Iterative Retrieval Skill

Problem

Loading all potentially relevant context upfront:

•Wastes context window
•Includes irrelevant information
•Reduces signal-to-noise ratio

Solution

Retrieve context incrementally based on actual execution needs.

Retrieval Levels

code

Level 0: Task Description
  └── Just the user request

Level 1: Immediate Context
  └── Files mentioned + direct dependencies

Level 2: Extended Context
  └── Related modules + tests

Level 3: Full Context
  └── Architecture docs + cross-cutting concerns

Retrieval Protocol

1. Start Minimal

yaml

initial_load:
  - Task description
  - CLAUDE.md (current section)
  - Target file(s) only

2. Detect Gaps

yaml

gap_signals:
  - Reference to unknown function/type
  - Import from unloaded module
  - Pattern that needs clarification
  - Test failure with unclear cause

3. Retrieve On-Demand

yaml

retrieval_action:
  signal: "Unknown type UserProfile"
  action: Load types/user.ts
  scope: Type definitions only

4. Cache Decisions

yaml

cache_entry:
  query: "UserProfile type"
  result: "types/user.ts lines 15-30"
  relevance: 0.95
  reuse_for: ["user-related tasks"]

Implementation Patterns

For Subagent Delegation

markdown

# Subagent Context Protocol

## Mandatory (Level 0-1)
- Task objective
- Target file
- Immediate imports

## On-Request (Level 2)
- Related tests
- Usage examples
- Similar implementations

## Escalation (Level 3)
- Architecture docs
- Cross-module dependencies
- Historical decisions

For Complex Analysis

javascript

async function iterativeAnalysis(task) {
  // Level 0: Understand task
  const taskContext = await loadMinimal(task);
  
  // Level 1: Load immediate
  let context = await loadImmediate(task.files);
  
  while (hasGaps(context)) {
    // Level 2+: Fill gaps
    const gaps = identifyGaps(context);
    const additional = await loadForGaps(gaps);
    context = mergeContext(context, additional);
    
    // Prevent infinite loops
    if (context.level > MAX_LEVEL) break;
  }
  
  return context;
}

Gap Detection Rules

Signal	Action	Priority
Undefined reference	Load definition file	High
Test import	Load test file	Medium
Config reference	Load config	Medium
Doc comment link	Load doc	Low
Historical mention	Query experience	Low

Context Scoring

yaml

relevance_score:
  direct_reference: 1.0    # Explicitly mentioned
  import_chain: 0.8        # Imported by target
  type_dependency: 0.7     # Type used
  test_coverage: 0.6       # Tests target
  same_module: 0.5         # Same directory
  doc_reference: 0.4       # Documentation
  historical: 0.3          # Past experience

Integration with VibeCoding

With phase-router

yaml

routing_context:
  path_a: level 0-1 only
  path_b: level 0-2
  path_c: full iterative

With subagents

yaml

subagent_protocol:
  initial: level 0-1
  on_request: level 2
  escalate_to_main: level 3

With verification-loop

yaml

verification_context:
  initial: test file + target
  on_failure: add related modules
  on_complex_failure: full context

Anti-Patterns

❌ Don't: Load entire codebase upfront ✅ Do: Start with target file only

❌ Don't: Include all tests ✅ Do: Load tests when verification fails

❌ Don't: Pass full history to subagent ✅ Do: Pass task-relevant summary

❌ Don't: Keep irrelevant context ✅ Do: Prune after task completion

Metrics

Track retrieval efficiency:

yaml

session_metrics:
  initial_context_tokens: 2000
  final_context_tokens: 8000
  retrieval_requests: 5
  cache_hits: 3
  relevance_score_avg: 0.82