Skip to content
Development
Skill

/research-external

External research workflow for docs, web, APIs - NOT codebase exploration

From plugin
continuous-claude-v3
3.9k156 skills32 agents

Claude Code

$ npx -y skills add parcadei/Continuous-Claude-v3 --skill research-external --agent claude-code

SKILL.md

research-external.SKILL.md
name: research-external
description: External research workflow for docs, web, APIs - NOT codebase exploration
model: sonnet
allowed-tools: [Bash, Read, Write, Task]

External Research Workflow

Research external sources (documentation, web, APIs) for libraries, best practices, and general topics.

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

Invocation

/research-external <focus> [options]

Question Flow (No Arguments)

If the user types just `/research-external` with no or partial arguments, guide them through this question flow. Use AskUserQuestion for each phase.

Phase 1: Research Type

question: "What kind of information do you need?"
header: "Type"
options:
  - label: "How to use a library/package"
    description: "API docs, examples, patterns"
  - label: "Best practices for a task"
    description: "Recommended approaches, comparisons"
  - label: "General topic research"
    description: "Comprehensive multi-source search"
  - label: "Compare options/alternatives"
    description: "Which tool/library/approach is best"

**Mapping:**

  • "How to use library" → library focus
  • "Best practices" → best-practices focus
  • "General topic" → general focus
  • "Compare options" → best-practices with comparison framing

Phase 2: Specific Topic

question: "What specifically do you want to research?"
header: "Topic"
options: []  # Free text input

Examples of good answers:

  • "How to use Prisma ORM with TypeScript"
  • "Best practices for error handling in Python"
  • "React vs Vue vs Svelte for dashboards"

Phase 3: Library Details (if library focus)

If user selected library focus:

question: "Which package registry?"
header: "Registry"
options:
  - label: "npm (JavaScript/TypeScript)"
    description: "Node.js packages"
  - label: "PyPI (Python)"
    description: "Python packages"
  - label: "crates.io (Rust)"
    description: "Rust crates"
  - label: "Go modules"
    description: "Go packages"

Then ask for specific library name if not already provided.

Phase 4: Depth

question: "How thorough should the research be?"
header: "Depth"
options:
  - label: "Quick answer"
    description: "Just the essentials"
  - label: "Thorough research"
    description: "Multiple sources, examples, edge cases"

**Mapping:**

  • "Quick answer" → --depth shallow
  • "Thorough" → --depth thorough

Phase 5: Output

question: "What should I produce?"
header: "Output"
options:
  - label: "Summary in chat"
    description: "Tell me what you found"
  - label: "Research document"
    description: "Write to thoughts/shared/research/"
  - label: "Handoff for implementation"
    description: "Prepare context for coding"

**Mapping:**

  • "Research document" → --output doc
  • "Handoff" → --output handoff

Summary Before Execution

Based on your answers, I'll research:

**Focus:** library
**Topic:** "Prisma ORM connection pooling"
**Library:** prisma (npm)
**Depth:** thorough
**Output:** doc

Proceed? [Yes / Adjust settings]

Focus Modes (First Argument)

| Focus | Primary Tool | Purpose | |-------|--------------|---------| | `library` | nia-docs | API docs, usage patterns, code examples | | `best-practices` | perplexity-search | Recommended approaches, patterns, comparisons | | `general` | All MCP tools | Comprehensive multi-source research |

Options

| Option | Values | Description | |--------|--------|-------------| | `--topic` | `"string"` | **Required.** The topic/library/concept to research | | `--depth` | `shallow`, `thorough` | Search depth (default: shallow) | | `--output` | `handoff`, `doc` | Output format (default: doc) | | `--library` | `"name"` | For `library` focus: specific package name | | `--registry` | `npm`, `py_pi`, `crates`, `go_modules` | For `library` focus: package registry |

Workflow

Step 1: Parse Arguments

Extract from user input:

FOCUS=$1           # library | best-practices | general
TOPIC="..."        # from --topic
DEPTH="shallow"    # from --depth (default: shallow)
OUTPUT="doc"       # from --output (default: doc)
LIBRARY="..."      # from --library (optional)
REGISTRY="npm"     # from --registry (default: npm)

Step 2: Execute Research by Focus

Focus: `library`

Primary tool: **nia-docs** - Find API documentation, usage patterns, code examples.

# Semantic search in package
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/nia_docs.py \
  --package "$LIBRARY" \
  --registry "$REGISTRY" \
  --query "$TOPIC" \
  --limit 10)

# If thorough depth, also grep for specific patterns
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/nia_docs.py \
  --package "$LIBRARY" \
  --grep "$TOPIC")

# Supplement with official docs if URL known
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/firecrawl_scrape.py \
  --url "https://docs.example.com/api/$TOPIC" \
  --format markdown)

**Thorough depth additions:**

  • Multiple semantic queries with variations
  • Grep for specific function/class names
  • Scrape official documentation pages

Focus: `best-practices`

Primary tool: **perplexity-search** - Find recommended approaches, patterns, anti-patterns.

# AI-synthesized research (sonar-pro)
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --research "$TOPIC best practices 2024 2025")

# If comparing alternatives
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --reason "$TOPIC vs alternatives - which to choose?")

**Thorough depth additions:**

# Chain-of-thought for complex decisions
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --reason "$TOPIC tradeoffs and considerations 2025")

# Deep comprehensive research
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --deep "$TOPIC comprehensive guide 2025")

# Recent devel
Read more
@parcadei
Ships withcontinuous-claude-v3

A persistent, learning, multi-agent development environment built on Claude Code Continuous Claude transforms Claude Code into a continuously learning system that maintains context across sessions, orchestrates specialized agents, and eliminates wasting

3.9k156 skills32 agents
Get the whole plugin

Stars on GitHub

Momentum

stars in total
3.9k
Star history of parcadei/Continuous-Claude-v3 on GitHub, a chart by star-history.com

Other skills on continuous-claude-v3.

More skills from other plugins.

brainstorming
Auto-invoked

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…

@obra@obraInstall Skill
ask-matt

ask-matt

Ask which skill or flow fits your situation. A router over the skills in this repo.

skills2w309k
@mattpocock@mattpocockInstall Skill
accessibility
Auto-invoked

accessibility

Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android — semantic ARIA roles and labels,…

ecc2w293k
@affaan-m@affaan-mInstall Skill
compiler-commit

compiler-commit

Use when you want to verify compiler changes and commit with the correct convention. Runs tests, lint, and format, then commits…

react5d252k
@facebook@facebookInstall Skill

Questions about research-external.

Which coding agents can use research-external?
research-external installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.