using-context7-for-docs
Use when researching library documentation with Context7 MCP tools for official patterns and best practices
What this skill does
# Using Context7 for Documentation
Use this skill when researching library documentation with Context7 MCP tools for official patterns and best practices.
## Core Principles
- Always resolve library ID first (unless user provides exact ID)
- Use topic parameter to focus documentation
- Paginate when initial results insufficient
- Prioritize high benchmark scores and reputation
## Workflow
### 1. Resolve Library ID
**Use `resolve-library-id`** before fetching docs:
```python
# Search for library
result = resolve_library_id(libraryName="react")
# Returns matches with:
# - Context7 ID (e.g., "/facebook/react")
# - Description
# - Code snippet count
# - Source reputation (High/Medium/Low)
# - Benchmark score (0-100, higher is better)
```
**Selection criteria:**
1. Exact name match preferred
2. Higher documentation coverage (more snippets)
3. High/Medium reputation sources
4. Higher benchmark scores (aim for 80+)
**Example output:**
```markdown
Selected: /facebook/react
Reason: Official React repository, High reputation, 850 snippets, Benchmark: 95
```
### 2. Fetch Documentation
**Use `get-library-docs`** with resolved ID:
```python
# Get focused documentation
docs = get_library_docs(
context7CompatibleLibraryID="/facebook/react",
topic="hooks",
page=1
)
```
**Topic parameter:**
- Focuses results on specific area
- Examples: "hooks", "routing", "authentication", "testing"
- More specific = better results
**Pagination:**
- Default `page=1` returns first batch
- If insufficient, try `page=2`, `page=3`, etc.
- Maximum `page=10`
### 3. Version-Specific Docs
**Include version in ID** when needed:
```python
# Specific version
docs = get_library_docs(
context7CompatibleLibraryID="/vercel/next.js/v14.3.0-canary.87",
topic="server components"
)
```
Use when:
- Project uses specific version
- Breaking changes between versions
- Need migration guidance
## Reporting Format
Structure findings as:
```markdown
## Library Documentation Findings
### Library: React 18
**Context7 ID:** /facebook/react
**Benchmark Score:** 95
### Relevant APIs
**useEffect Hook** (Official pattern)
```javascript
// Recommended: Cleanup pattern
useEffect(() => {
const subscription = api.subscribe()
return () => subscription.unsubscribe()
}, [dependencies])
```
Source: React docs, hooks section
### Best Practices
1. **Dependency Arrays**
- Always specify dependencies
- Use exhaustive-deps ESLint rule
- Avoid functions in dependencies
2. **Performance**
- Prefer useMemo for expensive calculations
- useCallback for function props
- React.memo for component memoization
### Migration Notes
- React 18 introduces concurrent features
- Automatic batching now default
- Upgrade guide: /facebook/react/v18/migration
```
## Common Libraries
**Frontend:**
- React: `/facebook/react`
- Next.js: `/vercel/next.js`
- Vue: `/vuejs/vue`
- Svelte: `/sveltejs/svelte`
**Backend:**
- Express: `/expressjs/express`
- FastAPI: `/tiangolo/fastapi`
- Django: `/django/django`
**Tools:**
- TypeScript: `/microsoft/typescript`
- Vite: `/vitejs/vite`
- Jest: `/jestjs/jest`
## Anti-Patterns
❌ **Don't:** Skip resolve-library-id step
✅ **Do:** Always resolve first (unless user provides exact ID)
❌ **Don't:** Use vague topics like "general"
✅ **Do:** Use specific topics: "authentication", "state management"
❌ **Don't:** Accept low benchmark scores (<50) without checking alternatives
✅ **Do:** Prefer high-quality sources (benchmark 80+)
❌ **Don't:** Cite docs without library version
✅ **Do:** Include version in findings
## Example Session
```python
# 1. Resolve library
result = resolve_library_id(libraryName="fastapi")
# → Selected: /tiangolo/fastapi (Benchmark: 92, High reputation)
# 2. Get auth documentation
docs = get_library_docs(
context7CompatibleLibraryID="/tiangolo/fastapi",
topic="authentication",
page=1
)
# → Got OAuth2, JWT patterns, security best practices
# 3. Need more detail on dependencies
docs2 = get_library_docs(
context7CompatibleLibraryID="/tiangolo/fastapi",
topic="dependency injection",
page=1
)
# → Got Depends() patterns, testing with overrides
# 4. Check pagination if needed
if insufficient:
docs3 = get_library_docs(
context7CompatibleLibraryID="/tiangolo/fastapi",
topic="authentication",
page=2 # Next page
)
```
## Quality Indicators
**High-quality results have:**
- ✅ Benchmark score 80+
- ✅ High/Medium source reputation
- ✅ Recent documentation (check dates)
- ✅ Official repositories
- ✅ Code examples with explanation
**Consider alternatives if:**
- ❌ Benchmark score <50
- ❌ Low reputation source
- ❌ Very few code snippets (<10)
- ❌ Unofficial/outdated sources
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.