galeharness-cli

Analyzes code changes from an architectural perspective for pattern compliance and design integrity. Use when reviewing PRs, adding services, or evaluating structural refactors.

Always-on code-review persona. Reviews code for premature abstraction, unnecessary indirection, dead code, coupling between unrelated modules, and naming that obscures intent.

Conducts thorough research on repository structure, documentation, conventions, and implementation patterns. Use when onboarding to a new codebase or understanding project conventions.

Detects unrelated schema.rb changes in PRs by cross-referencing against included migrations. Use when reviewing PRs with database schema changes.

Always-on code-review persona. Reviews code for test coverage gaps, weak assertions, brittle implementation-coupled tests, and missing edge case coverage.

Conditional code-review persona, selected when the diff touches migration files, schema changes, data transformations, or backfill scripts. Reviews code for data integrity and migration safety.

Produces Go/No-Go deployment checklists with SQL verification queries, rollback procedures, and monitoring plans. Use when PRs touch production data, migrations, or risky data changes.

Visually compares live UI implementation against Figma designs and provides detailed feedback on discrepancies. Use after writing or modifying HTML/CSS/React components to verify design fidelity.

Iteratively refines UI design through N screenshot-analyze-improve cycles. Use PROACTIVELY when design changes aren't coming together after 1-2 attempts, or when user requests iterative refinement.

Reviews planning documents for missing design decisions -- information architecture, interaction states, user flows, and AI slop risk. Uses dimensional rating to identify gaps. Spawned by the document-review skill.

Conditional code-review persona, selected when Rails diffs introduce architectural choices, abstractions, or frontend patterns that may fight the framework. Reviews code from an opinionated DHH perspective.

Evaluates whether proposed technical approaches in planning documents will survive contact with reality -- architecture conflicts, dependency gaps, migration risks, and implementability. Spawned by the document-review skill.

Detects and fixes visual differences between a web implementation and its Figma design. Use iteratively when syncing implementation to match Figma specs.

Conditional document-review persona, selected when the document has >5 requirements or implementation units, makes significant architectural decisions, covers high-stakes domains, or proposes new abstractions. Challenges premises, surfaces unstated assumptions, and stress-tests decisions rather than evaluating document quality.

Conditional code-review persona, selected when the diff is large (>=50 changed lines) or touches high-risk domains like auth, payments, data mutations, or external APIs. Actively constructs failure scenarios to break the implementation rather than checking against known patterns.

Reviews code to ensure agent-native parity -- any action a user can take, an agent can also take. Use after adding UI features, agent tools, or system prompts.

Creates or updates README files following Ankane-style template for Ruby gems. Use when writing gem documentation with imperative voice, concise prose, and standard section ordering.

Conditional code-review persona, selected when the diff touches API routes, request/response types, serialization, versioning, or exported type signatures. Reviews code for breaking contract changes.

Researches and synthesizes external best practices, documentation, and examples for any technology or framework. Use when you need industry standards, community conventions, or implementation guidance.

Reviews CLI source code, plans, or specs for AI agent readiness using a severity-based rubric focused on whether a CLI is merely usable by agents or genuinely optimized for them.

Conditional code-review persona, selected when the diff touches CLI command definitions, argument parsing, or command handler implementations. Reviews CLI code for agent readiness -- how well the CLI serves autonomous agents, not just human users.

Final review pass to ensure code is as simple and minimal as possible. Use after implementation is complete to identify YAGNI violations and simplification opportunities.

Reviews planning documents for internal consistency -- contradictions between sections, terminology drift, structural issues, and ambiguity where readers would diverge. Spawned by the document-review skill.

Always-on code-review persona. Reviews code for logic errors, edge cases, state management bugs, error propagation failures, and intent-vs-implementation mismatches.

Reviews database migrations, data models, and persistent data code for safety. Use when checking migration safety, data constraints, transaction boundaries, or privacy compliance.

Validates data migrations, backfills, and production data transformations against reality. Use when PRs involve ID mappings, column renames, enum conversions, or schema changes.

Gathers comprehensive documentation and best practices for frameworks, libraries, or dependencies. Use when you need official docs, version-specific constraints, or implementation patterns.

Conditional code-review persona, selected when the diff touches Python code. Reviews changes with wangrenzhu's strict bar for Pythonic clarity, type hints, and maintainability.

Conditional code-review persona, selected when the diff touches Rails application code. Reviews Rails changes with wangrenzhu's strict bar for clarity, conventions, and maintainability.

Conditional code-review persona, selected when the diff touches TypeScript code. Reviews changes with wangrenzhu's strict bar for type safety, clarity, and maintainability.

Performs archaeological analysis of git history to trace code evolution, identify contributors, and understand why code patterns exist. Use when you need historical context for code changes.

Fetches and analyzes GitHub issues to surface recurring themes, pain patterns, and severity trends. Use when understanding a project's issue landscape, analyzing bug patterns for ideation, or summarizing what users are reporting.

Conditional code-review persona, selected when the diff touches async UI code, Stimulus/Turbo lifecycles, or DOM-timing-sensitive frontend behavior. Reviews code for race conditions and janky UI failure modes.

Searches docs/solutions/ for relevant past solutions by frontmatter metadata. Use before implementing features or fixing problems to surface institutional knowledge and prevent repeated mistakes.

Analyzes code for design patterns, anti-patterns, naming conventions, and duplication. Use when checking codebase consistency or verifying new code follows established patterns.

Analyzes code for performance bottlenecks, algorithmic complexity, database queries, memory usage, and scalability. Use after implementing features or when performance concerns arise.

Conditional code-review persona, selected when the diff touches database queries, loop-heavy data transforms, caching layers, or I/O-intensive paths. Reviews code for runtime performance and scalability issues.

Evaluates and resolves one or more related PR review threads -- assesses validity, implements fixes, and returns structured summaries with reply text. Spawned by the resolve-pr-feedback skill.

Conditional code-review persona, selected when reviewing a PR that has existing review comments or review threads. Checks whether prior feedback has been addressed in the current diff.

Reviews planning documents as a senior product leader -- challenges premise claims, assesses strategic consequences (trajectory, identity, adoption, opportunity cost), and surfaces goal-work misalignment. Domain-agnostic: users may be end users, developers, operators, or any audience. Spawned by the document-review skill.

Always-on code-review persona. Audits changes against the project's own CLAUDE.md and AGENTS.md standards -- frontmatter rules, reference inclusion, naming conventions, cross-platform portability, and tool selection policies.

Conditional code-review persona, selected when the diff touches error handling, retries, circuit breakers, timeouts, health checks, background jobs, or async handlers. Reviews code for production reliability and failure modes.

Reviews planning documents for scope alignment and unjustified complexity -- challenges unnecessary abstractions, premature frameworks, and scope that exceeds stated goals. Spawned by the document-review skill.

Evaluates planning documents for security gaps at the plan level -- auth/authz assumptions, data exposure risks, API surface vulnerabilities, and missing threat model elements. Spawned by the document-review skill.

Conditional code-review persona, selected when the diff touches auth middleware, public endpoints, user input handling, or permission checks. Reviews code for exploitable vulnerabilities.

Performs security audits for vulnerabilities, input validation, auth/authz, hardcoded secrets, and OWASP compliance. Use when reviewing code for security issues or before deployment.

Searches Claude Code, Codex, and Cursor session history for related prior sessions about the same problem or topic. Use to surface investigation context, failed approaches, and learnings from previous sessions that the current session cannot see. Supports time-based queries for conversational use.

Searches Slack for organizational context relevant to the current task -- decisions, constraints, and discussions that may not be documented elsewhere. Use when the user explicitly asks to search Slack for context during ideation, planning, or brainstorming. Always surfaces the workspace identity so the user can verify the correct Slack instance was searched.

Analyzes specifications and feature descriptions for user flow completeness and gap identification. Use when a spec, plan, or feature description needs flow analysis, edge case discovery, or requirements validation.

Conditional code-review persona, selected when the diff touches Swift files (.swift), SwiftUI views, UIKit controllers, iOS entitlements, privacy manifests, Core Data model bundles, SPM manifests, storyboards/XIBs, or semantic build-setting/target/signing changes inside .pbxproj. Reviews Swift and iOS code for SwiftUI correctness, state management, memory safety, Swift concurrency, Core Data threading, and accessibility.

Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.

Run comprehensive agent-native architecture review with scored principles

Sync GaleHarnessCLI skills with latest changes from the reference upstream repo. Use when you need to pull upstream updates, review what changed, apply gh: renames, and re-inject HKTMemory patches. Triggers: 'sync upstream', 'update skills', 'pull latest changes', 'upstream diff'.

This skill should be used when writing Ruby and Rails code in DHH's distinctive 37signals style. It applies when writing Ruby code, Rails applications, creating models, controllers, or any Ruby file. Triggers on Ruby/Rails code generation, refactoring requests, code review, or when the user mentions DHH, 37signals, Basecamp, HEY, or Campfire style. Embodies REST purity, fat models, thin controllers, Current attributes, Hotwire patterns, and the "clarity over cleverness" philosophy.

Review requirements or plan documents using parallel persona agents that surface role-specific issues. Use when a requirements document or plan document exists and the user wants to improve it.

Build web interfaces with genuine design quality, not AI slop. Use for any frontend work - landing pages, web apps, dashboards, admin panels, components, interactive experiences. Activates for both greenfield builds and modifications to existing applications. Detects existing design systems and respects them. Covers composition, typography, color, motion, and copy. Verifies results via screenshots before declaring done.

This skill should be used when reviewing or editing copy to ensure adherence to Every's style guide. It provides a systematic line-by-line review process for grammar, punctuation, mechanics, and style guide compliance.

This skill should be used when generating and editing images using the Gemini API (Nano Banana Pro). It applies when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images.

Explore requirements and approaches through collaborative dialogue before writing a right-sized requirements document and planning implementation. Use for feature ideas, problem framing, when the user says 'let's brainstorm', or when they want to think through options before deciding what to build. Also use when a user describes a vague or ambitious feature request, asks 'what should we build', 'help me think through X', presents a problem with multiple valid solutions, or seems unsure about scope or direction — even if they don't explicitly ask to brainstorm.

Refresh stale or drifting learnings and pattern docs in docs/solutions/ by reviewing, updating, consolidating, replacing, or deleting them against the current codebase. Use after refactors, migrations, dependency upgrades, or when a retrieved learning feels outdated or wrong. Also use when reviewing docs/solutions/ for accuracy, when a recently solved problem contradicts an existing learning, when pattern docs no longer reflect current code, or when multiple docs seem to cover the same topic and might benefit from consolidation.

Document a recently solved problem to compound your team's knowledge

Debug and fix iOS Swift/ObjC bugs with Morph-X blueprint, transform, audit, and memory fingerprinting to reduce template-code repetition risk.

Systematically find root causes and fix bugs. Use when debugging errors, investigating test failures, reproducing bugs from issue trackers (GitHub, Linear, Jira), or when stuck on a problem after failed fix attempts. Also use when the user says 'debug this', 'why is this failing', 'fix this bug', 'trace this error', or pastes stack traces, error messages, or issue references.

Capture a visual demo reel (GIF, terminal recording, screenshots) for PR descriptions. Use when shipping UI changes, CLI features, or any work with observable behavior that benefits from visual proof. Also use when asked to add a demo, record a GIF, screenshot a feature, show what changed visually, create a demo reel, capture evidence, add proof to a PR, or create a before/after comparison.

Generate and critically evaluate grounded improvement ideas for the current project. Use when asking what to improve, requesting idea generation, exploring surprising improvements, or wanting the AI to proactively suggest strong project directions before brainstorming one in depth. Triggers on phrases like 'what should I improve', 'give me ideas', 'ideate on this project', 'surprise me with improvements', 'what would you change', or any request for AI-generated project improvement suggestions rather than refining the user's own idea.

Run metric-driven iterative optimization loops. Define a measurable goal, build measurement scaffolding, then run parallel experiments that try many approaches, measure each against hard gates and/or LLM-as-judge quality scores, keep improvements, and converge toward the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation. Inspired by Karpathy's autoresearch, generalized for multi-file code changes and non-ML domains.

Create structured plans for any multi-step task -- software features, research workflows, events, study plans, or any goal that benefits from structured breakdown. Also deepen existing plans with interactive review of sub-agent findings. Use for plan creation when the user says 'plan this', 'create a plan', 'write a tech plan', 'plan the implementation', 'how should we build', 'what's the approach for', 'break this down', 'plan a trip', 'create a study plan', or when a brainstorm/requirements document is ready for planning. Use for plan deepening when the user says 'deepen the plan', 'deepen my plan', 'deepening pass', or uses 'deepen' in reference to a plan.

[BETA] Start the dev server, open the feature in a browser, and iterate on improvements together.

Write or regenerate a value-first pull-request description (title + body) for the current branch's commits or for a specified PR. Use when the user says 'write a PR description', 'refresh the PR description', 'regenerate the PR body', 'rewrite this PR', 'freshen the PR', 'update the PR description', 'draft a PR body for this diff', 'describe this PR properly', 'generate the PR title', or pastes a GitHub PR URL / #NN / number. Also used internally by git-commit-push-pr (single-PR flow) and gh-pr-stack (per-layer stack descriptions) so all callers share one writing voice. Input is a natural-language prompt. A PR reference (a full GitHub PR URL, `pr:561`, `#561`, or a bare number alone) picks a specific PR; anything else is treated as optional steering for the default 'describe my current branch' mode. Returns structured {title, body_file} (body written to an OS temp file) for the caller to apply via gh pr edit or gh pr create — this skill never edits the PR itself and never prompts for confirmation.

Structured code review using tiered persona agents, confidence-gated findings, and a merge/dedup pipeline. Use when reviewing code changes before creating a PR.

Extract conversation skeleton or error signals from a single session file at a given path. Invoked by session-research agents after they have selected which sessions to deep-dive — not intended for direct user queries.

Discover session files for a repo across Claude Code, Codex, and Cursor, and extract session metadata (timestamps, branch, cwd, size, platform). Invoked by session-research agents — not intended for direct user queries.

Search and ask questions about your coding agent session history. Use when asking what you worked on, what was tried before, how a problem was investigated across sessions, what happened recently, or any question about past agent sessions. Also use when the user references prior sessions, previous attempts, or past investigations — even without saying 'sessions' explicitly.

Diagnose and configure compound-engineering environment. Checks CLI dependencies, plugin version, and repo-local config. Offers guided installation for missing tools. Use when troubleshooting missing tools, verifying setup, or before onboarding.

Search Slack for interpreted organizational context -- decisions, constraints, and discussion arcs that shape the current task. Produces a research digest with cross-cutting analysis and research-value assessment, not raw message lists. Use when searching Slack for context during planning, brainstorming, or any task where organizational knowledge matters. Trigger phrases: 'search slack for', 'what did we discuss about', 'slack context for', 'organizational context about', 'what does the team think about', 'any slack discussions on'. Differs from slack:find-discussions which returns individual message results without synthesis.

Check if the GaleHarnessCLI plugin is up to date and recommend the update command if not. Use when the user says "update gale harness", "check gale harness version", "gh update", "is gale harness up to date", "update gh plugin", or reports issues that might stem from a stale GaleHarnessCLI plugin version. This skill only works in Claude Code — it relies on the plugin harness cache layout.

[BETA] Execute work with external delegate support. Same as gh:work but includes experimental Codex delegation mode for token-conserving code implementation.

Execute iOS Swift/ObjC work with Morph-X blueprint, transform, audit, and memory fingerprinting to reduce template-code repetition risk.

Execute work efficiently while maintaining quality and finishing features

Clean up local branches whose remote tracking branch is gone. Use when the user says "clean up branches", "delete gone branches", "prune local branches", "clean gone", or wants to remove stale local branches that no longer exist on the remote. Also handles removing associated worktrees for branches that have them.

Commit, push, and open a PR with an adaptive, value-first description. Use when the user says "commit and PR", "push and open a PR", "ship this", "create a PR", "open a pull request", "commit push PR", or wants to go from working changes to an open pull request in one step. Also use when the user says "update the PR description", "refresh the PR description", "freshen the PR", or wants to rewrite an existing PR description. Produces PR descriptions that scale in depth with the complexity of the change, avoiding cookie-cutter templates.

Create a git commit with a clear, value-communicating message. Use when the user says "commit", "commit this", "save my changes", "create a commit", or wants to commit staged or unstaged work. Produces well-structured commit messages that follow repo conventions when they exist, and defaults to conventional commit format otherwise.

Create an isolated git worktree for parallel feature work or PR review. Use when starting work that should not disturb the current checkout, or when `gh:work` or `gh:review` offers a worktree option.

Full autonomous engineering workflow

Create, share, view, comment on, edit, and run human-in-the-loop review loops over markdown documents via Proof, the collaborative markdown editor at proofeditor.ai ("Proof editor"). Use when the user wants to render or view a local markdown file in Proof, share markdown to get a URL, iterate collaboratively on a Proof doc, comment on or suggest edits in Proof, HITL a spec/plan/draft for human review, sync a Proof doc back to local, or work from a proofeditor.ai URL. Trigger on phrases like "view this in proof", "share to proof", "iterate with proof", or "HITL this doc", and on gh-brainstorm / gh-ideate / gh-plan handoffs for human review. Also match clear requests for a rendered/shared markdown review surface even if the user does not name Proof. Do not trigger on "proof" meaning evidence, math/logic proof, burden of proof, proof-of-concept, or bare "proofread this" requests where inline text review is expected.

Report a bug in the compound-engineering plugin

Resolve PR review feedback by evaluating validity and fixing issues in parallel. Use when addressing PR review comments, resolving review threads, or fixing code review feedback.

Run browser tests on pages affected by current PR or branch

Build and test iOS apps on simulator using XcodeBuildMCP. Use after making iOS code changes, before creating a PR, or when verifying app behavior and checking for crashes on simulator.