deep-research

deep-research is a skill for Claude Code from joaquimscosta/arkhe-claude-plugins. It costs 86 tokens per session (999 once invoked), scanned A, original, MIT.

A research workflow for investigating technical topics, best practices, patterns, and software architectures. It saves research so the same findings can be reused across projects.

In plain words
What is it for?
Researching a topic, retrieving saved findings, refreshing outdated research, and promoting useful results into version-controlled project documentation.
Why use it?
It reduces repeated web research and keeps useful technical findings available for future work and team reference.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_SKILL_DIR} variable. Also seen: reads .claude/ paths.

Part of the core plugin — 5 skills, 7 commands, 6 agents shipped together

Good fit Researching a topic, retrieving saved findings, refreshing outdated research, and promoting useful results into version-controlled project documentation.

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

Made for: Claude Code.

Or install core, the plugin that ships this one along with the rest of its 5 skills, 7 commands, 6 agents.

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/joaquimscosta/arkhe-claude-plugins/deep-research/github.svg)](https://agentmods.dev/skills/joaquimscosta/arkhe-claude-plugins/deep-research)
Your own site
<a href="https://agentmods.dev/skills/joaquimscosta/arkhe-claude-plugins/deep-research"><img src="https://agentmods.dev/badge/skills/joaquimscosta/arkhe-claude-plugins/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/joaquimscosta/arkhe-claude-plugins/deep-research"><img src="https://agentmods.dev/badge/skills/joaquimscosta/arkhe-claude-plugins/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 999 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 $0.00086 $0.00999
Opus 5 $0.00043 $0.00500
Sonnet 5 $0.00017 $0.00200
Haiku 4.5 $0.00009 $0.00100

Measured 10d ago against content hash 1a117f790c3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, 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 10d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/cache_manager.py, scripts/index_generator.py, scripts/promote.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.

plugins/core/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

Coordinate deep technical research with intelligent caching for cross-project reuse and team knowledge sharing.

Quick Start

When research is needed:

  1. Scripts path - ${CLAUDE_SKILL_DIR}/scripts/
  2. Single fetch call - Run python3 ${CLAUDE_SKILL_DIR}/scripts/cache_manager.py fetch "{topic}" (combines check+get)
  3. If exists=true - Present the content field directly (no agent needed). Suggest promote if valid, refresh if expired.
  4. If exists=false - Invoke deep-researcher agent for EXA research, which caches via cache_manager.py put
  5. Report findings - Include cache status and promote suggestion

Cache Architecture

Tier Location Purpose Shared
1 ~/.claude/plugins/research/ Fast, cross-project User only
2 docs/research/ or JD-resolved path Curated, version controlled Team

Operations

Operation Trigger Fast Path? Action
Research /research <topic> or natural language Yes (cache hit) Check cache → return if valid, else research → cache
Promote /research promote <slug> Yes Run promote.py {slug} directly
Refresh /research refresh <slug> No Spawn agent → fresh research → cache → update promoted
List /research list Yes Run cache_manager.py list (project-scoped by default, --all for everything)

JD-Aware Path Resolution

Promote and refresh operations detect .jd-config.json to resolve the research output path. If an area containing "research" exists (e.g. "30": "research"), output goes to docs/30-research/. Otherwise falls back to docs/research/. The frontmatter standard is defined by the research-frontmatter skill in the doc plugin.

Project Scoping

Research entries are automatically associated with the current git repository when cached. The list operation filters by current project by default, so each project sees only its relevant research. Use --all to see everything.

Read the full file on GitHub · 98 lines

Files

What ships with it

7 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.

  1. 10d ago First seen · 98 lines · 86 tokens per session scan A 1a117f790c3a

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository joaquimscosta/arkhe-claude-plugins (21 stars, last pushed 27d ago), licensed MIT. It adds 86 tokens to every session and 999 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.