research-online

SKILL.md

Research Online

Research a programming topic from multiple angles using parallel sub-agents, with critical evaluation of source credibility.

Usage

/research-online <library> <what you want to do>
/research-online "<error message>" <library>
/research-online how to implement auth in react-navigation v7
/research-online best practices for state management in React
/research-online Redux vs Zustand for large app

Workflow

Step 1: Parse Input

Extract from the user's query:

  • Library/framework name (e.g., "react-navigation", "prisma", "next.js")
  • Error message (if any, usually in quotes)
  • Version (if mentioned, e.g., "v7", "version 14")
  • Goal/intent (what they're trying to build or achieve)
  • Problem description (if debugging: what's broken or unexpected)
  • Comparison targets (if comparing: "X vs Y", "X or Y")

Step 2: Check Internal Documentation First

Before external research, use the Grep tool to search for relevant keywords in the project's docs:

Grep pattern: "<relevant_keywords>" path: "docs/" and "*.md"

If found, read and include internal patterns/conventions in the synthesis. Internal docs often contain project-specific decisions that external research won't cover.

Step 3: Determine Which Agents to Spawn

Agent Spawn When Purpose
Docs Library/framework mentioned Context7 documentation lookup
GitHub Library with known repository Search issues AND discussions
General Always Broad "how to" web search
Specific Error message provided Search for exact error text
StackOverflow Common problem/implementation pattern Community Q&A solutions
Changelog Version mentioned OR "stopped working" / "after upgrade" Breaking changes, migration guides
Best Practices Feature implementation (no error message) Architecture patterns, recommended approaches
Comparison Query contains "vs", "or", "compare", "which", "best library" Compare options, pros/cons

Step 4: Spawn Agents in Parallel

Use the Task tool to spawn ALL relevant agents in a single message (parallel execution). Each agent uses subagent_type: general-purpose.

Every agent must capture metadata for each source: URL, date, and source type (official docs / GitHub issue / blog / SO answer / forum).

Agent Tool Search Strategy
Docs Context7 resolve-library-id then query-docs
GitHub WebSearch site:github.com {lib} "{terms}", then WebFetch top 2-3
General WebSearch how to {goal} {lib}
Specific WebSearch "{exact_error_message}" {lib}
StackOverflow WebSearch site:stackoverflow.com {lib} {keywords}, then WebFetch top answers
Changelog WebSearch {lib} {version} changelog breaking changes migration
Best Practices WebSearch {lib} best practices {goal} + {lib} recommended architecture {goal}
Comparison WebSearch {option_A} vs {option_B} {context}

For full agent prompt templates with detailed instructions, see references/agent-prompts.md.

Step 5: Collect Results

Wait for all agents to complete and gather their findings with metadata.

Step 6: Critical Evaluation

Before synthesizing, evaluate each source:

Recency:

Age Score Notes
< 6 months High Likely current
6-18 months Medium Check for updates
18+ months Low May be outdated
> 3 years Very Low Likely outdated, verify

Adjust for library velocity: fast-moving libraries (React, Next.js) decay faster than stable ones (Express, lodash).

Authority:

Source Type Score
Official docs, changelogs, core team posts High
GitHub issues (maintainer response) High
GitHub issues (community), recent blogs (known author) Medium
SO answers (accepted, high votes), comparison articles Medium
SO answers (low votes), old blogs, old comparisons Low
Random forums Very Low

Relevance: Exact error/goal match = High. Same library, similar task = Medium. Related concept = Low.

When sources conflict: Prefer more recent, then higher authority. Note conflicts in synthesis. If official docs conflict with recent issues, the issue may reveal a bug or undocumented behavior.

Step 7: Present Results

Structure the output with these sections (include only those relevant to the query):

  1. Documentation — Context7 findings with authority rating
  2. GitHub Issues & Discussions — table with date, type, authority, relevance
  3. General Solutions — table with source, date, authority
  4. Best Practices — (feature queries only) recommended patterns
  5. Comparison — (comparison queries only) pros/cons/best-for per option
  6. Specific Error Matches — (error queries only) causes and fixes
  7. Stack Overflow — question table with date, votes, accepted status
  8. Version/Changelog — (version queries only) breaking changes
  9. Source Evaluation Summary — most credible, potentially outdated, conflicts found
  10. Synthesis — goal, key findings weighted by credibility, recommended approach, confidence level

For the full output format template with markdown tables, see references/output-format.md.

Examples

Example 1: Feature Implementation

/research-online how to implement authentication in Next.js 14

Spawns: Docs, GitHub, General, Best Practices, StackOverflow

Example 2: Comparison Query

/research-online Redux vs Zustand for large React app

Spawns: Docs (both), General, Comparison, StackOverflow

Example 3: Specific Error

/research-online "Cannot read property 'navigate' of undefined" react-navigation

Spawns: Docs, GitHub, General, Specific, StackOverflow

Example 4: Version-Specific

/research-online auth navigation not working in react-navigation v7

Spawns: Docs, GitHub, General, Changelog, StackOverflow

Example 5: Best Practices

/research-online best practices for folder structure in Express API

Spawns: Docs, General, Best Practices, StackOverflow

Troubleshooting

Agent fails or times out

Solution: Continue with remaining agents. Note the gap in the synthesis and which source types are missing. The research is still useful with partial results.

No results found for a query

Solution: Widen search terms — try without the library name, use alternative terminology, or search for the underlying concept rather than the specific implementation.

All sources are outdated

Solution: Flag explicitly in the synthesis. Note the dates and recommend the user verify against current documentation. Prefer official docs over old blog posts.

Sources conflict with each other

Solution: Weight by recency and authority. Note the conflict clearly in the Source Evaluation Summary with a resolution explaining which source to trust and why.

Notes

  • All agents run in parallel for speed
  • Each agent should complete in under 60 seconds
  • Always capture source metadata for critical evaluation
  • Weight findings by credibility in synthesis — a recent GitHub issue from a maintainer outweighs a 5-year-old blog post
  • For comparisons, be especially careful about recency — library landscapes change quickly
Weekly Installs
9
First Seen
Feb 28, 2026
Installed on
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