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searcharvester-deep-research

searcharvester-deep-research is a skill for Claude Code, Codex from vakovalskii/searcharvester. It costs 107 tokens per session (3,947 once invoked), scanned A, original, AGPL-3.0.

A research workflow that splits a question among several AI helpers, including researchers, a critic, and a fact-checker, then combines their findings into a cited report.

In plain words
What is it for?
Use it for multi-part investigations that need source citations, adversarial checking, and verification of dates or numbers.
Why use it?
It reduces the need to handle broad research, opposing evidence, and date or number checks separately. The result is organized in one report file.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

not rated 281repo +2 changed 1mo ago A scan 107 tokens AGPL-3.0

Good fit Use it for multi-part investigations that need source citations, adversarial checking, and verification of dates or numbers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vakovalskii/searcharvester/searcharvester-deep-research
View source ↗ vakovalskii/searcharvester
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 vakovalskii/searcharvester --skill searcharvester-deep-research
Clone the repo
git clone --depth 1 https://github.com/vakovalskii/searcharvester

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 searcharvester-deep-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/vakovalskii/searcharvester/searcharvester-deep-research/github.svg)](https://agentmods.dev/skills/vakovalskii/searcharvester/searcharvester-deep-research)
Your own site
<a href="https://agentmods.dev/skills/vakovalskii/searcharvester/searcharvester-deep-research"><img src="https://agentmods.dev/badge/skills/vakovalskii/searcharvester/searcharvester-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 searcharvester-deep-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/vakovalskii/searcharvester/searcharvester-deep-research"><img src="https://agentmods.dev/badge/skills/vakovalskii/searcharvester/searcharvester-deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,947 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 unknown 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 $0.00107 $0.03947
Opus 5.5 $0.00043 $0.01579
Sonnet 5.5 $0.00021 $0.00789
Haiku 4.5 $0.00011 $0.00395

Measured 1mo ago against content hash 0b51b7ac5b80, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

searcharvester-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.

hermes_skills/searcharvester-deep-research/SKILL.md · 453 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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 Changed · +25 lines 0b51b7ac5b80
  2. 2mo ago First seen · 428 lines · 107 tokens per session scan A 81d23d962e66

Subscribe to this mod's changes

searcharvester-deep-research is a skill published in the GitHub repository vakovalskii/searcharvester (281 stars, last pushed 1mo ago), licensed AGPL-3.0. It adds 107 tokens to every session and 3,947 once invoked, about $0.0004 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 2026-08-30.

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Related

searcharvester-deep-research compared with skills from other repositories

searcharvester-deep-research next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
searcharvester-deep-researchvakovalskii/searcharvesterSkill2811mo agoAGPL-3.0A107Claude Code, Codex
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ardot_design_corecrane-in-clear-sky/WorkWit-AI-AgentSkill1082mo agononeA132Claude Code
humanizer_zhcrane-in-clear-sky/WorkWit-AI-AgentSkill1082mo agononeA121Claude Code
multimodal_generationcrane-in-clear-sky/WorkWit-AI-AgentSkill1082mo agononeA146Claude Code
tdoc_orchestratorcrane-in-clear-sky/WorkWit-AI-AgentSkill1082mo agononeA163Claude Code