Small to Before Research

Transform vague prompts into optimized research prompts for the researchCodebase agent.

Process

1. Analyze the vague input - Identify the core intent, implicit assumptions, and missing specifics
2. Extract key elements:

- What is being searched for (files, patterns, implementations, architecture) - Why (understanding, modification, debugging, documentation) - Scope constraints (specific directories, file types, modules)

1. Generate optimized prompt with these characteristics:

- Imperative voice ("Find...", "Identify...", "Document...") - Specific search targets (function names, patterns, file types) - Clear deliverables (list files, explain flow, map dependencies) - Scope boundaries when applicable

Output Format

**Research Prompt:**

[Optimized prompt here]

**Search Targets:**
- [Specific files/patterns/keywords to look for]

**Expected Deliverables:**
- [What the research should produce]

Examples

Vague: "how does auth work" Optimized:

Research Prompt:
Document the authentication flow from login to session management. Identify entry points, middleware, token handling, and session storage mechanisms.

Search Targets:
- auth, login, session, token, middleware, jwt, passport
- Files: *auth*, *session*, *login*

Expected Deliverables:
- Authentication entry points and routes
- Token/session lifecycle
- Key files and their relationships

Vague: "find where we handle errors" Optimized:

Research Prompt:
Locate error handling patterns across the codebase. Document centralized error handlers, try-catch patterns, error middleware, and custom error classes.

Search Targets:
- error, catch, throw, ErrorHandler, middleware
- Files: *error*, *exception*, *handler*

Expected Deliverables:
- Error handling entry points
- Custom error classes/types
- Error propagation patterns