
Claude Skills by Kastalien-Research
github.com/Kastalien-ResearchManage the assumption registry — track, verify, and query assumptions about external dependencies and system behavior. Prevents costly rediscovery of known failures.
Capture significant learnings from the current work session. Structures insights for future sessions and updates agent memory.
Comprehensive prompt engineering reference for Claude Opus 4.6. Use this skill whenever you are writing, reviewing, or optimizing prompts for Claude Opus 4.6 (or Sonnet 4.6 / Haiku 4.5). Covers foundational clarity principles, output formatting control, tool use, adaptive thinking, agentic system design, multi-context-window workflows, and migration guidance from earlier models. Trigger this skill for any task involving system prompt authorship, agent harness design, multi-step pipeline const...
Write or improve prompts for Claude using Anthropic's official best practices. Creates system prompts, agent prompts, tool descriptions, and MCP resource templates. Pass an existing prompt to improve it, or describe what you need to create one from scratch.
Guide for designing, implementing, and advising on MCP servers that use Code Mode — the pattern where an LLM writes and executes code to orchestrate API calls instead of calling individual tools one at a time. Use this skill whenever the user mentions Code Mode, MCP tool proliferation, context window bloat from MCP tools, programmatic tool calling, LLM code execution in MCP, building a Code Mode server, or wants to compress a large API into a small MCP surface. Also use when the user asks how...
Deploy a multi-agent team that coordinates through Thoughtbox Hub.
Generate architecture diagrams for a codebase subsystem or module. Explores source files and produces Mermaid diagrams in docs/.
Extract reusable principles and decision frameworks from accumulated experience. Use after significant work sessions, project milestones, or when you notice recurring patterns worth codifying.
Effect-TS expert — write, debug, refactor, and explain code using the Effect ecosystem (effect, @effect/platform, @effect/rpc, @effect/cli, @effect/schema, @effect/cluster). Use this skill whenever the user works with Effect-TS code, mentions Effect services/layers/fibers/streams/schedules, asks about Effect error handling or dependency injection, wants to migrate code to Effect, or asks questions like 'how do I do X in Effect'. Also trigger when you see Effect imports in code being discussed...
Format a structured escalation to the human decision-maker (Chief Agentic). Use when hitting an escalation threshold.
View and manage the evaluation harness — session metrics, baselines, trend analysis, and regression detection. The feedback loop that tells the system whether improvements actually improved things.
Run parallel experiments across git worktrees. Define competing approaches to the same problem, dispatch sub-agents to implement each in isolation, then compare results. Use when you have 2-5 alternatives and want to test all of them before committing to one.
Hypothesis-Driven Development — treat ADRs as the source of truth, not code. Form testable hypotheses, stage ADRs, implement to test them, validate against predictions, then accept or reject based on evidence. Prevents repeated mistakes by documenting failures. Enables agent-to-agent collaboration through explicit architectural reasoning. This is the canonical HDD entry point — it replaces the thin router at .claude/commands/hdd/hdd.md.
Run an Agent-Native Architecture Audit using Thoughtbox Hub for multi-agent coordination. Spawns 3 auditor agents and 1 synthesizer that collaborate through structured channels, cross-reference findings, and build consensus on scores.
Orchestrate a multi-agent collaboration demo on the Thoughtbox Hub. Spawns MANAGER, ARCHITECT, and DEBUGGER agents that coordinate through shared workspaces, problems, proposals, and channels.
Implement a specification using a TDD-oriented workflow. Extracts requirements, generates tests first, then implements to pass the tests. Includes spiral detection and acceptance gates.
Unified cross-store knowledge query. Searches MEMORY.md, Thoughtbox knowledge graph, git history, and assumption registry in parallel, returning results with provenance.
View the unified loop controller state — which loops are active, what phase they're in, recent cross-loop knowledge flow, and pending actions.
Govern ADR-022 MCP peer notebook implementation units. Use before or during durable control-plane, manifest lifecycle, web app inspection, runtime provider, or isolation/policy hardening work to prevent mock substitution, scope drift, and incomplete acceptance evidence.
Execute a research task using compositional workflow planning. Characterizes the task, selects an approach from a library of research strategies, executes it, and self-evaluates output quality.
Generate a structured session summary for cross-session continuity. Captures key decisions, hypotheses, partial work, and knowledge references. Output is written to .claude/session-handoff.json for the next session to load automatically.
Generate a status report across all workstreams using git history and GitHub issues. Shows active work, recent changes, and open PRs.
Manage Supabase local and hosted infrastructure. Migrations, schema diff, status, reset, push, and inspection. Wraps the Supabase CLI with project-specific context and gotcha avoidance.
Fuse insights from multiple knowledge sources (code, docs, memory, research, web) into coherent understanding. Use when you have scattered information that needs integration.
Run a taste evaluation on a research proposal or technical direction. Determines whether to proceed, simplify, defer, or kill before committing research effort.
Orchestrate an Agent Teams session with Thoughtbox as the reasoning substrate
Run behavioral smoke tests against the live Thoughtbox Code Mode MCP server. Verifies the public `/mcp` surface (`thoughtbox_search` + `thoughtbox_execute`) plus the main execution paths behind it.
Thoughtbox-first Theseus workflow for behavior-preserving refactors. Use this when structure changes but behavior must stay fixed and scope drift needs hard boundaries.
Trigger when debugging something unexpected — a test failure, surprising behavior, production incident, or any situation where initial attempts aren't working. Prevents the common agent failure mode of trying random things when stuck. Use when "the first fix didn't work", "this is behaving unexpectedly", "I'm stuck", "why is this happening", or after 2+ failed attempts to fix something.
Structure decisions with parallel hypothesis exploration and knowledge graph persistence. Triggers on: "decide", "choose between", "which approach", "compare options", "evaluate alternatives", "tradeoff analysis".
A-Mem thought evolution — check which prior thoughts should be updated when a significant new insight arrives. Spawns a lightweight subagent to classify prior thoughts as UPDATE or NO_UPDATE, then applies revisions. Use during long reasoning sessions when you reach a synthesis, make a decision, or discover something that changes earlier assumptions. Triggers on "this changes what I thought earlier", "update prior reasoning", "evolve thoughts", or automatically on conclusion/synthesis thoughts...
Cross-session knowledge retrieval from the Thoughtbox knowledge graph. Searches entities, traverses relations, retrieves observations, and synthesizes findings from past sessions. Use when you need to recall prior decisions, check what's already known about a topic, find related insights, or build on past work. Triggers on "what do we know about", "have we seen this before", "recall", "prior decisions about", "knowledge graph", or when starting work that might have prior context.
Gateway orientation for agents using Thoughtbox MCP for the first time. Use this skill when you connect to a Thoughtbox MCP server and need to understand what's available, how to structure reasoning sessions, or how to use the tb SDK. Also use when you're unsure which Thoughtbox operation to use for a task, or when you want to check what modules and patterns are available. Triggers on first Thoughtbox interaction, "how do I use Thoughtbox", "what can Thoughtbox do", or any confusion about Tho...
Friction-gated refactoring using the Theseus protocol. Prevents scope creep and refactoring fugue state by enforcing file scope boundaries, visa-based expansion, checkpoint audits, and a brittleness counter. Use when refactoring code, restructuring modules, renaming across files, or any task where "structure changes but behavior must stay the same". Triggers on "refactor", "restructure", "rename across", "extract module", "move code", or when a change touches 3+ files without adding features.
Structured research using Thoughtbox IRCoT (Interleaved Retrieval and Chain-of-Thought). Triggers on: "research", "investigate", "explore", "literature review", "what do we know about".
Analyze completed Thoughtbox sessions to extract patterns, anti-patterns, and learnings for the knowledge graph. This is the learning loop that makes Thoughtbox improve over time. Use after completing a reasoning session, when reviewing past sessions for insights, or when you want to assess reasoning quality. Triggers on "review session", "what did I learn", "extract insights", "analyze reasoning", "session retrospective", or proactively after any significant session completes.
Spawn an Agent Team with a background Thoughtbox analyst teammate. The analyst monitors your reasoning sessions for evolution candidates, contradictions, and generates periodic digests. Use this at the start of any deep Thoughtbox reasoning session, when you're about to record many thoughts and want background analysis. Triggers on "start thoughtbox team", "I want a session analyst", "monitor my reasoning", or at the start of any session where you plan to use Thoughtbox extensively.
Start a Unified Loop Controller session via Ralph Wiggum. Autonomously works through backlog, dispatches agents, and explores via QD when idle.
Thoughtbox-first Ulysses workflow for surprise-gated debugging. Use this when debugging gets uncertain and you need explicit plan, outcome, and reflection discipline without relying on local shell state.
This skill should be used before implementing features, building components, or making changes. It guides exploring user intent, approaches, and design decisions before planning. Triggers on "let's brainstorm", "help me think through", "what should we build", "explore approaches", ambiguous feature requests, or when the user's request has multiple valid interpretations that need clarification.
Evaluate whether an idea is worth implementing by asking structured questions about outcomes, alignment, and opportunity cost. Stage 1 of the development workflow.
Finalize the workflow by reflecting on the process, moving ADRs, closing issues, and preparing for merge. Stage 8 of the development workflow.
Iterate on implementation fixes surfaced by review until all claims are verified. Stage 6 of the development workflow.
Execute an implementation by dispatching multiple sub-agents to parallel Git worktrees. Each builds the entire feature independently, and the best implementation is selected and merged.
Orchestrate the full development lifecycle from ideation through merge. Sequences 8 stages with gates, dispatches to stage skills, and maintains workflow state.
Capture learnings from the workflow into reusable documentation. Stage 7 of the development workflow.
Transform spec and ADR into an implementation plan with task decomposition and sub-agent assignment. Stage 3 of the development workflow.
Verify implementation claims by dispatching review agents. Stage 5 of the development workflow.
Execute the implementation plan by dispatching sub-agents for each task. Stage 4 of the development workflow.
Use this skill before implementing features, lifecycle changes, runtime boundaries, persistence contracts, or architectural work where the codebase may already contain canonical domain models. It prevents duplicate abstractions, illegal representable states, and plans built on the wrong source of truth.