small-claims-assistant-prototype

Use this skill when a BC Small Claims Notice of Claim draft is already captured in canonical JSON and the next step is deterministic PDF-generation readiness review, renderer handoff, or artifact verification. This skill is for JSON-to-PDF generation only. It must not take over guided intake or canonical JSON authoring.

Use this skill when a BC Small Claims Notice of Claim draft already exists in canonical JSON and the next step is to produce a deterministic mock filing payload, simulate downstream submission, or inspect adapter artifacts. This skill is for JSON-to-adapter handoff only. It must not take over guided intake or PDF rendering.

This skill should be used when the user wants to start a BC Small Claims Notice of Claim, answer the Form 1 questions interactively, turn freeform facts into a structured intake packet, align the answers to the observed Filing Assistant question flow and canonical case JSON, or identify what information is still missing before validation or rendering.

Use this skill when a BC Small Claims Notice of Claim draft is already captured in canonical JSON and the next step is deterministic PDF-generation readiness review, renderer handoff, or artifact verification. This skill is for JSON-to-PDF generation only. It must not take over guided intake or canonical JSON authoring.

Use this skill when a BC Small Claims Notice of Claim draft already exists in canonical JSON and the next step is to produce a deterministic mock filing payload, simulate downstream submission, or inspect adapter artifacts. This skill is for JSON-to-adapter handoff only. It must not take over guided intake or PDF rendering.

This skill should be used when the user wants to start a BC Small Claims Notice of Claim, answer the Form 1 questions interactively, turn freeform facts into a structured intake packet, align the answers to the observed Filing Assistant question flow and canonical case JSON, or identify what information is still missing before validation or rendering.

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Use when you have a written implementation plan to execute in a separate session with review checkpoints

SME-facing orchestrator for the Business Exploration Loop. Supports 4 session types (greenfield, brownfield, discovery-only, spike) with adaptive phase selection. Manages state via exploration-dashboard.md, enforces phase gates, and routes to child skills in sequence. Phases can be skipped based on session type. Single canonical entry point — invoke at the start of any exploration session or to resume an in-progress session. Trigger phrases: "start an exploration", "let's explore this idea", "resume my exploration", "where did we leave off", "start discovery".

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

Use when executing implementation plans with independent tasks in the current session

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Use when implementing any feature or bugfix, before writing implementation code

Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Use when you have a spec or requirements for a multi-step task, before touching code

Use when creating new skills, editing existing skills, or verifying skills work before deployment

ADR management skill. Auto-invoked for generating architecture decisions, documenting design rationale, and maintaining the decision record log. Uses native read/write tools to scaffold and update ADR markdown files.

(Industry standard: Parallel Agent) Primary Use Case: Work that can be partitioned into independent sub-tasks running concurrently across multiple agents. Parallel multi-agent execution pattern. Use when: work can be partitioned into independent tasks that N agents can execute simultaneously across worktrees. Includes routing (sequential vs parallel), merge verification, and correction loops.

Provides sandboxing validation, HMAC key rotation, and budget verification to manage security boundaries under Agentic Group Theory (AGT).

Antigravity (`agy`) CLI sub-agent system for frontier Google Gemini models. Use when dispatching tasks to Gemini 3.5 Flash and above via the `agy` binary. For cheaper/older Gemini models (gemini-3-flash-preview, gemini-3.1-pro-preview), use gemini-cli-agent instead. Trigger with "use agy", "dispatch to antigravity", "run with agy", "use frontier gemini model", or "agy sub-agent".

Systematically analyze agent plugins and skills to extract design patterns, architectural decisions, and reusable techniques. Trigger with "analyze this plugin", "mine patterns from", "review plugin structure", "extract learnings from", "what patterns does this plugin use", "check if this plugin is well-structured", "validate plugin compliance", or when examining any plugin or skill collection to understand its design. Use this skill even when the user just says "look at this plugin" or "tell me how this is structured."

Interactive skill to scaffold and optimize the .agents/ directory for any project mapping up Antigravity configuration. Sets up .gemini/GEMINI.md, skills/, prompts/, and config.json using best practices. Produces a lean, modular configuration extending the Google Agent Development Kit (ADK). Trigger with "set up antigravity", "scaffold .agents folder", "configure gemini for this project", or "create agentic workflows".

Triggers the L5 Red Team Sub-Agent to rigorously audit a plugin against the 39-point L4 pattern matrix.

This skill should be used when the user asks to "audit a plugin", "validate my plugin", "check plugin structure", "verify plugin is correct", "validate .claude-plugin/plugin.json", "check if my plugin is compliant", "review plugin components", or mentions plugin validation or structure compliance. Also trigger proactively after the user creates or modifies any plugin component (commands, agents, skills, hooks, .claude-plugin/plugin.json). Use this skill even when the user says "check my work" or "make sure this is right" in a plugin context. Do NOT use this for auditing individual skills only (use skill-reviewer for that).

Captures and refines business requirements, including functional requirements, non-functional requirements, business rules, constraints, assumptions, and success measures. Produces structured BRD-style documents with [CONFIRMED] and [UNCONFIRMED] confidence markers. Trigger with "capture requirements", "generate a BRD", "document business rules", "list the constraints", or "create a requirements document".

Generate Mermaid flowcharts documenting business processes, state machines, and workflow logic from session captures. Use when you need to map multi-step processes, approval flows, user journeys, or decision trees during exploration. Trigger with "map this workflow", "create a process diagram", "flowchart the business process", "document this workflow", or "visualize the state machine".

Claude CLI sub-agent system for persona-based analysis. Use when piping large contexts to Anthropic models for security audits, architecture reviews, QA analysis, or any specialized analysis requiring a fresh model context.

Interactive skill to scaffold and optimize the .claude/ directory for any project. Sets up CLAUDE.md, .claude/rules/, .claude/settings.json with best practices, and optional hooks. Produces a lean, modular configuration that avoids monolithic context bloat. Trigger with "set up claude", "optimize my CLAUDE.md", "scaffold .claude folder", "configure claude for this project", or "create claude settings".

Coding conventions enforcement agent. Auto-invoked when writing new code, reviewing code quality, adding headers, or checking documentation compliance across Python, TypeScript/JavaScript, and C#/.NET.

Activate when the user wants to compile an APM package into top-level context documents such as AGENTS.md, CLAUDE.md, or GEMINI.md, especially for Codex, Gemini, OpenCode, or agents-protocol style hosts. Do not use when the user only needs per-skill installation; use install-apm-package instead.

Interactively creates technical bundles of code, design, and documentation for external review or context sharing. It conducts a brief discovery phase to confirm the targets and format, presents a plan, and then packages multiple project files into a single Markdown file or a portable `.zip` archive.

Translate .mmd diagram files into PNG images with configurable resolution (retina/HQ/scale), supporting rasterization (raster, rasterize, rasterization). V2 includes L5 Delegated Constraint Verification via verify_png for strict binary linting and Puppeteer-based rendering.

Activate when the user wants to add APM governance, lockfile/audit readiness, or multi-runtime package management to an existing Claude/Copilot/agent plugin, or explicitly convert a plugin into an APM-native package.

Copilot CLI sub-agent system for dispatching tasks and persona-based analysis to GitHub Copilot models. Use for task delegation (agent reads/writes files directly), security audits, architecture reviews, or any work requiring a fresh model context.

Scaffold a GitHub agentic workflow from an existing skill