deep-research

deep-research is a skill for Claude Code from softspark/ai-toolkit. It costs 69 tokens per session (2,207 once invoked), scanned A, original, Apache-2.0.

A method for carrying out research across several web sources and combining the findings carefully. It explains when a question needs multiple sources, how to search, and how to handle conflicting evidence.

In plain words
What is it for?
Use it to plan multi-source web research, compare evidence, verify facts, and write supported summaries.
Why use it?
It prevents spending too much effort on simple facts and helps reduce errors in contested, recent, or changing information. It also encourages checking claims against reliable original sources.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the ai-toolkit plugin — 115 skills, 44 agents, 14 hooks shipped together

Good fit Use it to plan multi-source web research, compare evidence, verify facts, and write supported summaries.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/softspark/ai-toolkit/deep-research
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 softspark/ai-toolkit --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/softspark/ai-toolkit

Made for: Claude Code.

Or install ai-toolkit, the plugin that ships this one along with the rest of its 115 skills, 44 agents, 14 hooks.

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/softspark/ai-toolkit/deep-research/github.svg)](https://agentmods.dev/skills/softspark/ai-toolkit/deep-research)
Your own site
<a href="https://agentmods.dev/skills/softspark/ai-toolkit/deep-research"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/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/softspark/ai-toolkit/deep-research"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,207 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00069 $0.02207
Opus 5.5 $0.00028 $0.00883
Sonnet 5.5 $0.00014 $0.00441
Haiku 4.5 $0.00007 $0.00221

Measured 1mo ago against content hash 737ca6cb6c63, 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.

app/skills/deep-research/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research

This is the web / multi-source counterpart to research-mastery. That skill is KB-first: it answers from the project's own knowledge base and only reaches outward when the KB comes up empty. This one governs what happens once you are already out on the open web pulling from many independent sources and have to weave them into one trustworthy answer. It is a method, not a fetcher — it does not retrieve anything by itself. You supply the search and fetch tools (built-in WebSearch / WebFetch, or the runtime deep-research command); this skill tells you how to spend them and how hard to doubt what comes back.

Retrieve-vs-Answer Gate

Run this gate before you spend a single search:

  1. Is the answer already in the KB or your own context? Then this is not a deep-research job — hand it to research-mastery (which checks RAG-MCP first) or just answer.
  2. Is it one stable fact with a single obvious authority (a constant, a published spec value, a definition that does not move)? One targeted lookup, confirm, done. Do not open a research campaign.
  3. Does it need several independent sources reconciled, or is it contested, recent, or moving? That is the case this skill exists for. Continue.

Skipping this gate is the most common failure: people fan out ten searches on a question that one source already settled, or worse, answer a contested question from memory because it "felt known."

Scale Effort to Complexity

Match the search budget to the question. Burning twenty searches on a lookup wastes turns; doing two searches on a contested synthesis ships a half-checked claim.

Question shape Plan first? Rough search budget
Single stable fact, clear authority no 1, maybe a second to confirm
Compare a few known options / current state of one topic light a handful, broaden then narrow
Contested, multi-faceted, or "what is the latest on…" yes — write the plan many, with follow-ups as conflicts surface

Read the full file on GitHub · 98 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 · 98 lines · 69 tokens per session scan A 737ca6cb6c63

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository softspark/ai-toolkit (180 stars, last pushed yesterday), licensed Apache-2.0. It adds 69 tokens to every session and 2,207 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 2026-09-03.