What is research-gate?

Research Gate is a specialized Claude skill designed to optimize research workflows by enforcing a 'local-first' knowledge hierarchy. It acts as an intelligent guardrail that gates expensive external tools, such as Perplexity Deep Research, while prioritizing internal project documentation, local RAG sources, and specific library guides. This ensures that AI agents remain grounded in project-specific context, minimize API costs, and reduce hallucinations by exhausting verified local data before seeking external information.

When should I use research-gate?

research-gate is useful in the following scenarios: • Cost Management: Preventing AI agents from autonomously triggering high-cost deep research tasks for queries that can be answered by local project files. • Context-Aware Development: Enforcing the use of project-specific conventions (e.g., CLAUDE.md, PLANNING.md) as the primary source of truth before looking for generic external solutions. • Hallucination Prevention: Requiring agents to verify library APIs and documentation through local RAG or specialized tools like Context7 before relying on general web knowledge. • Workflow Optimization: Streamlining developer productivity by allowing quick, low-cost lookups while maintaining a strict approval gate for time-consuming comprehensive research.

name	research-gate
description	Gates expensive external research (perplexity deep_research) while allowing quick lookups. Enforces knowledge priority - local documentation and project patterns first, external research only when necessary. Permissive mode allows context7, local-rag, and quick perplexity searches. (project)

Research Gate Skill

Purpose

Enforce knowledge priority by gating expensive research while allowing quick lookups. Context is king - project documentation takes precedence over external sources.

Permissive Mode (Default)

This skill operates in permissive mode:

Quick searches allowed
Library documentation allowed
Only expensive deep research is gated

What Gets Gated vs Allowed

BLOCKED (Requires Explicit Request)

Tool	Reason
`mcp__perplexity__deep_research`	Expensive, slow, often unnecessary

ALWAYS ALLOWED

Tool	Reason
`mcp__context7__resolve-library-id`	Needed for accurate library lookups
`mcp__context7__get-library-docs`	Prevents API hallucination
`mcp__local-rag__query_documents`	Project knowledge
`mcp__local-rag__ingest_file`	Adding to project knowledge
`mcp__perplexity__search`	Quick lookups, low cost
`mcp__perplexity__reason`	Reasoning, moderate cost
`WebSearch`	Quick web lookups
`WebFetch`	Fetching user-provided URLs

Knowledge Priority (Enforced)

When researching any topic, follow this priority:

1. CLAUDE.md (project conventions) ← MANDATORY
2. .claude/PLANNING.md (architecture) ← MANDATORY
3. examples/ (working code patterns) ← MANDATORY
4. local-rag (indexed project docs) ← ALWAYS QUERY
5. PRPs/ai_docs/ (library guides) ← CHECK
6. context7 (library APIs) ← ALLOWED
7. perplexity search/reason ← ALLOWED
8. perplexity deep_research ← GATED

When deep_research is Blocked

If mcp__perplexity__deep_research is called without explicit request:

Research gate: deep_research blocked

This operation is expensive and usually unnecessary.
Already checked:
- local-rag: [X results]
- context7: [available/not available]

To proceed, explicitly request deep research:
- "Do deep research on [topic]"
- "I need comprehensive research on [topic]"
- Use /maintenance:research command

When deep_research is Allowed

The gate opens when:

User explicitly says "deep research" or "comprehensive research"
User runs /maintenance:research command
User says "research this thoroughly"
No relevant results from local-rag AND context7

Pre-Research Checklist

Before ANY external research, verify:

Checked CLAUDE.md for conventions?
Checked PLANNING.md for architecture decisions?
Queried local-rag for existing knowledge?
Checked PRPs/ai_docs/ for library guides?
Used context7 for library APIs?

Only proceed to perplexity if local sources insufficient.

Research Flow

User asks about [topic]
        ↓
1. Check local-rag
   Found? → Use it
        ↓
2. Check PRPs/ai_docs/
   Found? → Use it
        ↓
3. Check context7 (if library-related)
   Found? → Use it
        ↓
4. Use perplexity search/reason (quick)
   Sufficient? → Use it
        ↓
5. deep_research ONLY if:
   - Explicitly requested, OR
   - All above sources insufficient

Integration with Agents

research-expert Agent

Bypasses gate (designed for research)
Still follows knowledge priority
Documents findings in PRPs/ai_docs/

implementation-guide Agent

Uses local knowledge first
Quick lookups allowed
deep_research requires explicit request

pattern-enforcer Agent

Uses project docs only
No external research needed
context7 for library verification

Output When Gated

research-gate: Checking local sources first...

Local results:
- local-rag: Found 3 relevant documents
- PRPs/ai_docs/: Found typer-patterns.md
- context7: Typer library docs available

Recommendation: Use local sources. Deep research not needed.

[If user still wants deep research, they must explicitly request it]

Configuration

Projects can adjust gate strictness in CLAUDE.md:

## Research Gate Settings

- deep_research: gated (default)
- perplexity_reason: allowed (default)
- perplexity_search: allowed (default)
- context7: always_allowed
- local_rag: always_first

What This Skill Does NOT Do

Does not block context7 (prevents hallucination)
Does not block local-rag (project knowledge)
Does not block quick perplexity searches
Does not require flags for normal lookups

Success Metrics

90%+ of queries answered from local sources
deep_research used only when necessary
No API hallucinations (context7 always available)
Fast response times (local sources first)

Core Principle: Project documentation is the source of truth. External research supplements, never replaces, local knowledge.

research-gate

When & Why to Use This Skill

Use Cases