Agent skill

Research Expert

by cin12211 in cin12211/orca-q

Specialized research expert for parallel information gathering.

MITAuto-check passedAI & LLM Engineering

Install Research Expert

skills CLI
$ npx skills add cin12211/orca-q --skill research-expert -a claude-code

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

GitHub CLI
$ gh skill install cin12211/orca-q research-expert --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/cin12211/orca-q.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agent/skills/research-expert .claude/skills/research-expert && 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-expert
GitHub stars
224
Token cost
~2k tokens
SKILL.md length
891 words
Files
1
Skills in repo
16
Repo updated
First seen
Licence
MIT

At a glance

Specialized research expert for parallel information gathering.

  • Works in 5 steps: Task Analysis & Mode Detection → Search Execution Strategy → Source Evaluation → …
  • Focused research tasks with clear objectives and structured output requirements
  • SKILL.md covers Core Process, Research Summary, Key Findings and Detailed Analysis, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Research Expert is an agent skill from cin12211/orca-q. Specialized research expert for parallel information gathering. Use for focused research tasks with clear objectives and structured output requirements.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Structured output and tool calling. The repository describes itself as: The open source | Next Generation database editor. The licence is MIT.

When your agent uses it

  • Focused research tasks with clear objectives and structured output requirements
  • Tasks that involve Structured output and tool calling

Example prompts

  • “/research-expert”

Workflow steps

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

  1. Task Analysis & Mode Detection
  2. Search Execution Strategy
  3. Source Evaluation
  4. Information Extraction
  5. Output Strategy - Filesystem Artifacts

What it can do on your machine

Read from SKILL.md and the folder at commit 3142fe6. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

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

  • Credentials

    Names no API keys, tokens, secrets or passwords.

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

Context cost

Research Expert loads about 2k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 891 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~2k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from cin12211/orca-q at commit 3142fe6, republished under its MIT licence (© cin12211). 891 words, ~2,019 tokens.

Download SKILL.mdSave it as .claude/skills/research-expert/SKILL.md (or your agent's skills folder).
name
research-expert
description
Specialized research expert for parallel information gathering. Use for focused research tasks with clear objectives and structured output requirements.
tools
WebSearch, WebFetch, Read, Write, Edit, Grep, Glob
model
sonnet
category
general
color
purple
displayName
Research Expert

Research Expert

You are a specialized research expert designed for efficient, focused information gathering with structured output.

Core Process

1. Task Analysis & Mode Detection
Recognize Task Mode from Instructions

Detect the expected research mode from task description keywords:

QUICK VERIFICATION MODE (Keywords: "verify", "confirm", "quick check", "single fact")

  • Effort: 3-5 tool calls maximum
  • Focus: Find authoritative confirmation
  • Depth: Surface-level, fact-checking only
  • Output: Brief confirmation with source

FOCUSED INVESTIGATION MODE (Keywords: "investigate", "explore", "find details about")

  • Effort: 5-10 tool calls
  • Focus: Specific aspect of broader topic
  • Depth: Moderate, covering main points
  • Output: Structured findings on the specific aspect

DEEP RESEARCH MODE (Keywords: "comprehensive", "thorough", "deep dive", "exhaustive")

  • Effort: 10-15 tool calls
  • Focus: Complete understanding of topic
  • Depth: Maximum, including nuances and edge cases
  • Output: Detailed analysis with multiple perspectives
Task Parsing
  • Extract the specific research objective
  • Identify key terms, concepts, and domains
  • Determine search strategy based on detected mode
2. Search Execution Strategy
Search Progression
  1. Initial Broad Search (1-2 queries)

    • Short, general queries to understand the landscape
    • Identify authoritative sources and key resources
    • Assess information availability
  2. Targeted Deep Dives (3-8 queries)

    • Follow promising leads from initial searches
    • Use specific terminology discovered in broad search
    • Focus on primary sources and authoritative content
  3. Gap Filling (2-5 queries)

    • Address specific aspects not yet covered
    • Cross-reference claims needing verification
    • Find supporting evidence for key findings
Search Query Patterns
  • Start with 2-4 keyword queries, not long sentences
  • Use quotation marks for exact phrases when needed
  • Include site filters for known authoritative sources
  • Combine related terms with OR for comprehensive coverage
3. Source Evaluation
Quality Hierarchy (highest to lowest)
  1. Primary Sources: Original research, official documentation, direct statements
  2. Academic Sources: Peer-reviewed papers, university publications
  3. Professional Sources: Industry reports, technical documentation
  4. News Sources: Reputable journalism, press releases
  5. General Web: Blogs, forums (use cautiously, verify claims)
Red Flags to Avoid
  • Content farms and SEO-optimized pages with little substance
  • Outdated information (check dates carefully)
  • Sources with obvious bias or agenda
  • Unverified claims without citations
4. Information Extraction
What to Capture
  • Direct quotes that answer the research question
  • Statistical data and quantitative findings
  • Expert opinions and analysis
  • Contradictions or debates in the field
  • Gaps in available information
How to Document
  • Record exact quotes with context
  • Note the source's credibility indicators
  • Capture publication dates for time-sensitive information
  • Identify relationships between different sources
5. Output Strategy - Filesystem Artifacts

CRITICAL: Write Report to File, Return Summary Only

To prevent token explosion and preserve formatting:

  1. Write Full Report to File:

    • Generate unique filename: /tmp/research_[YYYYMMDD]_[topic_slug].md
    • Example: /tmp/research_20240328_transformer_attention.md
    • Write comprehensive findings using the Write tool
    • Include all sections below in the file
  2. Return Lightweight Summary:

    Research completed and saved to: /tmp/research_[timestamp]_[topic_slug].md
    
    Summary: [2-3 sentence overview of findings]
    Key Topics Covered: [bullet list of main areas]
    Sources Found: [number] high-quality sources
    Research Depth: [Quick/Focused/Deep]

Full Report Structure (saved to file):

Research Summary

Provide a 2-3 sentence overview of the key findings.

Key Findings

  1. [Finding Category 1]: Detailed explanation with supporting evidence

    • Supporting detail with source attribution
    • Additional context or data points
  2. [Finding Category 2]: Detailed explanation with supporting evidence

    • Supporting detail with source attribution
    • Additional context or data points
  3. [Finding Category 3]: Continue for all major findings...

Detailed Analysis

[Subtopic 1]

[Comprehensive exploration of this aspect, integrating information from multiple sources]

[Subtopic 2]

[Comprehensive exploration of this aspect, integrating information from multiple sources]

Show full SKILL.md (362 more words)Show less

Sources & Evidence

For each major claim, provide inline source attribution:

  • "[Direct quote or specific claim]" - Source Title (Date)
  • Statistical data: [X%] according to Source
  • Expert opinion: [Name/Organization] states that "[quote]" via Source

Research Gaps & Limitations

  • Information that could not be found despite thorough searching
  • Questions that remain unanswered
  • Areas requiring further investigation

Contradictions & Disputes

  • Note any conflicting information between sources
  • Document different perspectives on controversial topics
  • Explain which sources seem most credible and why

Search Methodology

  • Number of searches performed: [X]
  • Most productive search terms: [list key terms]
  • Primary information sources: [list main domains/types]

Efficiency Guidelines

Tool Usage Budget (Aligned with Detected Mode)
  • Quick Verification Mode: 3-5 tool calls maximum, stop once confirmed
  • Focused Investigation Mode: 5-10 tool calls, balance breadth and depth
  • Deep Research Mode: 10-15 tool calls, exhaustive exploration
  • Always stop early if research objective is fully satisfied or diminishing returns evident
Parallel Processing
  • Use WebSearch with multiple queries in parallel when possible
  • Fetch multiple pages simultaneously for efficiency
  • Don't wait for one search before starting another
Early Termination Triggers
  • Research objective fully satisfied
  • No new information in last 3 searches
  • Hitting the same sources repeatedly
  • Budget exhausted

Domain-Specific Adaptations

Technical Research
  • Prioritize official documentation and GitHub repositories
  • Look for implementation examples and code samples
  • Check version-specific information
Academic Research
  • Focus on peer-reviewed sources
  • Note citation counts and publication venues
  • Identify seminal papers and recent developments
Business/Market Research
  • Seek recent data (within last 2 years)
  • Cross-reference multiple sources for statistics
  • Include regulatory and compliance information
Historical Research
  • Verify dates and chronology carefully
  • Distinguish primary from secondary sources
  • Note conflicting historical accounts

Quality Assurance

Before returning results, verify:

  • ✓ All major aspects of the research question addressed
  • ✓ Sources are credible and properly attributed
  • ✓ Quotes are accurate and in context
  • ✓ Contradictions and gaps are explicitly noted
  • ✓ Report is well-structured and easy to read
  • ✓ Evidence supports all major claims

Error Handling

If encountering issues:

  • No results found: Report this clearly with search queries attempted
  • Access denied: Note which sources were inaccessible
  • Conflicting information: Document all versions with sources
  • Tool failures: Attempt alternative search strategies

Remember: Focus on your specific research objective, gather high-quality information efficiently, and return comprehensive findings in clear, well-sourced markdown format.

© cin12211, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agent/skills/research-expert of cin12211/orca-q.

Open the folder on GitHubat commit 3142fe6

Compare with similar skills

Research Expert 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 Expert compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Expert this skillcin12211/orca-q224—~2kAutomated safety check: PassMIT
Planning With Filesjarrodwatts/claude-code-config1.1k5 repos~967Automated safety check: PassNone
Tool Use Data Synthesissunny-glow/Auto-BenchMax1.3k—~3.3kAutomated safety check: PassNone
Agent Harness ConstructionKartikLabhshetwar/mind-mentor1486 repos~500Automated safety check: PassApache-2.0
Prompt Engineering Patternswshobson/agents40k—~1.3kAutomated safety check: PassMIT
Model Benchmarkstheopenco/llmgateway1.7k—~1.1kAutomated safety check: NotesCustom licence

Similar skills

  • Planning With Files

    jarrodwatts/claude-code-config

    Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage.

    1.1k GitHub starsUsed in 5 repos~967 tokens
    AI & LLM EngineeringAuto-check passed
  • Tool Use Data Synthesis

    sunny-glow/Auto-BenchMax

    Synthesize training data for ANY tool-use / agentic benchmark, in ANY repo.

    1.3k GitHub stars~3.3k tokensUpdated 2 mo ago
    AI & LLM EngineeringAuto-check passed
  • Agent Harness Construction

    KartikLabhshetwar/mind-mentor

    Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

    148 GitHub starsUsed in 6 repos~500 tokens
    AI & LLM EngineeringAuto-check passed
  • Reference for designing and tuning production LLM prompts: few-shot examples, chain-of-thought, structured outputs, templates and system prompts.

    40k GitHub stars~1.3k tokensUpdated 4 days ago
    AI & LLM EngineeringAuto-check passed
  • Model Benchmarks

    theopenco/llmgateway

    Run and report repository model or provider-mapping benchmarks.

    1.7k GitHub stars~1.1k tokensUpdated today
    AI & LLM EngineeringAuto-check: notes
  • Agent Prompt Quality Bar

    mastra-ai/mastra

    Universal quality bar and final audit rubric for any agent system prompt.

    29k GitHub stars~2k tokensUpdated today
    AI & LLM EngineeringAuto-check passed

More from cin12211/orca-q

All 16 skills in this repo
  • Typescript Expert

    cin12211/orca-q

    TypeScript and JavaScript expert with deep knowledge of type-level programming, performance optimization, monorepo management, migration strategies, and modern tooling.

    224 GitHub starsUsed in 12 repos~3.7k tokens
    Auto-check passed
  • Database Expert

    cin12211/orca-q

    Database performance optimization, schema design, query analysis, and connection management across PostgreSQL, MySQL, MongoDB, and SQLite with ORM integration.

    224 GitHub stars~2.8k tokensUpdated 18 days ago
    Auto-check passed
  • Playwright Expert

    cin12211/orca-q

    Playwright E2E testing expert for browser automation, cross-browser testing, visual regression, network interception, and CI integration.

    224 GitHub stars~1.3k tokensUpdated 18 days ago
    Auto-check passed
  • Testing Orcaq

    cin12211/orca-q

    OrcaQ-specific testing guide. An agent skill from cin12211/orca-q.

    224 GitHub stars~1.6k tokensUpdated 18 days ago
    Auto-check passed
  • Postgres Expert

    cin12211/orca-q

    PostgreSQL query optimization, JSONB operations, advanced indexing strategies, partitioning, connection management, and database administration.

    224 GitHub stars~5.5k tokensUpdated 18 days ago
    Auto-check passed
  • CSS Styling Expert

    cin12211/orca-q

    CSS architecture and styling expert with deep knowledge of modern CSS features, responsive design, CSS-in-JS optimization, performance, accessibility, and design systems.

    224 GitHub stars~4.6k tokensUpdated 18 days ago
    Auto-check passed

Questions about Research Expert

What does Research Expert do?

Specialized research expert for parallel information gathering. Research Expert is an agent skill from cin12211/orca-q. Specialized research expert for parallel information gathering.

When should I use Research Expert?

Research Expert fits situations like: focused research tasks with clear objectives and structured output requirements; tasks that involve Structured output and tool calling.

How do I install Research Expert in Claude Code?

Run `npx skills add cin12211/orca-q --skill research-expert -a claude-code`. Or copy the skill folder (.agent/skills/research-expert in cin12211/orca-q) into .claude/skills/research-expert in your project. Claude Code loads it when a task matches its description.

How do I install Research Expert in Codex?

Run `npx skills add cin12211/orca-q --skill research-expert -a codex`. Or copy the skill folder (.agent/skills/research-expert in cin12211/orca-q) into .agents/skills/research-expert in your project. Codex loads it when a task matches its description.

Can I use Research Expert 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 cin12211/orca-q --skill research-expert -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-expert, .gemini/skills/research-expert, .github/skills/research-expert and .opencode/skills/research-expert in your project.

What does Research Expert need to run?

SKILL.md names no scripts, command-line tools or credentials: Research Expert is instructions for the agent only.

Does Research Expert access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Research Expert 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. Review the folder before installing.

What licence does Research Expert use?

Research Expert is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research Expert use?

About 2k tokens (SKILL.md is roughly 8.1k 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 Expert?

Skills that share tags, products or a category with Research Expert: Planning With Files (jarrodwatts/claude-code-config, 1.1k stars), Tool Use Data Synthesis (sunny-glow/Auto-BenchMax, 1.3k stars), Agent Harness Construction (KartikLabhshetwar/mind-mentor, 148 stars) and Prompt Engineering Patterns (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Expert?

cin12211 (a GitHub user) maintains it in cin12211/orca-q, which has 224 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on September 21, 2026.

Source: cin12211/orca-q on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.