pattern-detection

A codebase analysis guide that finds repeated conventions in naming, architecture, testing, organization, error handling, and configuration. It records examples and confidence for each detected pattern.

In plain words
What is it for?
Use it when joining an unfamiliar project, creating new code, reviewing changes, or resolving inconsistencies between different parts of a codebase.
Why use it?
It reduces the risk of adding code that conflicts with the project's existing style or architectural choices.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/rsmdt/the-startup/pattern-detection
Any agent
npx skills add rsmdt/the-startup --skill pattern-detection
Clone the repo
git clone --depth 1 https://github.com/rsmdt/the-startup

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,133 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00037 $0.01133
Opus 5 $0.00018 $0.00566
Sonnet 5 $0.00007 $0.00227
Haiku 4.5 $0.00004 $0.00113

Measured 2d ago against content hash 3fff6029b378, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pattern-detection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/team/skills/cross-cutting/pattern-detection/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 }

State { target = $ARGUMENTS samples = [] patterns = [] conflicts = [] }

Constraints

Always:

  • 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.
  • Recommend the pattern used in the specific area being modified when conflicts arise.
  • When tied on conflicts, prefer the pattern with tooling enforcement.

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.

Read the full file on GitHub · 158 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 158 lines · 37 tokens per session scan A 3fff6029b378

Subscribe to this mod's changes

pattern-detection is a skill published in the GitHub repository rsmdt/the-startup (510 stars, last pushed 29d ago), licensed MIT. It adds 37 tokens to every session and 1,133 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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