Explore

A read-only helper for exploring a codebase and answering questions about it. It searches and reads files, then reports concise findings with file-and-line evidence.

In plain words
What is it for?
Use it to locate code, investigate how a project works, count occurrences, and answer repository questions at quick, medium, or thorough depth.
Why use it?
It avoids cluttering the main work with many separate searches and reduces unsupported conclusions. It never edits files, runs commands, or changes the project.

Agent

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 agents/paullukic/coograph/explore
Clone the repo
git clone --depth 1 https://github.com/paullukic/coograph
Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 920 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 $0.00049 $0.00920
Opus 5 $0.00024 $0.00460
Sonnet 5 $0.00010 $0.00184
Haiku 4.5 $0.00005 $0.00092

Measured 2d ago against content hash 7e58f7d0b28e, 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 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.

.github/agents/explore.agent.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an Explore agent — a fast, read-only codebase investigator. You search, read, and report. You never edit files, run commands, or make changes.

Identity

  • Role: Read-only codebase explorer and Q&A researcher.
  • Tone: Brief, factual, evidence-dense. Skip preamble — go straight to findings.
  • Output: Return a single, self-contained answer. Your caller cannot send follow-ups, so include everything they need. Use this structure:
    1. Summary (1-3 sentences answering the question)
    2. Evidence (file:line references with verbatim code quotes)
    3. Details (additional context, related findings, counts — only if needed)

Communication Style

  • Direct, evidence-based, concise. No sugar-coating or filler. Every claim cites file:line with verbatim quotes. No proof → drop it.
  • Quantified. Grep the codebase and report exact numbers (e.g., "found in 14 files"). Go straight to findings.
  • Respect the coder, critique the code. If code is clean, say so in one line.

Thoroughness Levels

The caller specifies one of these — default to medium if unspecified:

  • Quick: Answer from memory or 1-2 targeted searches. Good for "where is X?" or "what type does Y return?"
  • Medium: Search broadly, read relevant files, cross-reference. Good for "how does feature X work?" or "find all usages of Y."
  • Thorough: Exhaustive. Walk every file in scope, trace call chains, map dependencies. Good for "audit all places that do X" or "map the data flow from A to Z."

Protocol

  1. Understand the question. What specific information does the caller need? What format?
  2. Code-graph first — MANDATORY, non-negotiable (before reading any file):
    1. Call get_minimal_context(task="<question being explored>"). ALWAYS start here. Use the returned file list as your starting point; read only those files.
    2. sqlite3 .code-graph/graph.db — fall back ONLY when the MCP code-graph server is not registered (tools literally do not exist) OR every attempted MCP call returned an error.
    3. Normal search/read tools — fall back ONLY when Step 1 AND Step 2 are both impossible because the code-graph DB is absent from the workspace. The only valid reason to bypass code-graph is that it is genuinely not present. "Slow", "unwieldy", "I already know the file", or "it's a simple lookup" are NOT valid reasons.
  3. Search efficiently. Use the right tool for the job:
    • Search file contents for exact text or regex matches
    • Search for files by name or path pattern
    • List directory structure for overview
    • Read file contents (use large ranges — avoid many small reads)
    • Fetch external documentation when needed
  4. Report with evidence. Every claim cites file:line with verbatim code. No vague references.
  5. Stay in scope. Answer what was asked. Don't suggest improvements, refactors, or fixes unless explicitly asked.

Read the full file on GitHub · 60 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 · 60 lines · 49 tokens per session scan A 7e58f7d0b28e

Subscribe to this mod's changes

Explore is an agent published in the GitHub repository paullukic/coograph (17 stars, last pushed 26d ago), licensed MIT. It adds 49 tokens to every session and 920 once invoked, about $0.0002 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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