By codybrom
Automate MangroveTrader trades with x402 micropayment signing after MCP tool calls, and inject command documentation into every prompt for frictionless agent-driven trading workflows.
Evaluates whether abstractions genuinely provide a fundamentally different way of thinking or are structurally shallow. Use when adjacent layers feel redundant, when decorator/wrapper patterns add boilerplate without depth or when an abstraction feels leaky. Not for measuring a single module's interface-to-implementation ratio (use deep-modules) or checking for information leakage across boundaries (use information-hiding).
Evaluates whether modifications to existing code maintain or degrade design quality. Use when reviewing changes to existing code (diffs, PRs, or recently modified files) to assess whether each change looks designed-in or bolted-on. Not for scanning against a checklist of design smells (use red-flags) or assessing overall design investment (use strategic-mindset).
Reviews comment quality and documentation practices. Use when the user asks to review comments or documentation, when comments just repeat the code, when something is hard to describe in a sentence, or when writing documentation before code to surface design problems. Evaluates the four comment types, comments-first workflow, and comment rot.
Diagnoses what makes code complex and why, using the three-symptom two-root-cause framework. Use when code feels harder to work with than it should but the specific problem is unclear. This skill identifies WHETHER complexity exists and WHERE it comes from. Not for scanning a checklist of known design smells (use red-flags) or evaluating a specific module's depth (use deep-modules).
Measures module depth, whether the interface is simple relative to the implementation behind it. Use when a module's interface has too many parameters or methods, when there are too many small classes each doing too little or when methods just forward calls to other methods. Not for evaluating whether adjacent layers provide different abstractions (use abstraction-quality) or deciding whether to merge/split specific modules (use module-boundaries).
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
AI agents can write working code, but they don't stop to consider effective design unless asked. Clairvoyance is a set of skills inspired by John Ousterhout's A Philosophy of Software Design. Each skill gives your agent extrasensory perspective around software design, with concrete tests to see ahead of obstacles during implementation and review.
Skills activate automatically and push your agent to ask questions like:
You can also invoke them directly. Use /red-flags to trigger a design smell scan, /deep-modules to check interface depth and /design-it-twice to compare alternatives before committing.
Note: Installation differs by platform. Claude Code has a built-in plugin marketplace. Codex and OpenCode require manual setup.
/plugin marketplace add codybrom/clairvoyance
/plugin install clairvoyance@clairvoyance-plugins
npx skills add codybrom/clairvoyance --skill '*'
Tell Codex:
Fetch and follow instructions from https://raw.githubusercontent.com/codybrom/clairvoyance/refs/heads/main/.codex/INSTALL.md
See .codex/INSTALL.md for detailed steps.
Tell OpenCode:
Fetch and follow instructions from https://raw.githubusercontent.com/codybrom/clairvoyance/refs/heads/main/.opencode/INSTALL.md
See .opencode/INSTALL.md for detailed steps.
Machine-readable skill index for LLM agents:
| Skill | Covers |
|---|---|
deep-modules | Module depth, shallow modules, classitis, pass-through methods, interface vs implementation |
module-boundaries | Merge vs split, conjoined methods, method splitting, dependency minimization |
information-hiding | Information leakage, temporal decomposition, partial hiding, false encapsulation |
pull-complexity-down | Caller burden, configuration parameters, the core asymmetry |
| Skill | Covers |
|---|---|
abstraction-quality | Genuine vs false abstractions, layer boundaries, decorators |
general-vs-special | Interface generality, special-general mixture, edge-case elimination |
error-design | Define errors out of existence, exception masking, aggregation, just crash |
| Skill | Covers |
|---|---|
naming-obviousness | Isolation test, scope-length principle, consistency, avoid extra words |
comments-docs | Comment types, comments-first workflow, cross-module documentation |
| Skill | Covers |
|---|---|
strategic-mindset | Strategic vs tactical, investment rule, tactical tornado |
design-it-twice | Generate alternatives, compare on criteria, synthesize |
code-evolution | "Designed this way" standard, repetition, technical debt |
complexity-recognition | Change amplification, cognitive load, unknown unknowns |
| Skill | Covers |
|---|---|
red-flags | Design smell scan covering structure, boundaries, documentation, naming, and process |
design-review | Structured review funnel from complexity triage through structural, interface, and surface checks |
diagnose | Routes a vague symptom or complaint to the most relevant skill via a decision tree |
These skills are adapted in part from the teachings of John Ousterhout, professor of computer science at Stanford University, and his book A Philosophy of Software Design. This project is not affiliated with, endorsed by, or sponsored by John Ousterhout, Stanford University, or the publishers of A Philosophy of Software Design.
npx claudepluginhub codybrom/clairvoyance --plugin clairvoyanceIterative AI development loop for Claude Code — spins up isolated agents in a loop, each building on the journal notes of the previous one.
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.
Production-grade engineering skills for AI coding agents — covering the full software development lifecycle from spec to ship.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.