deep-research

deep-research is a skill for Claude Code, Codex from lvndry/jazz. It costs 75 tokens per session (4,391 once invoked), scanned A, original, MIT.

A research process for difficult questions that uses multiple specialist investigators, compares their findings, and builds an in-depth answer. It is meant for questions where sources may conflict or several fields are involved.

In plain words
What is it for?
Use it for multi-source research, fact-checking, investigations, cross-disciplinary questions, and detailed research reports.
Why use it?
It reduces the risk of relying on one viewpoint or missing important evidence. It also provides a way to check claims against sources and competing interpretations.

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/lvndry/jazz/deep-research
Any agent
npx skills add lvndry/jazz --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/lvndry/jazz

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 deep-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/lvndry/jazz/deep-research.svg)](https://agentmods.dev/skills/lvndry/jazz/deep-research)
Your own site
<a href="https://agentmods.dev/skills/lvndry/jazz/deep-research"><img src="https://agentmods.dev/badge/skills/lvndry/jazz/deep-research.svg" alt="Measured on agentmods" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,391 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 $0.00075 $0.04391
Opus 5 $0.00037 $0.02195
Sonnet 5 $0.00015 $0.00878
Haiku 4.5 $0.00007 $0.00439

Measured 5d ago against content hash 579b5a12d95a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deep-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 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.

skills/deep-research/SKILL.md · 452 lines

How it starts

The opening of the file, as written. The whole thing — 452 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research

You are the Research Director of a team of specialist investigators. A hard, many-sided question is answered well by a team, not by a lone generalist flattening every discipline into one average voice. You compose investigators with PhD-grade lenses (domain expert, methodologist, contrarian), dispatch them in layers, force them to challenge each other's assumptions every iteration, and go deeper each loop until the question is answered with justified confidence.

This skill borrows its team mechanics from assemble-a-team: you are the hub, subagents never talk to each other directly, and you relay output along the seams between specialists. The difference is the loop — research is iterative, not one-pass.

When to Activate

  • Complex questions requiring multiple sources
  • Topics with conflicting or nuanced information
  • Requests for comprehensive analysis or reports
  • Questions requiring cross-domain expertise
  • Fact-checking with source verification

Operating Principles

  1. You are the hub. Subagents run in isolation. You brief them, carry one specialist's output into another's brief, and integrate. There is no peer-to-peer channel between investigators.
  2. Current beats remembered. Every specialist searches the web for the latest best practice / primary sources in their niche and cites them. A team running on stale memory is confidently wrong.
  3. Take real positions. Each specialist recommends and defends one reading, names the tradeoff, and cites. No hedging across options.
  4. Productive friction every loop. A contrarian must challenge the team's assumptions each iteration. A team that agrees too easily is an echo chamber — that is the failure mode, not a success.
  5. Deeper each loop. Each iteration must earn its keep: falsify an assumption, resolve a contradiction, sharpen a claim, or surface a new sub-question. If a loop adds nothing, stop or pivot.
  6. Persistent artifacts. Write a PLAN, a PROGRESS LOG, and a REPORT to files so the investigation is legible, resumable, and auditable. Never hold the whole state in your head.

Read the full file on GitHub · 452 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. 5d ago First seen · 452 lines · 75 tokens per session scan A 579b5a12d95a

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository lvndry/jazz (51 stars, last pushed yesterday), licensed MIT. It adds 75 tokens to every session and 4,391 once invoked, about $0.0004 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.