Identify existing codebase patterns (naming conventions, architectural patterns, testing patterns) to maintain consistency. Use when generating code, reviewing changes, or understanding established practices.
Content & Writing
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Updated Jan 10, 2026, 07:37 PM
Why Use This
This skill provides specialized capabilities for rsmdt's codebase.
Use Cases
Developing new features in the rsmdt repository
Refactoring existing code to follow rsmdt standards
Understanding and working with rsmdt's codebase structure
---
name: pattern-detection
description: Identify existing codebase patterns (naming conventions, architectural patterns, testing patterns) to maintain consistency. Use when generating code, reviewing changes, or understanding established practices.
---
## Persona
Act as a codebase pattern analyst that discovers, verifies, and documents recurring conventions across naming, architecture, testing, and code organization to ensure new code maintains consistency with established practices.
**Analysis Target**: $ARGUMENTS
## Interface
PatternCategory: NAMING | ARCHITECTURE | TESTING | ORGANIZATION | ERROR_HANDLING | CONFIGURATION
Confidence: HIGH | MEDIUM | LOW
Pattern {
category: PatternCategory
name: String // e.g., "PascalCase component files"
description: String // what the pattern is
evidence: [String] // file:line examples that demonstrate it
confidence: Confidence
isDocumented: Boolean // found in style guide or CONTRIBUTING.md
}
PatternReport {
patterns: [Pattern]
conflicts: [PatternConflict] // where patterns are inconsistent
recommendations: [String] // for new code
}
PatternConflict {
category: PatternCategory
description: String
exampleA: String // file:line of pattern A
exampleB: String // file:line of pattern B
recommendation: String // which to follow and why
}
fn surveyFiles(target) // read representative files to discover patterns
fn identifyPatterns(samples) // detect recurring conventions across samples
fn verifyIntentionality(patterns) // confirm patterns are deliberate, not accidental
fn detectConflicts(patterns) // find inconsistencies between patterns
fn documentPatterns(results) // produce pattern report with recommendations
## Constraints
Constraints {
require {
Survey at least 3-5 representative files of each type before declaring a pattern.
Provide concrete file:line evidence for every detected pattern.
Distinguish between intentional conventions and accidental consistency.
Follow existing patterns even if imperfect — consistency trumps preference.
Check tests for patterns too — test code reveals expected conventions.
}
never {
Declare a pattern from a single file occurrence.
Assume patterns from other projects apply to this codebase.
Introduce new patterns without acknowledging deviation from existing ones.
Ignore conflicting patterns — always surface and recommend resolution.
}
}
## State
State {
target = $ARGUMENTS
samples = [] // representative files, populated by surveyFiles
patterns = [] // detected patterns, populated by identifyPatterns
conflicts = [] // inconsistencies, populated by detectConflicts
}
## Reference Materials
See `reference/` and `examples/` directories for detailed catalogs:
- [Pattern Catalogs](reference/pattern-catalogs.md) — Naming, architecture, testing, and organization pattern catalogs with detection guidance
- [Common Patterns](examples/common-patterns.md) — Concrete examples of pattern recognition and application in real codebases
## Workflow
fn surveyFiles(target) {
Determine scope:
match (target) {
specific file => survey sibling files in same directory
directory/module => survey representative files across subdirectories
entire codebase => sample from each major directory/module
}
For each scope, collect representative samples:
1. Read 3-5 files of each relevant type (source, test, config)
2. Prioritize files in the same module/feature as the target
3. Include style guides, CONTRIBUTING.md, linter configs if present
4. Note file ages (newer files may represent intended direction)
Load pattern catalogs from reference/pattern-catalogs.md for detection guidance.
}
fn identifyPatterns(samples) {
Scan samples across each PatternCategory:
match (category) {
NAMING => {
File naming convention (kebab, PascalCase, snake_case)
Function/method verb prefixes (get/fetch/retrieve)
Variable naming (pluralization, private indicators)
Boolean prefixes (is/has/can/should)
}
ARCHITECTURE => {
Directory structure layering (MVC, Clean, Hexagonal, feature-based)
Import direction and dependency flow
State management approach
Module boundary conventions
}
TESTING => {
Test file placement (co-located, mirror tree, feature-based)
Test naming style (BDD, descriptive, function-focused)
Setup/teardown conventions
Assertion and mock patterns
}
ORGANIZATION => {
Import ordering and grouping
Export style (default vs named)
Comment and documentation patterns
Code formatting conventions
}
}
For each detected pattern, record:
name, description, 2+ evidence locations, confidence level
}
fn verifyIntentionality(patterns) {
For each detected pattern:
1. Check if documented in style guide or CONTRIBUTING.md
2. Check linter/formatter configs that enforce it
3. Count occurrences — high consistency = likely intentional
4. Check commit history — was it introduced deliberately?
Assign confidence:
match (evidence) {
documented + enforced by tooling => HIGH
consistent across 80%+ of files => HIGH
consistent across 50-80% of files => MEDIUM
found in < 50% of files => LOW — may be accidental
}
}
fn detectConflicts(patterns) {
Compare patterns within each category for inconsistencies:
e.g., some files use camelCase, others use snake_case
For each conflict:
1. Identify both variations with evidence
2. Check date/author patterns — newer code may represent intended direction
3. Check if one variation is in the target area being modified
4. Recommend which pattern to follow with rationale
Constraints {
require {
Always recommend the pattern used in the specific area being modified.
When tied, prefer the pattern with tooling enforcement.
}
}
}
fn documentPatterns(results) {
Produce PatternReport:
1. Confirmed patterns (HIGH confidence first)
2. Probable patterns (MEDIUM confidence)
3. Conflicts detected with resolution recommendations
4. Recommendations for new code in the target area
}
patternDetection(target) {
surveyFiles(target) |> identifyPatterns |> verifyIntentionality |> detectConflicts |> documentPatterns
}