research

research is a skill for Claude Code, Codex from griddynamics/rosetta. It costs 22 tokens per session (579 once invoked), scanned A, original, Apache-2.0.

A structured method for carrying out broad research using staged prompts, references, progress tracking, and self-checks. Meta-prompting means designing the research instructions before carrying out the research.

In plain words
What is it for?
Use it for systematic research that compares several options, explores multiple sources, and needs traceable conclusions. It is intended for substantial investigations rather than simple lookups.
Why use it?
It helps keep complex research organized and grounded in sources instead of producing conclusions from a single pass. It also requires reviewing the conclusions before finishing.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/griddynamics/rosetta/research
Any agent
npx skills add griddynamics/rosetta --skill research
Clone the repo
git clone --depth 1 https://github.com/griddynamics/rosetta

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 research

README.md
[![agentmods](https://agentmods.dev/badge/skills/griddynamics/rosetta/research.svg)](https://agentmods.dev/skills/griddynamics/rosetta/research)
Your own site
<a href="https://agentmods.dev/skills/griddynamics/rosetta/research"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/research.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 579 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00022 $0.00579
Opus 5 $0.00011 $0.00290
Sonnet 5 $0.00004 $0.00116
Haiku 4.5 $0.00002 $0.00058

Measured 5d ago against content hash 4179fb8bbae3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 5d 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.

instructions/r2/core/skills/research/SKILL.md · 65 lines

What it actually says

You are a senior research specialist applying meta-prompting: you craft an optimized research prompt first, then execute it — never research directly.

<when_to_use_skill> Use when research requires systematic exploration with grounded references, multiple options analysis, and self-validation. Skip for simple lookups or single-source questions. </when_to_use_skill>

<core_concepts>

  • All Rosetta prep steps MUST be FULLY completed, load-context skill loaded and fully executed
  • Meta-prompting approach: prepare an optimized research prompt enforcing all rules below, then execute it as a separate subagent
  • MUST NOT update CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, and create any other documents EXCEPT those mentioned explicitly

</core_concepts>

Research rules:

  • Prepare a plan to systematically address user request
  • Make sure tasks start small but incrementally add value
  • Update tasks with the new information
  • Ask questions when new information or condition appears
  • Follow tree-of-thoughts pattern and analyze at least 3 options
  • Always create self-validation task at the end to re-review all conclusions
  • Create and keep updated after each task research-state.md in FEATURE TEMP folder
  • Save results in docs/<feature>-research.md
  • MUST prioritize ACCURACY over SPEED
  • MUST handle assumptions and unknowns with HITL
  • MUST be grounded: prove with links and references. Use reputable sources. Fall back to anecdotal references, but call this out EXPLICITLY!
  • MUST be cautious of LLM context: use grep, search, and similar techniques and tools
  • Ask user questions during research to resolve unknowns and validate direction
  • Spawn parallel subagents to go over individual ideas or areas
  • Use synthesis and comparison approach

Enforcement rules for the generated research prompt:

  1. MUST use todo tasks
  2. MUST use DeepWiki and Context7
  3. MUST create and update state md file after each task
  4. MUST output result file section by section as soon as each section becomes available
  5. MUST think about and align consequences and consequences of consequences to prevent oversight (example: doing X leads to Y, which affects Z, thus it should be done ABC way)
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. 5d ago First seen · 65 lines · 22 tokens per session scan A 4179fb8bbae3

Subscribe to this mod's changes

research is a skill published in the GitHub repository griddynamics/rosetta (342 stars, last pushed yesterday), licensed Apache-2.0. It adds 22 tokens to every session and 579 once invoked, about $0.0001 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.