deep-research

deep-research is a skill for Claude Code, Codex from bugrabilge/bilge-development-kit. It costs 40 tokens per session (713 once invoked), scanned A, a copy of deep-research, MIT.

An automated research tool that plans searches, reads sources, and combines findings into a report.

In plain words
What is it for?
Use it for market analysis, competitor research, literature reviews, technical research, and due diligence.
Why use it?
It reduces the manual work of searching across many sources and organizing the results into a detailed, cited document.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 scripts/research.py --query "Research the history of Kubernetes".

Good fit Use it for market analysis, competitor research, literature reviews, technical research, and due diligence.

Compare 6 skills from other repositories ↓
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/bugrabilge/bilge-development-kit
agentmods
npx agentmods add skills/bugrabilge/bilge-development-kit/deep-research

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/bugrabilge/bilge-development-kit/deep-research/github.svg)](https://agentmods.dev/skills/bugrabilge/bilge-development-kit/deep-research)
Your own site
<a href="https://agentmods.dev/skills/bugrabilge/bilge-development-kit/deep-research"><img src="https://agentmods.dev/badge/skills/bugrabilge/bilge-development-kit/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.

agentmods 80×15 button for deep-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/bugrabilge/bilge-development-kit/deep-research"><img src="https://agentmods.dev/badge/skills/bugrabilge/bilge-development-kit/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 713 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 91% copy Near-identical to another mod 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 $0.00040 $0.00713
Opus 5.5 $0.00016 $0.00285
Sonnet 5.5 $0.00008 $0.00143
Haiku 4.5 $0.00004 $0.00071

Measured 1mo ago against content hash f30f8b4af0aa, 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 1mo 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.

Origin

This is a copy

91% identical to deep-research — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills-extra/deep-research/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gemini Deep Research Skill

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

When to Use This Skill

Use this skill when:

  • Performing market analysis
  • Conducting competitive landscaping
  • Creating literature reviews
  • Doing technical research
  • Performing due diligence
  • Need detailed, cited research reports

Requirements

  • Python 3.8+
  • httpx: pip install -r requirements.txt
  • GEMINI_API_KEY environment variable

Setup

  1. Get a Gemini API key from Google AI Studio
  2. Set the environment variable:
    export GEMINI_API_KEY=your-api-key-here
    
    Or create a .env file in the skill directory.

Usage

Start a research task

python3 scripts/research.py --query "Research the history of Kubernetes"

With structured output format

python3 scripts/research.py --query "Compare Python web frameworks" \
  --format "1. Executive Summary\n2. Comparison Table\n3. Recommendations"

Stream progress in real-time

python3 scripts/research.py --query "Analyze EV battery market" --stream

Start without waiting

python3 scripts/research.py --query "Research topic" --no-wait

Check status of running research

python3 scripts/research.py --status <interaction_id>

Wait for completion

python3 scripts/research.py --wait <interaction_id>

Continue from previous research

python3 scripts/research.py --query "Elaborate on point 2" --continue <interaction_id>

List recent research

python3 scripts/research.py --list

Output Formats

  • Default: Human-readable markdown report
  • JSON (--json): Structured data for programmatic use
  • Raw (--raw): Unprocessed API response

Cost & Time

Metric Value
Time 2-10 minutes per task
Cost $2-5 per task (varies by complexity)
Token usage ~250k-900k input, ~60k-80k output

Read the full file on GitHub · 115 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. 1mo ago First seen · 115 lines · 40 tokens per session scan A f30f8b4af0aa

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository bugrabilge/bilge-development-kit (10 stars, last pushed 6mo ago), licensed MIT. It adds 40 tokens to every session and 713 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to deep-research, differing in 8 lines, and is treated as a copy.

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