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.
npx agentmods add skills/bostonaholic/rpikit/researching-codebasenpx skills add bostonaholic/rpikit --skill researching-codebasegit clone --depth 1 https://github.com/bostonaholic/rpikitWrote 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.
[](https://agentmods.dev/skills/bostonaholic/rpikit/researching-codebase)<a href="https://agentmods.dev/skills/bostonaholic/rpikit/researching-codebase"><img src="https://agentmods.dev/badge/skills/bostonaholic/rpikit/researching-codebase.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.01555 |
| Opus 5 | $0.00016 | $0.00777 |
| Sonnet 5 | $0.00006 | $0.00311 |
| Haiku 4.5 | $0.00003 | $0.00155 |
Grade A, and why
researching-codebase 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Methodology
Research topic: $ARGUMENTS
Overview
Help turn research requests into thorough codebase understanding through natural collaborative dialogue.
Start by understanding what the user needs to learn, then ask questions one at a time to refine the scope. Once you understand what you're researching, explore the codebase systematically, presenting findings in digestible sections and validating as you go.
The Iron Law
Ask questions BEFORE exploring code.
Do not touch the codebase until the problem is understood. Resist the urge to immediately search for files or read code.
Phase 1: Understanding the Request
Your first action must be asking a clarifying question.
Do NOT:
- Read any files
- Search the codebase
- Use Glob or Grep
- Explore anything
- Make assumptions about what the user wants
Ask questions one at a time using AskUserQuestion:
- Prefer multiple choice questions when possible, but open-ended is fine too
- Only one question per message
- If a topic needs more exploration, break it into multiple questions
Focus on understanding:
- Purpose: What are they trying to accomplish? (build, change, fix, learn)
- Specifics: What exactly should happen or change?
- Scope: How big is this? (one file, multiple files, architectural)
- Constraints: Any requirements around performance, compatibility, security?
- Context: Have they already looked at anything or have hunches?
When you believe you understand, confirm:
Summarize your understanding and ask if it's accurate before proceeding. If anything needs clarification, ask follow-up questions.
Phase 2: Exploration
Only proceed after confirming understanding with the user.
Locate Relevant Files
Use the file-finder agent to locate files relevant to the research objective:
Task tool with subagent_type: "file-finder"
Prompt: "Find files related to [topic from interrogation]. Goal: [user's stated purpose]"
The file-finder will return a structured report with:
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.
- 5d ago First seen · 243 lines · 32 tokens per session scan A c0c4b9d257de
researching-codebase is a skill published in the GitHub repository bostonaholic/rpikit (20 stars, last pushed 5d ago), licensed MIT. It adds 32 tokens to every session and 1,555 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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