---
name: aiskillstore/code-context-finder
source: https://app.decimal.ai/s/aiskillstore-code-context-finder@1/SKILL.md
source_sha256: baae1d2bb0e4
---

# Code Context Finder

## Overview

Find and surface relevant context while coding by combining knowledge graph search with code relationship analysis. Uses smart detection to identify when additional context would be helpful, then retrieves:

- **Knowledge graph entities**: Prior decisions, project context, related concepts
- **Code relationships**: Dependencies, imports, function calls, class hierarchies

## When to Use (Smart Detection)

This skill activates automatically when detecting:

| Trigger | What to Search |
|---------|----------------|
| Opening unfamiliar file | Knowledge graph for file/module context, code for imports/dependencies |
| Working on new feature | Prior decisions, related concepts, similar implementations |
| Debugging errors | Related issues, error patterns, affected components |
| Refactoring code | Dependent files, callers/callees, test coverage |
| Making architectural decisions | Past ADRs, related design docs, established patterns |
| Touching config/infra files | Related deployments, environment notes, past issues |

For detection triggers reference, load `references/detection_triggers.md`.

## Core Workflow

### 1. Detect Context Need

Identify triggers that suggest context would help:

```
Signals to watch:
- New/unfamiliar file opened
- Error messages mentioning unknown components
- Questions about "why" or "how" something works
- Changes to shared/core modules
- Architectural or design discussions
```

### 2. Search Knowledge Graph

Use MCP memory tools to find relevant entities:

```
# Search for related context
mcp__memory__search_nodes(query="<topic>")

# Open specific entities if known
mcp__memory__open_nodes(names=["entity1", "entity2"])

# View relationships
mcp__memory__read_graph()
```

**Search strategies:**

- Module/file names → project context
- Error types → past issues, solutions
- Feature names → prior decisions, rationale
- People names → ownership, expertise

### 3. Analyze Code Relationships

Find code-level context:

```python
# Find what imports this module
grep -r "from module import" --include="*.py"
grep -r "import module" --include="*.py"

# Find function callers
grep -r "function_name(" --include="*.py"

# Find class usages
grep -r "ClassName" --include="*.py"

# Find test coverage
find . -name "*test*.py" -exec grep -l "module_name" {} \;
```

For common search patterns, load `references/search_patterns.md`.

### 4. Synthesize Context

Present findings concisely:

```markdown
## Context Found

**Knowledge Graph:**
- [Entity]: Relevant observation
- [Decision]: Prior architectural choice

**Code Relationships:**
- Imported by: file1.py, file2.py
- Depends on: module_a, module_b
- Tests: test_module.py (5 tests)

**Suggested Actions:**
- Review [entity] before modifying
- Consider impact on [dependent files]
```

## Quick Reference

### Knowledge Graph Queries

| Intent | Query Pattern |
|--------|---------------|
| Find project context | `search_nodes("project-name")` |
| Find prior decisions | `search_nodes("decision")` or `search_nodes("<feature>")` |
| Find related concepts | `search_nodes("<concept>")` |
| Find people/owners | `search_nodes("<person-name>")` |
| Browse all | `read_graph()` |

### Code Relationship Queries

| Intent | Command |
|--------|---------|
| Find importers | `grep -r "from X import\|import X"` |
| Find callers | `grep -r "function("` |
| Find implementations | `grep -r "def function\|class Class"` |
| Find tests | `find -name "*test*" -exec grep -l "X"` |
| Find configs | `grep -r "X" *.json *.yaml *.toml` |

## Integration with Coding Workflow

### Before Making Changes

1. Check knowledge graph for context on module/feature
2. Find all files that import/depend on target
3. Locate relevant tests
4. Review prior decisions if architectural

### After Making Changes

1. Update knowledge graph if significant decision made
2. Note new patterns or learnings
3. Add observations to existing entities

### When Debugging

1. Search knowledge graph for similar errors
2. Find all code paths to affected component
3. Check for related issues/decisions
4. Document solution if novel

## Resources

### references/

- `detection_triggers.md` - Detailed trigger patterns for smart detection
- `search_patterns.md` - Common search patterns for code relationships

### scripts/

- `find_code_relationships.py` - Analyze imports, dependencies, and call graphs