phoenix-auth-customization
MANDATORY when extending phx.gen.auth with custom fields. Invoke before adding usernames, profiles, or custom registration fields.
phoenix-authorization-patterns
MANDATORY for ALL authorization and access control work. Invoke before writing permission checks, policy modules, or role-based access.
telemetry-essentials
MANDATORY for ALL telemetry, logging, and observability work. Invoke before writing telemetry handlers, Logger calls, or metrics code.
otp-essentials
MANDATORY for ALL OTP work. Invoke before writing GenServer, Supervisor, Task, or Agent modules.
phoenix-channels-essentials
MANDATORY for ALL Phoenix Channels work. Invoke before writing socket, channel, or Presence modules.
security-essentials
MANDATORY for ALL security-sensitive code. Invoke before writing auth, token handling, redirects, or user input processing.
testing-essentials
MANDATORY for ALL test files. Invoke before writing any _test.exs file.
ecto-nested-associations
MANDATORY for ALL nested association and multi-table work. Invoke before writing cast_assoc, cast_embed, Ecto.Multi, or cascade operations.
elixir-essentials
MANDATORY for ALL Elixir code changes. Invoke before writing any .ex or .exs file.
oban-essentials
MANDATORY for ALL Oban work. Invoke before writing workers or enqueuing jobs.
phoenix-uploads
MANDATORY for file upload features. Invoke before implementing upload or file serving functionality.
phoenix-pubsub-patterns
MANDATORY for ALL PubSub and real-time broadcast work. Invoke before writing PubSub.subscribe, broadcast, or handle_info for real-time updates.
phoenix-liveview-essentials
MANDATORY for ALL LiveView work. Invoke before writing LiveView modules or .heex templates.
phoenix-liveview-auth
MANDATORY for ALL LiveView authentication work. Invoke before writing on_mount hooks, auth plugs for LiveViews, or session handling in LiveView modules.
phoenix-json-api
MANDATORY for ALL JSON API work. Invoke before writing API controllers, pipelines, or JSON responses.
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
skill-tester
Validates all interactive skills in this repo against the Agent Skills spec, project conventions, and structural requirements. Runs quick_validate.py, checks line limits, verifies cross-references, and tests hook scripts. Use when skills have been added or modified and you want to verify everything passes before committing or submitting.
skill-tester-ci
Validates all CI skills in this repo. Checks Agent Skills spec compliance, gh-aw workflow compilation, permission correctness, and structural conventions. Use when CI skills have been added or modified and you want to verify they compile and conform before committing.
skill-pipeline
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simplify-and-harden-ci
CI-only Simplify & Harden workflow for pull requests using gh-aw (GitHub Agentic Workflows). Runs headless scan-and-report checks for simplify/harden/document, posts structured findings, and can block merges on critical or advisory classes. Use when: you want automated quality/security review in CI without interactive approvals.
self-improvement-ci
CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.
dx-data-navigator
Query Developer Experience (DX) data via the DX Data MCP server PostgreSQL database. Use this skill when analyzing developer productivity metrics, team performance, PR/code review metrics, deployment frequency, incident data, AI tool adoption, survey responses, DORA metrics, or any engineering analytics. Triggers on questions about DX scores, team comparisons, cycle times, code quality, developer sentiment, AI coding assistant adoption, sprint velocity, or engineering KPIs.
verify-gate
Runs project compile, test, and lint commands between implementation and quality review. Gates simplify-and-harden behind machine verification. If checks fail, routes back to implementation with diagnostics for a fix loop. If checks pass, signals ready for the quality pass. Use after any implementation work completes and before simplify-and-harden. Essential for the inner loop's verify step.
simplify-and-harden
Post-completion self-review for coding agents that runs simplify, harden, and micro-documentation passes on non-trivial code changes. Use when: a coding task is complete in a general agent session and you want a bounded quality and security sweep before signaling done. For CI pipeline execution, use simplify-and-harden-ci.
self-improvement
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Codex ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Codex realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.
plan-interview
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mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
intent-framed-agent
Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.
pre-flight-check
[Beta] Session-start scan that surfaces relevant learnings, recent errors, and eval status before work begins. Bridges the outer loop back into the inner loop by making accumulated knowledge visible at task start. Activated via SessionStart hook or manually before major tasks.
learning-aggregator-ci
[Beta] CI-only learning aggregation workflow using gh-aw (GitHub Agentic Workflows). Scans .learnings/ files on a schedule, groups entries by pattern_key, identifies promotion-ready patterns, and posts a gap report as a PR or issue comment. Use when: you want automated cross-session pattern detection in CI/headless pipelines without interactive prompts. For interactive use, use learning-aggregator.
learning-aggregator
[Beta] Cross-session analysis of accumulated .learnings/ files. Reads all entries, groups by pattern_key, computes recurrence across sessions, and outputs ranked promotion candidates. This is the outer loop's inspect step — it turns raw learning data into actionable gap reports. Use on a regular cadence (weekly, before major tasks, or at session start for critical projects). Can be invoked manually or scheduled.
eval-creator
[Beta] Creates permanent eval cases from promoted learnings and runs regression checks against them. Turns failures into test cases that prevent silent regression. This is the outer loop's regress-test step. Use when a learning is promoted and has a clear pass/fail condition, or on cadence to verify promoted rules still hold.
eval-creator-ci
[Beta] CI-only eval regression runner using gh-aw (GitHub Agentic Workflows). Runs all eval cases in .evals/ on a schedule or per-PR, reports pass/fail results, and can block merges on regressions. Also creates new eval cases from promoted patterns flagged by learning-aggregator-ci. Use when: you want automated regression testing of promoted rules in CI/headless pipelines. For interactive eval creation and runs, use eval-creator.
agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or the loop cap is reached. Use when: implementing features from a spec or plan, hardening existing code, fixing a batch of issues, or any multi-file task that benefits from a build-verify-fix cycle.
context-surfing
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gh-pr-review
View and manage inline GitHub PR review comments with full thread context from the terminal
nano-banana-build
Generate and edit high-quality images using Gemini 2.5 Flash Image and Gemini 3 Pro Image (Nano Banana). Supports Text-to-Image, Style Transfer, Virtual Try-On, and Character Consistency.
deep-research
Perform autonomous, multi-step research using the Gemini Deep Research Agent (Interactions API). Supports web search, file/directory context, and resilient streaming.
google-adk-python
Expert guidance on the Google Agent Development Kit (ADK) for Python. Use this skill when the user asks about building agents, using tools, streaming, callbacks, tutorials, deployment, or advanced architecture with the Google ADK in Python.
google-developer-knowledge
Search and retrieve Google's developer documentation using the Developer Knowledge API. Query documentation chunks, get full document content, or batch retrieve multiple documents. Covers ai.google.dev, developer.android.com, docs.cloud.google.com, firebase.google.com, and more.
google-genai-sdk-python
Expert guidance for writing Python code using the official Google GenAI SDK (google-genai) for Gemini API and Vertex AI. Use for text generation, multimodal inputs, reasoning, tools, and media generation.
nano-banana-use
Generate, edit, and compose images using Gemini Nano Banana models via portable Python scripts. Handles authentication via API Key or Vertex AI environment variables. Available parameters: prompt, model, aspect-ratio, safety-filter-level. Always confirm parameters with the user or explicitly state defaults before running.
speech-build
Generate and transcribe speech using Google's Gemini-TTS and Chirp 3 models. Supports Text-to-Speech (Single/Multi-speaker), Instant Custom Voice, and Speech-to-Text (Transcription/Diarization).
speech-use
Generate (TTS), Transcribe (STT), and Clone voices using Google's GenAI and Cloud Speech SDKs. Supports Gemini-TTS, Chirp 3, and Instant Custom Voice.
veo-build
Create and edit videos using Google's Veo 2 and Veo 3 models. Supports Text-to-Video, Image-to-Video, Inpainting, and Advanced Controls.
veo-use
Create and edit videos using Google's Veo 2 and Veo 3 models. Supports Text-to-Video, Image-to-Video, Reference-to-Video, Inpainting, and Video Extension. Available parameters: prompt, image, mask, mode, duration, aspect-ratio. Always confirm parameters with the user or explicitly state defaults before running.
nano-image-generator
Generate images using Nano Banana Pro (Gemini 3 Pro Preview). Use when creating app icons, logos, UI graphics, marketing banners, social media images, illustrations, diagrams, or any visual assets. Supports reference images for style transfer and character consistency. Triggers include phrases like 'generate an image', 'create a graphic', 'make an icon', 'design a logo', 'create a banner', 'same style as', 'keep the style', or any request needing visual content.
charlie
Your AI CFO for bootstrapped startups, named after Charlie Munger who embodied the principle that capital discipline is a competitive advantage. Provides financial frameworks for cash management, runway calculations, unit economics (LTV:CAC), capital allocation, hiring ROI, burn rate analysis, working capital optimization, and forecasting. Use for questions like "should we make this hire?", "how much runway do we need?", "what metrics should I track?", "how do I forecast revenue?", or any strategic financial decision at a self-funded company.
sentry-create-alert
Create Sentry alerts using the workflow engine API. Use when asked to create alerts, set up notifications, configure issue priority alerts, or build workflow automations. Supports email, Slack, PagerDuty, Discord, and other notification actions.
sentry-cocoa-sdk
Full Sentry SDK setup for Apple platforms (iOS, macOS, tvOS, watchOS, visionOS). Use when asked to "add Sentry to iOS", "add Sentry to Swift", "install sentry-cocoa", or configure error monitoring, tracing, profiling, session replay, or logging for Apple applications. Supports SwiftUI and UIKit.
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