Agent skill

Research

by jwynia in jwynia/agent-skills

Diagnose research quality and guide systematic query expansion.

MITAuto-check passedProductivity & Automation

Install Research

skills CLI
$ npx skills add jwynia/agent-skills --skill research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jwynia/agent-skills research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jwynia/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/general/research/methodology/research .claude/skills/research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
research
GitHub stars
169
Token cost
~3.9k tokens
SKILL.md length
1,341 words
Files
2 (incl. scripts)
Skills in repo
111
Repo updated
First seen
Licence
MIT

At a glance

Diagnose research quality and guide systematic query expansion.

  • Works in 5 steps: Analysis → Vocabulary Discovery → Foundational Search → …
  • Starting research on any topic
  • SKILL.md covers Setup, Quick Reference, Phase 0: Analysis and Phase 1: Vocabulary Discovery, plus 3 more sections
  • Runs TypeScript scripts from its folder; calls deno; needs TAVILY_API_KEY

What it does

Research is an agent skill from jwynia/agent-skills. Diagnose research quality and guide systematic query expansion. Use when starting research on any topic, when stuck in research, or when unsure if research is complete.

Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/tavily-cli.ts`).

It sits in Productivity & Automation, covering Web search. It works with Tavily. The licence is MIT.

When your agent uses it

  • Starting research on any topic
  • Stuck in research
  • Unsure if research is complete

Example prompts

  • “/research”

Requirements

  • Node.js
  • A credential in TAVILY_API_KEY

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Analysis
  2. Vocabulary Discovery
  3. Foundational Search
  4. Counter-Perspective Search
  5. Synthesis

What it can do on your machine

Read from SKILL.md and the folder at commit e02ec7e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (TypeScript), which the agent can run.

    Shell commands in SKILL.md call:

    • deno

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • deno.land
    • tavily.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • TAVILY_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Research loads about 3.9k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 1,341 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jwynia/agent-skills at commit e02ec7e, republished under its MIT licence (© jwynia). 1,341 words, ~3,905 tokens.

Download SKILL.mdSave it as .claude/skills/research/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
research
description
Diagnose research quality and guide systematic query expansion. Use when starting research on any topic, when stuck in research, or when unsure if research is complete.
license
MIT
metadata.author
jwynia
metadata.version
2.0
metadata.domain
research
metadata.cluster
methodology
metadata.type
diagnostic
metadata.mode
assistive

Research Skill

Tool-assisted research with Tavily integration. Transforms basic questions into comprehensive search strategies using AI-optimized web search.

Setup

This skill includes a bundled Tavily CLI script at scripts/tavily-cli.ts.

Requirements
  1. Deno - Install from https://deno.land
  2. Tavily API Key - Get one at https://tavily.com (free tier available)
Configuration

Set your API key:

bash
export TAVILY_API_KEY="your-key-here"

Create an alias for convenience (add to your shell profile):

bash
# Adjust path to where this skill is installed
alias tavily='deno run --allow-net --allow-env /path/to/skills/research/scripts/tavily-cli.ts'

Or run directly:

bash
deno run --allow-net --allow-env ./scripts/tavily-cli.ts "your query"

Commands below use tavily assuming the alias is configured.


Quick Reference

Common Commands
bash
# Basic search
tavily "your query"

# With AI answer summary
tavily "your query" --answer

# Deep search with more results
tavily "your query" --depth advanced --results 10 --answer

# News/recent content
tavily "your query" --topic news --time week

# Exclude familiar sources to find new perspectives
tavily "your query" --exclude wikipedia.org,reddit.com
Phase Summary
PhaseTypePurpose
0ManualAnalyze topic, set scope
1TavilyDiscover expert terminology
2TavilyFoundational search
3TavilyCounter-perspectives
4ManualSynthesize findings
Scope → Tavily Depth
Decision StakesTavily Settings
Low, reversible--depth basic --results 3
Moderate--depth basic --results 5 --answer
High, irreversible--depth advanced --results 10 --answer

Phase 0: Analysis

Goal: Structure topic before searching. Prevents unfocused searches and scope mismatch.

Scope Calibration

Before searching, assess stakes:

Decision TypeConfidence NeededResearch Depth
Reversible, low-stakes60-70%Quick scan (minutes)
Reversible, moderate75-85%Working knowledge
Irreversible, moderate85-90%Solid grounding
Irreversible, high90-95%Deep expertise
Analysis Template
markdown
# Research Analysis: [Topic]

## Core Concepts
- **Primary terms:** [Key terms requiring definition]
- **Terminology variants:** [Synonyms, jargon, historical terms]
- **Ambiguous terms:** [Terms with multiple meanings]

## Stakeholders
- **Primary actors:** [Who is directly involved?]
- **Affected groups:** [Who bears consequences?]
- **Opposing interests:** [Who benefits from different outcomes?]

## Temporal Scope
- **Historical origins:** [When did this begin?]
- **Key transitions:** [What changed and when?]
- **Current state:** [What's happening now?]

## Domains
- **Primary field:** [Main discipline]
- **Adjacent fields:** [Related disciplines]

## Controversies
- **Active debates:** [What's contested?]
- **Competing frameworks:** [Different ways of understanding]
Phase 0 Checklist
  • Identified primary terms
  • Listed potential stakeholders
  • Assessed decision stakes
  • Determined appropriate research depth

Phase 1: Vocabulary Discovery

Goal: Discover expert terminology to unlock deeper search results.

Why Vocabulary Matters
  • Outsider terms → introductory material
  • Expert terms → research, nuanced analysis
  • Cross-domain terms → bridge bodies of work
Tavily Commands for Vocabulary Discovery
Discovery NeedCommand
Expert terminologytavily "[topic] terminology experts" --answer
Academic termstavily "[topic] academic research terminology" --answer
Cross-domain synonymstavily "[topic] also known as called" --answer
Historical termstavily "[topic] history original term" --answer
Vocabulary Discovery Process
  1. Run initial terminology search:

    bash
    tavily "[topic] terminology" --answer --results 5
  2. From results, note:

    • Expert terms (technical vocabulary)
    • Outsider terms (popular/introductory language)
    • Cross-domain equivalents
  3. Update vocabulary map (template below)

  4. Re-run searches with expert terms:

    bash
    tavily "[expert-term]" --answer
  5. Compare result quality - expert terms should surface deeper content

Vocabulary Map Template
markdown
## Core Terms
| Term | Domain | Depth Level |
|------|--------|-------------|
| [expert term] | [field] | Expert |
| [outsider term] | General | Introductory |

## Cross-Domain Synonyms
| Concept | Terms by Domain |
|---------|-----------------|
| [concept] | Field A: [term], Field B: [term] |

## Depth Indicators
| Level | Terms | What They Surface |
|-------|-------|-------------------|
| Introductory | [terms] | Overviews, explainers |
| Expert | [terms] | Research, nuanced analysis |
Phase 1 Checklist
  • Ran terminology discovery search
  • Identified expert vs. outsider terms
  • Mapped cross-domain synonyms
  • Created vocabulary map

Goal: Build foundational understanding with authoritative sources.

Question Pattern → Tavily Command
Question PatternStrategyCommand
"What is X?"Consensus from authoritiestavily "[expert-term] definition" --answer --depth advanced
"Should I X?"Pros/cons, alternativestavily "[expert-term] pros cons comparison" --answer
"Is X true?"Evidence, counter-evidencetavily "[claim] evidence research" --answer --depth advanced
"How do I X?"Step-by-step, pitfallstavily "[expert-term] guide tutorial" --answer
Historical contextOrigins and evolutiontavily "[topic] history origins development" --answer
Source Type Selection
Source TypeBest ForTavily Approach
Academic/ResearchMechanism, causation--depth advanced --results 10
Practitioner contentHow things work, edge cases--topic general --answer
News/CurrentRecent developments--topic news --time week
Official docsTechnical specs, policy--include [official-domain]
Foundational Search Process
  1. Start with expert terminology from Phase 1

  2. Run foundational queries:

    bash
    # Definition/overview
    tavily "[expert-term] comprehensive overview" --answer --depth advanced
    
    # Key perspectives
    tavily "[expert-term] major approaches" --answer --results 7
  3. For each major perspective found, get 2-3 authoritative sources:

    bash
    tavily "[perspective-name] [expert-term]" --answer --results 5
  4. Track sources in research notes

Phase 2 Checklist
  • Used expert terminology from Phase 1
  • Searched for foundational overview
  • Identified 2-3 major perspectives
  • Found authoritative sources per perspective
  • Tracked sources

Goal: Explicitly find opposing viewpoints to avoid confirmation bias.

Why Counter-Perspectives Matter

Single-perspective research:

  • All sources support one viewpoint
  • Missing counterarguments
  • Echo chamber risk
Tavily Commands for Counter-Perspectives
NeedCommand
General criticismtavily "[topic] criticism problems" --answer
Opposing viewpointtavily "[topic] skeptics critique" --answer
Alternative approachestavily "[topic] alternatives instead of" --answer
Failure casestavily "[topic] failures when wrong" --answer
Avoid echo chambertavily "[topic] debate" --exclude [familiar-sources]
Counter-Perspective Process
  1. Identify your current understanding/lean

  2. Search for strongest counterargument:

    bash
    tavily "[topic] strongest argument against" --answer --depth advanced
  3. Exclude sources you've already seen:

    bash
    tavily "[topic]" --exclude [domains-already-searched]
  4. Search for failure modes:

    bash
    tavily "[topic] when fails problems limitations" --answer
  5. Document opposing perspectives in research notes

Phase 3 Checklist
  • Identified current understanding/position
  • Searched for strongest counterargument
  • Used --exclude to find new sources
  • Searched for limitations/failure cases
  • Documented opposing perspectives

Phase 4: Synthesis

Goal: Synthesize findings with explicit confidence markers.

Completion Criteria
Minimum Viable (Quick Decisions)
  • Can define core concepts in own words
  • Know 2-3 major perspectives
  • Found authoritative source per perspective
  • Identified known unknowns
Working Knowledge (Most Decisions)
  • Can explain historical context
  • Understand stakeholder positions
  • Encountered counterarguments
  • Checked multiple domains
Deep Expertise (High-Stakes)
  • Traced claims to primary sources
  • Can evaluate competing evidence
  • Understand knowledge limitations
Diminishing Returns Signals

Stop when:

  • New sources cite same foundational works (circular)
  • New searches return familiar content (repetitive)
  • Each hour adds less than previous (marginal)
  • Can make decision or take action (sufficient)
Confidence Markers
LevelPhrases to Use
Established"X is...", "X works by..."
Strong evidence"Evidence strongly suggests..."
Moderate evidence"Most sources report..."
Limited evidence"One study found..."
Unknown"No reliable information found..."
Synthesis Template
markdown
## Summary
[Direct answer to question]

## Confidence Level
[High/Medium/Low] - [Justification]

## Key Findings
1. [Finding with source type]

## Perspectives
| Perspective | Key Argument | Source Quality |
|-------------|--------------|----------------|
| [view] | [argument] | [assessment] |

## Counter-Evidence
- [What argues against the main conclusion]

## Caveats
- [What wasn't consulted]
- [What assumptions were made]

## For Deeper Investigation
[What would increase confidence]
Phase 4 Checklist
  • Met completion criteria for stakes level
  • Checked diminishing returns signals
  • Applied confidence markers
  • Completed synthesis template
  • Stored findings for future reference

Show full SKILL.md (558 more words)Show less

Tavily Command Reference

Basic Usage
bash
tavily "search query" [options]
Options
OptionDescriptionValues
--answerInclude AI-generated answer summaryflag
--depthSearch depthbasic (default), advanced
--resultsNumber of results1-20 (default: 5)
--topicTopic categorygeneral (default), news, finance
--timeTime filterday, week, month, year
--includeOnly include domainscomma-separated
--excludeExclude domainscomma-separated
--rawInclude raw page contentflag
--jsonOutput as JSONflag
Scenario → Command Mapping
Research ScenarioCommand
Quick overviewtavily "query" --answer
Deep divetavily "query" --depth advanced --results 10 --answer
Recent newstavily "query" --topic news --time week
Academic focustavily "query" --depth advanced --include scholar.google.com,arxiv.org
Avoid Wikipediatavily "query" --exclude wikipedia.org
Fresh perspectivestavily "query" --exclude [already-seen-domains]
Financial datatavily "query" --topic finance --answer
Raw content for analysistavily "query" --raw --json

Diagnostic States

Use these to identify where research is stuck and which phase to revisit.

StateSymptomPhase to Revisit
R0: No AnalysisSearching without structuring topicPhase 0
R1: No VocabularyUsing outsider terms, finding only surface contentPhase 1
R2: Single-PerspectiveAll sources support one viewPhase 3
R3: Domain BlindnessSearching only in familiar fieldPhase 1 (cross-domain terms)
R4: Recency BiasOnly recent sourcesPhase 2 (historical queries)
R5: Breadth Without DepthMany tabs, no synthesisPhase 4
R6: Completion UncertaintyUnsure when to stopPhase 4 (completion criteria)
R7: CompleteCan explain, identify uncertainties, actDone
Quick Diagnostic
  1. Can you explain the topic in expert terminology? → If no, Phase 1
  2. Have you found opposing viewpoints? → If no, Phase 3
  3. Can you state your confidence level with justification? → If no, Phase 4
  4. Is your research depth proportional to stakes? → If no, Phase 0

Anti-Patterns

PatternSymptomFix
Confirmation TrapSearching to confirm, not learnPhase 3: Search for strongest counterargument
Authority FallacyAccepting claims by source prestigeEvaluate evidence, not source
Recency TrapOnly recent sourcesPhase 2: Historical context queries
Breadth Trap50 tabs, none readPhase 4: 3-source rule, synthesize before continuing
Single-SourceOne source as final answerRequire 3 independent sources
Jargon Blind SpotMissing other fields' terminologyPhase 1: Cross-domain vocabulary
Infinite Rabbit HoleLost original purposePhase 0: Return to scope/stakes
Echo ChamberSame sources repeatedlyPhase 3: Use --exclude flag

Output Persistence

Output Discovery

Before doing any other work:

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. If not found or no entry for this skill, ask the user first:
    • "Where should I save output from this research session?"
    • Suggest: explorations/research/ or a sensible location for this project
  4. Store the user's preference
What to Store
LayerContents
Vocabulary MapTerms, domains, depth levels
SourcesURLs, relevance scores, quality notes
SynthesisSummary, confidence, findings, caveats
Query LogTavily commands that worked/failed
GapsWhat remains unknown
File Naming

Pattern: {topic}-research-{date}.md Example: competency-frameworks-research-2025-01-15.md


Integration Points

SkillConnection
doppelgangerResearch informs decisions; apply /truth-check to findings
context-networksStore research findings in appropriate network node
boundary-critiqueApply to advice and recommendations encountered

Health Check Questions

During research, ask:

  1. Am I searching to learn or to confirm?
  2. What's the strongest argument against my current view?
  3. Have I looked outside my familiar domains?
  4. Am I using expert or outsider vocabulary?
  5. Is my depth proportional to the stakes?
  6. Have I stored what I've learned for future use?

Source Framework

Derived from: references/research-framework.md

© jwynia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in skills/general/research/methodology/research of jwynia/agent-skills.

  • SKILL.md
  • scripts/tavily-cli.ts

Open the folder on GitHubat commit e02ec7e

Compare with similar skills

Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research this skilljwynia/agent-skills169—~3.9kAutomated safety check: PassMIT
Ultimate Searchckckck/UltimateSearchSkill289—~944Automated safety check: NotesMIT
Web SearchEXboys/skilllite1702 repos~1kAutomated safety check: PassMIT
Mysearchskernelx/MySearch-Proxy159—~3kAutomated safety check: NotesNone
Tavilyopenclaw/openclaw392k2 repos~1.2kAutomated safety check: PassMIT
Web Search Plus Plugin V2robbyczgw-cla/web-search-plus-plugin101—~1.9kAutomated safety check: NotesMIT

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Works with

Questions about Research

What does Research do?

Diagnose research quality and guide systematic query expansion. Research is an agent skill from jwynia/agent-skills. Diagnose research quality and guide systematic query expansion.

When should I use Research?

Research fits situations like: starting research on any topic; stuck in research; unsure if research is complete.

How do I install Research in Claude Code?

Run `npx skills add jwynia/agent-skills --skill research -a claude-code`. Or copy the skill folder (skills/general/research/methodology/research in jwynia/agent-skills) into .claude/skills/research in your project. Claude Code loads it when a task matches its description.

How do I install Research in Codex?

Run `npx skills add jwynia/agent-skills --skill research -a codex`. Or copy the skill folder (skills/general/research/methodology/research in jwynia/agent-skills) into .agents/skills/research in your project. Codex loads it when a task matches its description.

Can I use Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jwynia/agent-skills --skill research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research, .gemini/skills/research, .github/skills/research and .opencode/skills/research in your project.

What does Research need to run?

Going by SKILL.md and its folder, Research needs TypeScript for the scripts in its folder, the command-line tools its instructions call (deno) and credentials named TAVILY_API_KEY. Our summary lists: Node.js; A credential in TAVILY_API_KEY.

Does Research access the network?

SKILL.md names 2 domains. As links in the text: deno.land and tavily.com. This is read from the text; nothing was executed.

Is Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Research use?

Research is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research use?

About 3.9k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Research?

Skills that share tags, products or a category with Research: Ultimate Search (ckckck/UltimateSearchSkill, 289 stars), Web Search (EXboys/skilllite, 170 stars), Mysearch (skernelx/MySearch-Proxy, 159 stars) and Tavily (openclaw/openclaw, 392k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research?

jwynia (a GitHub user) maintains it in jwynia/agent-skills, which has 169 GitHub stars. The repository holds 111 skills in this directory. The repository was last updated on February 24, 2026.

Source: jwynia/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.