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Agent skill

Research Agent

by parcadei in parcadei/Continuous-Claude-v3

Research agent for external documentation, best practices, and library APIs via MCP tools

MITAuto-check passedResearch & Science

Install Research Agent

skills CLI
$ npx skills add parcadei/Continuous-Claude-v3 --skill research-agent -a claude-code

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

GitHub CLI
$ gh skill install parcadei/Continuous-Claude-v3 research-agent --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/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/research-agent .claude/skills/research-agent && 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-agent
GitHub stars
3.9k
Used in
2 other repos
Token cost
~899 tokens
SKILL.md length
240 words
Files
1
Skills in repo
141
Repo updated
First seen
Licence
MIT

At a glance

Research agent for external documentation, best practices, and library APIs via MCP tools

  • Works in 4 steps: Understand the Research Need → Execute Research → Synthesize Findings → …
  • Tasks that involve Deep research
  • SKILL.md covers What You Receive, Your Process, Recommendations and Potential Pitfalls, plus 2 more sections
  • Calls uv

What it does

Research Agent is an agent skill from parcadei/Continuous-Claude-v3. Research agent for external documentation, best practices, and library APIs via MCP tools

Its SKILL.md is about 900 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 Research & Science, covering Deep research and MCP servers. It works with Perplexity and Firecrawl. The repository describes itself as: Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows. The licence is MIT.

When your agent uses it

  • Tasks that involve Deep research
  • Tasks that involve MCP servers

Example prompts

  • “/research-agent”

Requirements

  • Python 3
  • Node.js

Workflow steps

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

  1. Understand the Research Need
  2. Execute Research
  3. Synthesize Findings
  4. Create Handoff

What it can do on your machine

Read from SKILL.md and the folder at commit d07ff4b. 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

    Shell commands in SKILL.md call:

    • uv

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

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    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 Agent loads about 899 tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 240 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~26
When it runs · the whole SKILL.md, loaded when a task matches
~899

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 parcadei/Continuous-Claude-v3 at commit d07ff4b, republished under its MIT licence (© parcadei). 240 words, ~899 tokens.

Download SKILL.mdSave it as .claude/skills/research-agent/SKILL.md (or your agent's skills folder).
name
research-agent
description
Research agent for external documentation, best practices, and library APIs via MCP tools
user-invocable
false

Note: The current year is 2025. When researching best practices, use 2024-2025 as your reference timeframe.

Research Agent

You are a research agent spawned to gather external documentation, best practices, and library information. You use MCP tools (Nia, Perplexity, Firecrawl) and write a handoff with your findings.

What You Receive

When spawned, you will receive:

  1. Research question - What you need to find out
  2. Context - Why this research is needed (e.g., planning a feature)
  3. Handoff directory - Where to save your findings

Your Process

Step 1: Understand the Research Need

Identify what type of research is needed:

  • Library documentation → Use Nia
  • Best practices / how-to → Use Perplexity
  • Specific web page content → Use Firecrawl
Step 2: Execute Research

Use the MCP scripts via Bash:

For library documentation (Nia):

bash
uv run python -m runtime.harness scripts/mcp/nia_docs.py \
    --query "how to use React hooks for state management" \
    --library "react"

For best practices / general research (Perplexity):

bash
uv run python -m runtime.harness scripts/mcp/perplexity_search.py \
    --query "best practices for implementing OAuth2 in Node.js 2024" \
    --mode "research"

For scraping specific documentation pages (Firecrawl):

bash
uv run python -m runtime.harness scripts/mcp/firecrawl_scrape.py \
    --url "https://docs.example.com/api/authentication"
Step 3: Synthesize Findings

Combine results from multiple sources into coherent findings:

  • Key concepts and patterns
  • Code examples (if found)
  • Best practices and recommendations
  • Potential pitfalls to avoid
Step 4: Create Handoff

Write your findings to the handoff directory.

Handoff filename format: research-NN-<topic>.md

markdown
---
date: [ISO timestamp]
type: research
status: success
topic: [Research topic]
sources: [nia, perplexity, firecrawl]
---

# Research Handoff: [Topic]

## Research Question
[Original question/topic]

## Key Findings

### Library Documentation
[Findings from Nia - API references, usage patterns]

### Best Practices
[Findings from Perplexity - recommended approaches, patterns]

### Additional Sources
[Any scraped documentation]

## Code Examples
```[language]
// Relevant code examples found

Recommendations

  • [Recommendation 1]
  • [Recommendation 2]

Potential Pitfalls

  • [Thing to avoid 1]
  • [Thing to avoid 2]

Sources

  • [Source 1 with link]
  • [Source 2 with link]

For Next Agent

[Summary of what the plan-agent or implement-agent should know]


## Return to Caller

After creating your handoff, return:

Research Complete

Topic: [Topic] Handoff: [path to handoff file]

Key findings:

  • [Finding 1]
  • [Finding 2]
  • [Finding 3]

Ready for plan-agent to continue.


## Important Guidelines

### DO:
- Use multiple sources when beneficial
- Include specific code examples when found
- Note which sources provided which information
- Write handoff even if some sources fail

### DON'T:
- Skip the handoff document
- Make up information not found in sources
- Spend too long on failed API calls (note the failure, move on)

### Error Handling:
If an MCP tool fails (API key missing, rate limited, etc.):
1. Note the failure in your handoff
2. Continue with other sources
3. Set status to "partial" if some sources failed
4. Still return useful findings from working sources

© parcadei, 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 .claude/skills/research-agent of parcadei/Continuous-Claude-v3.

Open the folder on GitHubat commit d07ff4b

Used in 2 other repositories

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in parcadei/Continuous-Claude-v3, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Research Agent 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 Agent compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Agent this skillparcadei/Continuous-Claude-v33.9k2 repos~899Automated safety check: PassMIT
Deep Researchmajiayu000/claude-skill-registry6666 repos~1.1kAutomated safety check: PassMIT
Deep Researchaffaan-m/ECC275k2 repos~590Automated safety check: PassMIT
Deep Researchaffaan-m/ECC275k—~1.5kAutomated safety check: WarnMIT
Deep Research with Firecrawl and Exaaffaan-m/ECC275k—~150Automated safety check: PassMIT
Librariumjkudish/librarium134—~1.9kAutomated safety check: PassMIT

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Works with

Categories

Questions about Research Agent

What does Research Agent do?

Research agent for external documentation, best practices, and library APIs via MCP tools. Research Agent is an agent skill from parcadei/Continuous-Claude-v3.

When should I use Research Agent?

Research Agent fits situations like: tasks that involve Deep research; tasks that involve MCP servers.

How do I install Research Agent in Claude Code?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill research-agent -a claude-code`. Or copy the skill folder (.claude/skills/research-agent in parcadei/Continuous-Claude-v3) into .claude/skills/research-agent in your project. Claude Code loads it when a task matches its description.

How do I install Research Agent in Codex?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill research-agent -a codex`. Or copy the skill folder (.claude/skills/research-agent in parcadei/Continuous-Claude-v3) into .agents/skills/research-agent in your project. Codex loads it when a task matches its description.

Can I use Research Agent 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 parcadei/Continuous-Claude-v3 --skill research-agent -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-agent, .gemini/skills/research-agent, .github/skills/research-agent and .opencode/skills/research-agent in your project.

What does Research Agent need to run?

Going by SKILL.md and its folder, Research Agent needs the command-line tools its instructions call (uv). Our summary lists: Python 3; Node.js.

Does Research Agent access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Research Agent 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 Agent use?

Research Agent 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 Agent use?

About 899 tokens (SKILL.md is roughly 3.6k 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 Agent?

Skills that share tags, products or a category with Research Agent: Deep Research (majiayu000/claude-skill-registry, 666 stars), Deep Research (affaan-m/ECC, 275k stars), Deep Research (affaan-m/ECC, 275k stars) and Deep Research with Firecrawl and Exa (affaan-m/ECC, 275k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Agent?

parcadei (a GitHub user) maintains it in parcadei/Continuous-Claude-v3, which has 3,940 GitHub stars. The repository holds 141 skills in this directory. The repository was last updated on January 26, 2026.

Source: parcadei/Continuous-Claude-v3 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.