research

research is a skill for Claude Code, Codex from duongductrong/cursor-kit. It costs 25 tokens per session (1,358 once invoked), scanned A, original, MIT.

A method for researching and planning technical solutions with attention to scale, security, and long-term maintenance. It uses defined scope, evaluation criteria, and multiple sources.

In plain words
What is it for?
Use it to investigate architecture or implementation choices, compare best practices, check security and performance concerns, and produce a concise technical plan.
Why use it?
It helps prevent premature complexity and keeps technical decisions focused on the actual problem and available evidence.

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/duongductrong/cursor-kit/research
Any agent
npx skills add duongductrong/cursor-kit --skill research
Clone the repo
git clone --depth 1 https://github.com/duongductrong/cursor-kit

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/duongductrong/cursor-kit/research.svg)](https://agentmods.dev/skills/duongductrong/cursor-kit/research)
Your own site
<a href="https://agentmods.dev/skills/duongductrong/cursor-kit/research"><img src="https://agentmods.dev/badge/skills/duongductrong/cursor-kit/research.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,358 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 $0.00025 $0.01358
Opus 5 $0.00013 $0.00679
Sonnet 5 $0.00005 $0.00272
Haiku 4.5 $0.00003 $0.00136

Measured 5d ago against content hash 8d515c992a35, 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.

templates/skills/research/SKILL.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research

Research Methodology

Always honoring YAGNI, KISS, and DRY principles. Be honest, be brutal, straight to the point, and be concise.

Phase 1: Scope Definition

First, you will clearly define the research scope by:

  • Identifying key terms and concepts to investigate
  • Determining the recency requirements (how current must information be)
  • Establishing evaluation criteria for sources
  • Setting boundaries for the research depth

Phase 2: Systematic Information Gathering

You will employ a multi-source research strategy:

  1. Search Strategy:

    • Check if gemini bash command is available, if so, execute gemini -m gemini-2.5-flash -p "...your search prompt..." bash command (timeout: 10 minutes) and save the output to ./plans/<plan-name>/reports/YYMMDD-<your-research-topic>.md file (including all citations).
    • If gemini bash command is not available, fallback to WebSearch tool.
    • Run multiple gemini bash commands or WebSearch tools in parallel to search for relevant information.
    • Craft precise search queries with relevant keywords
    • Include terms like "best practices", "2024", "latest", "security", "performance"
    • Search for official documentation, GitHub repositories, and authoritative blogs
    • Prioritize results from recognized authorities (official docs, major tech companies, respected developers)
    • IMPORTANT: You are allowed to perform at most 5 researches (max 5 tool calls), user might request less than this amount, strictly respect it, think carefully based on the task before performing each related research topic.
  2. Deep Content Analysis:

    • When you found a potential Github repository URL, use docs-seeker skill to find read it.
    • Focus on official documentation, API references, and technical specifications
    • Analyze README files from popular GitHub repositories
    • Review changelog and release notes for version-specific information
  3. Video Content Research:

    • Prioritize content from official channels, recognized experts, and major conferences
    • Focus on practical demonstrations and real-world implementations

Read the full file on GitHub · 169 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. 5d ago First seen · 169 lines · 25 tokens per session scan A 8d515c992a35

Subscribe to this mod's changes

research is a skill published in the GitHub repository duongductrong/cursor-kit (22 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 1,358 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.

Related

Other skills, from other repositories

vindicate

Use when the user wants to write, add, fix, stabilize (flaky), refactor, run, or audit Playwright browser tests, draft requirements/stories from a recording (no tests), find test-coverage gaps, scaffold a Playwright project, or set up Playwright CI. Vindicate's guided workflow for grounded, conformant Playwright test…

OpenEvident/vindicate · 77 tokens

confluence-assistant

Central hub for Confluence operations - routes requests to specialized skills. ALWAYS use when user mentions confluence, wiki, or Atlassian wiki operations.

ulises-jeremias/agent-toolkit · 35 tokens

figma-create-design-system-rules

Generates custom design system rules for the user's codebase. Use when user says "create design system rules", "generate rules for my project", "set up design rules", "customize design system guidelines", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server…

ulises-jeremias/agent-toolkit · 71 tokens

megalinter-check

Collect MegaLinter lint errors for the current repository. Use when the user wants to know if the code passes linting, why the MegaLinter CI job fails, or before/after fixing lint errors. Two modes - watch a CI job (GitHub Actions, GitLab CI, Azure Pipelines, Bitbucket Pipelines) and parse its logs, or run MegaLinter…

ulises-jeremias/agent-toolkit · 96 tokens

assistant

Assistant — on any repo, scan README→docs→AGENTS→CONTRIBUTING→PR templates→task runners→devcontainer→CI→configs before code; cite sources; prefer AGENTS.md for agent behavior; portable across Cursor/Copilot/Claude; use agent-toolkit CLI when needed.

ulises-jeremias/agent-toolkit · 64 tokens

design-improvement

WHAT - Browser-grounded iterative design improvement. Consumes design-assessment findings, defines direction, prioritizes safe vs ambiguous changes, implements within existing design system, runs app, captures rendered evidence via browser, reviews and iterates. Reuses evidence model — no new scoring framework.

ulises-jeremias/agent-toolkit · 60 tokens