 5 $0.00004 $0.00072
Haiku 4.5 $0.00002 $0.00036

Measured 4d ago against content hash d71599907213, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

explore 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 4d 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.

explore/skills/explore/SKILL.md · 53 lines

What it actually says

Explore #$ARGUMENTS in depth using a structured, parallel approach.

Process

  1. Plan (30 seconds max):

    • Break the topic into 2-3 specific sub-questions
    • Identify what to search: codebase, docs, web, or all
  2. Explore (parallel agents):

    • Launch 1-2 agents maximum for codebase search
    • Launch 1 agent for web/docs if library-specific knowledge needed
    • Each agent has a focused question, not a vague "look around"
  3. Synthesize:

    • Merge findings from all agents
    • Identify conflicts or gaps
    • Produce a structured report

Report format

Exploration: [topic]

Key findings
  • [Finding 1 — with file:line references where applicable]
  • [Finding 2]
Architecture / Patterns
  • [How the codebase handles this]
Recommendations
  • [If the user asked "how should we..." — concrete recommendation]
  • [If the user asked "how does..." — no recommendation needed]
Files explored
  • path/to/file — [what was found]

Rules

  • NEVER explore without a plan — even 30 seconds of planning saves 5 minutes of wandering
  • Max 2 parallel agents during explore — more creates context fragmentation
  • Always include file:line references — vague answers are worthless
  • If the topic is too broad, narrow it and tell the user what you narrowed
  • If stuck after 2 minutes: stop exploring, report what you found, ask the user to refine
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. 4d ago First seen · 53 lines · 18 tokens per session scan A d71599907213

Subscribe to this mod's changes

explore is a skill published in the GitHub repository Bidiche49/claude-conf (2 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 361 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.

Related

Other skills, from other repositories

hooks-eval

Evaluate hook security, performance, and SDK compliance. Use for audits.

athola/claude-night-market · 18 tokens

webmcp-setup

Bootstraps webmcp-react into an existing React or Next.js app. Installs dependencies, adds WebMCPProvider, creates a first tool, and configures the MCP client bridge. Use when the user wants to set up WebMCP, add MCP tools to their app, integrate webmcp-react, or make their React app accessible to AI agents.

agentcathq/webmcp-react · 80 tokens

goal

Run a large or unfamiliar goal through the full ballast pipeline — mobilize what you already hold, terrain scan, full skeleton, atomic foundation learning with verification, then build from bedrock to a verified done. Use when the user hands over a big goal, enters a new field, or asks to learn X in order to achieve Y.

svy04/ballast · 69 tokens

report

Read the delivery log and say which rules actually fire, which never have, and what to prune or fix. Use when the user asks whether ballast is doing anything, wants to clean up their rule catalog, or on a periodic review.

svy04/ballast · 49 tokens

engram

Claude Engram persistent memory — quick reference for all MCP tools and automatic hook behaviors. Use when you need to remember how to store, search, or manage memories, or query session history.

20alexl/claude-engram · 41 tokens

eval-harness

Assessment-driven development — Quantify code generation quality with pass@k / pass^k metrics, automatically scored by Grader.

majiayu000/vibeguard · 29 tokens