What is deep-research?

A source-backed workflow for answering research questions with an agent-written brief and saved source material. It is intended for literature reviews, technical investigations, market research, and current-state analysis.

Use it to gather, capture, assess, and cite information for a research brief.

It makes important claims traceable to sources and distinguishes facts from interpretation, uncertainty, and missing evidence.

deep-research — Skill for Codex by keysersoose/claude-code-setup

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/keysersoose/claude-code-setup

agentmods

npx agentmods add skills/keysersoose/claude-code-setup/deep-research

Made for: 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/keysersoose/claude-code-setup/deep-research/github.svg)](https://agentmods.dev/skills/keysersoose/claude-code-setup/deep-research)

Your own site

<a href="https://agentmods.dev/skills/keysersoose/claude-code-setup/deep-research"><img src="https://agentmods.dev/badge/skills/keysersoose/claude-code-setup/deep-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/keysersoose/claude-code-setup/deep-research"><img src="https://agentmods.dev/badge/skills/keysersoose/claude-code-setup/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,120 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.

Model	Per session	Once invoked
Fable 5.1	$0.00071	$0.02120
Opus 5.5	$0.00028	$0.00848
Sonnet 5.5	$0.00014	$0.00424
Haiku 4.5	$0.00007	$0.00212

Measured 2mo ago against content hash 74674bafa4b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 2mo ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/batch_capture.py, scripts/test_batch_capture.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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 · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research

Overview

Use this skill for research where claims must be traceable to sources. It is harness-neutral, but the default discovery-to-capture path is explicit: use sibling advanced-web-search/scripts/opencli_google_search.py to save candidate URLs as JSON, then use this skill's scripts/batch_capture.py --search-json to crawl them with Crawl4AI, then read the raw markdown and write the final brief.

Runtime requirement: Crawl4AI must be installed for raw capture. Install with python -m pip install -U crawl4ai, then run crawl4ai-setup and crawl4ai-doctor. See ../crawl4ai/SKILL.md.

Operating Contract

Prefer official, primary, and direct sources.
Use multiple targeted query classes, not one broad query.
Treat search snippets as leads, not evidence.
Inspect extraction quality; do not treat HTTP success as content success.
Separate facts, interpretation, recommendations, counter-evidence, open questions, and confidence.
Cite material claims with URLs or local raw/source artifact paths.
Label blocked, partial, old, borderline, and inferred evidence.
For durable research, write artifacts in the Hermes Obsidian layout, not a generic flat folder.

Workflow

Phase 0: Scope

Restate the question, decision target, constraints, time window, output format, and source classes needed. Ask a concise clarifying question only if ambiguity changes the source universe or tool calls materially.

Completion: scope is clear enough to define at least four query classes.

Phase 1: Discovery

Use advanced-web-search/scripts/opencli_google_search.py when it is available. Do not use a harness built-in web search as the primary discovery step when OpenCLI is available. Read references/query-patterns.md when constructing the search plan.

Always save discovery output to a JSON file with --output:

python ../advanced-web-search/scripts/opencli_google_search.py \
  --query "Hybrid XBRL tagging after:2026-03-01" \
  --query "site:github.com XBRL AI tagging after:2026-03-01" \
  --max-results 30 \
  --pages 8 \
  --output outputs/hybrid_xbrl_sources.json

Read the full file on GitHub · 174 lines

Files

What ships with it

10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

2mo ago First seen · 174 lines · 71 tokens per session scan A 74674bafa4b0

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository keysersoose/claude-code-setup (2 stars, last pushed 4mo ago), licensed MIT. It adds 71 tokens to every session and 2,120 once invoked, about $0.0003 per session on Opus 5.5. 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.

Research

deep-research next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
deep-researchkeysersoose/claude-code-setup	Skill	2	4mo ago	MIT	A	71	Codex
imagegenopenai/codex	Skill	134k	today	Apache-2.0	A	113	Codex
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	yesterday	MIT	A	200	Claude Code, Codex
playwright-climicrosoft/playwright	Skill	100k	yesterday	Apache-2.0	A	19	Claude Code
browser-automationopenclaw/openclaw	Skill	394k	today	MIT	A	36	Claude Code
systematic-debuggingobra/superpowers	Skill	314k	4d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	today	MIT	A	95	Claude Code