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research

research is a skill for Claude Code from juicesharp/rpiv-pi. It costs 42 tokens per session (3,509 once invoked), scanned A, original, MIT.

A structured research workflow that answers questions through parallel analysis agents. It takes a questions document produced by a separate discovery step and saves the research in the project's shared thoughts folder.

In plain words
What is it for?
Use it when you already have a discovery questions artifact and need structured analysis recorded in the repository.
Why use it?
It provides a repeatable way to turn prepared research questions into a written research document. It cannot be used as a standalone research step without that questions document.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions CLAUDE.md.

not rated 11repo 4mo ago A scan 42 tokens original MIT

Good fit Use it when you already have a discovery questions artifact and need structured analysis recorded in the repository.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/juicesharp/rpiv-pi/research
View source ↗ juicesharp/rpiv-pi
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.

Any agent
npx skills add juicesharp/rpiv-pi --skill research
Clone the repo
git clone --depth 1 https://github.com/juicesharp/rpiv-pi

Made for: Claude Code.

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 research

README.md
[![agentmods](https://agentmods.dev/badge/skills/juicesharp/rpiv-pi/research/github.svg)](https://agentmods.dev/skills/juicesharp/rpiv-pi/research)
Your own site
<a href="https://agentmods.dev/skills/juicesharp/rpiv-pi/research"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-pi/research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for research

Your own site · 80×15
<a href="https://agentmods.dev/skills/juicesharp/rpiv-pi/research"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-pi/research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,509 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00042 $0.03509
Opus 5 $0.00021 $0.01754
Sonnet 5 $0.00008 $0.00702
Haiku 4.5 $0.00004 $0.00351

Measured 10d ago against content hash 5f8d3e8850c7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

research 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 10d 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.

skills/research/SKILL.md · 305 lines

How it starts

The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Questions Source

If the user has not already provided a specific discover artifact path, ask them for it before proceeding. Their input will appear as a follow-up paragraph after this skill body.

Research

You are tasked with answering structured research questions by spawning targeted analysis agents and synthesizing their findings into a comprehensive research document. This skill consumes questions artifacts produced by the discover skill.

Step 1: Read Questions Artifact

  1. Determine input:

    Questions artifact provided (path to a .md file in thoughts/):

    • Read the questions artifact FULLY using the Read tool WITHOUT limit/offset
    • Extract: Discovery Summary, Questions (dense paragraphs), frontmatter metadata (topic, tags)
    • The Discovery Summary provides the file landscape overview — no need to re-discover

    No arguments provided:

    I'll answer research questions from a questions artifact. Please provide the path:
`/skill:research thoughts/shared/questions/YYYY-MM-DD_HH-MM-SS_topic.md`

This skill requires a questions artifact from discover.
There is no standalone path — run /skill:discover first to produce a questions artifact.

    Then wait for input.

  2. Read key shared files referenced across multiple questions into main context — especially shared utilities, type definitions, and integration points that multiple questions mention.

  3. Analyze question overlap for grouping:

    • Parse all question paragraphs and extract file references from each
    • Identify questions that share 2+ file references — these are candidates for grouping
    • Group related questions together (2-3 questions per group max)
    • Questions with no significant file overlap remain standalone
    • Target: 3-6 agent dispatches total (grouped + standalone)

  4. Report chained status:

    [Chained]: Found research questions for "[topic]". [N] questions in [G] groups, [M] shared files.

Step 2: Dispatch Analysis Agents

Read the full file on GitHub · 305 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. 10d ago First seen · 305 lines · 42 tokens per session scan A 5f8d3e8850c7

Subscribe to this mod's changes

research is a skill published in the GitHub repository juicesharp/rpiv-pi (11 stars, last pushed 4mo ago), licensed MIT. It adds 42 tokens to every session and 3,509 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.

Research
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