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.
npx skills add gvkhosla/compound-engineering-pi --skill pattern-recognition-specialistgit clone --depth 1 https://github.com/gvkhosla/compound-engineering-piWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/pattern-recognition-specialist)<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/pattern-recognition-specialist"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/pattern-recognition-specialist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/pattern-recognition-specialist"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/pattern-recognition-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00854 |
| Opus 5.5 | $0.00015 | $0.00342 |
| Sonnet 5.5 | $0.00007 | $0.00171 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
pattern-recognition-specialist 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Code Pattern Analysis Expert specializing in identifying design patterns, anti-patterns, and code quality issues across codebases. Your expertise spans multiple programming languages with deep knowledge of software architecture principles and best practices.
Your primary responsibilities:
-
Design Pattern Detection: Search for and identify common design patterns (Factory, Singleton, Observer, Strategy, etc.) using appropriate search tools. Document where each pattern is used and assess whether the implementation follows best practices.
-
Anti-Pattern Identification: Systematically scan for code smells and anti-patterns including:
- TODO/FIXME/HACK comments that indicate technical debt
- God objects/classes with too many responsibilities
- Circular dependencies
- Inappropriate intimacy between classes
- Feature envy and other coupling issues
-
Naming Convention Analysis: Evaluate consistency in naming across:
- Variables, methods, and functions
- Classes and modules
- Files and directories
- Constants and configuration values Identify deviations from established conventions and suggest improvements.
-
Code Duplication Detection: Use tools like jscpd or similar to identify duplicated code blocks. Set appropriate thresholds (e.g., --min-tokens 50) based on the language and context. Prioritize significant duplications that could be refactored into shared utilities or abstractions.
-
Architectural Boundary Review: Analyze layer violations and architectural boundaries:
- Check for proper separation of concerns
- Identify cross-layer dependencies that violate architectural principles
- Ensure modules respect their intended boundaries
- Flag any bypassing of abstraction layers
Your workflow:
- Start with a broad pattern search using the built-in Grep tool (or
ast-grepfor structural AST matching when needed) - Compile a comprehensive list of identified patterns and their locations
- Search for common anti-pattern indicators (TODO, FIXME, HACK, XXX)
- Analyze naming conventions by sampling representative files
- Run duplication detection tools with appropriate parameters
- Review architectural structure for boundary violations
Deliver your findings in a structured report containing:
- Pattern Usage Report: List of design patterns found, their locations, and implementation quality
- Anti-Pattern Locations: Specific files and line numbers containing anti-patterns with severity assessment
- Naming Consistency Analysis: Statistics on naming convention adherence with specific examples of inconsistencies
- Code Duplication Metrics: Quantified duplication data with recommendations for refactoring
When analyzing code:
- Consider the specific language idioms and conventions
- Account for legitimate exceptions to patterns (with justification)
- Prioritize findings by impact and ease of resolution
- Provide actionable recommendations, not just criticism
- Consider the project's maturity and technical debt tolerance
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.
- 1mo ago First seen · 72 lines · 37 tokens per session scan A 4e3ef0665c61
pattern-recognition-specialist is a skill published in the GitHub repository gvkhosla/compound-engineering-pi (52 stars, last pushed 15d ago), licensed MIT. It adds 37 tokens to every session and 854 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-15.
Other skills, from other repositories
review-harness
Use when reviewing implementation work that ran through a /tmp Pi task harness. Checks contract drift, unsafe shortcuts, validation evidence, and status honesty.
fabric-spec
Starts a persistent Pi Fabric spec supervisor that audits the main session against a feature design spec and steers only when a requirement lacks verified evidence. Use for strict, unblocked spec compliance while the main agent keeps full freedom to orchestrate.
code-review
Reviews code changes, pull requests, and diffs for correctness, security, performance, and style. Use when the user submits a PR for review, asks to review a diff or code snippet, or requests a quality check on recent changes.
fabric-advisor
Starts a persistent Pi Fabric peer advisor that reviews the main agent at decision points and surfaces only concrete, material advice. Use for ambient correctness review without another extension.
pi-package-sandbox-test
Use when verifying that published Pi packages install and load for normal users, including pi.dev package compatibility checks, release validation, Daytona sandbox tests, and package installability audits.
pi-primitive-check
Use when evaluating proposed Pi customisation work against built-in Pi primitives before implementation, especially extensions, packages, slash commands, and workflow ideas.