LLM Mart Basic
@llm-mart · Joined Jun 2026
Apply whenever writing or updating a project-facing document — root CLAUDE.md, `.hedgehog/core-design.md`, specs, READMEs, or similar. Ensures the file reads as a clean, current, as-is snapshot rather than a log of edits or decisions. Applies on first generation and on every late
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
Facilitate a brainstorming session using diverse creative techniques. Use when the user says 'help me brainstorm' or 'help me ideate'.
Decision-grade research, three ways: draft a deep-research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), process a finished research report — file it, distill a succinct cited summary with metadata that downstream skills consume without repr
Pressure-test an idea through persona-driven interrogation until it hardens, proves out, or dies cheaply. Use when the user says 'forge an idea', 'pressure-test this idea', 'stress-test my thinking', or 'harden this idea'.
Create, update, or validate a PRD. Use when the user wants help producing, editing, or validating a PRD.
Working Backwards PRFAQ challenge that stress-tests a product concept customer-first. Use when the user requests to 'create a PRFAQ', 'work backwards', or 'run the PRFAQ challenge'.
Create, update, or validate a product brief. Use when the user wants help producing, editing, or validating a brief.
Plan UX patterns and design specifications. Use when the user says "lets create UX design" or "create UX specifications" or "help me plan the UX"
Maintainer-only. Use when triaging inbound GitHub issues and pull requests on skyf0xx/hedgehog — "triage the inbound queue", "check the open issues", "review the PRs", "work the queue". Reads every item read-only, judges it for security and for merit, then fixes and closes or com
Use once per invocation, at the start of a new Hedgehog project, to land the workspace for whichever core `planner` selected at Phase 0 — the first real workspace this project gets, since `init` with no explicit core flag lands the shared agents/skills/build-graph payload and lea
Use for planning intake (core selection, then scope boundary + domain vocabulary or Chain Method brief, depending on core) at the start of a project, and for re-entry when new scope enters play on a project already built or mid-build — including after a build has reached its Stop
Use at a phase or layer transition the core's own loop skill defines, or when the Correction Protocol is invoked. Also use when the user asks for a review, audit, or "look over this". Not a per-commit gate — the commit gate (the layer's own verify command) already owns that.
Use once a core's build is complete (every task in the build graph `complete`) and the user is offered a fresh-context session to iterate. Takes post-build tweak requests one at a time from a clean context, and — separately — reviews accumulated build friction and asks the user d
Imported from skyf0xx/hedgehog/vendor-skills/BMAD/bmm-skills/plan/bmad-prfaq/agents/artifact-analyzer.md.
Imported from skyf0xx/hedgehog/vendor-skills/BMAD/bmm-skills/plan/bmad-prfaq/agents/web-researcher.md.
Review AI-generated or human-written code changes with fallow's graph-grounded review brief. Subtracts deterministic concerns (unused code, complexity, duplication, styling) from the loop, ranks what to look at by blast radius and risk, and surfaces the few consequential structur
Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when agents need to read attached Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, or text-based PDF files without uploading them to a hosted parser.
Add Atomic Chat MCP server so the container agent can call local models served by the Atomic Chat desktop app via its OpenAI-compatible API.
Add clidash — a zero-dependency, read-only web dashboard that derives its tabs and tables at runtime from any CLI that lists resources as JSON. Ships pre-wired for NanoClaw's ncl CLI (agent groups, sessions, channels, users, roles), plus message-activity charts, a log tail, and a
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.
Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.
Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.
Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.
Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.
A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.
Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.
Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.
AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.
AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.
A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.
One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.
"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.
A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.
The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.
Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.
Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.
/ia-ideate
ia-ideate
Generate ranked improvement ideas by scanning the codebase, divergent ideation, adversarial critique, and impact ranking
/ia-lfg
ia-lfg
Full autonomous engineering workflow (plan, build, review, ship)
/ia-plan
ia-plan
Transform feature descriptions into well-structured project plans following conventions
/ia-report-bug
ia-report-bug
Report a bug in the whetstone plugin
/ia-reproduce-bug
ia-reproduce-bug
Reproduce a GitHub issue bug with visual evidence (browser screenshots, log analysis). Takes a GitHub issue number. For non-issue bug validation, use the bug-reproduction-validator agent.
/ia-resolve-pr
ia-resolve-pr
Resolve PR review comments with cluster analysis and parallel agents. Use when bulk-fixing PR comments after triage.
/ia-review
ia-review
Perform exhaustive code reviews using multi-agent analysis, ultra-thinking, and worktrees
/ia-setup
ia-setup
Diagnose the whetstone environment and configure review agents. Checks CLI dependencies and plugin version, then runs the review-agent wizard that writes whetstone.local.md. Use when onboarding a project, troubleshooting missing tools, or configuring review agents.
/ia-test-browser
ia-test-browser
Run browser tests on pages affected by current PR or branch
/ia-verify
ia-verify
Run pre-PR verification chain: build, types, lint, tests, security scan, diff review
/ia-work
ia-work
Execute work plans efficiently while maintaining quality and finishing features
/memory-compact
Memory compact
Run a dry run first:
/memory-forget
Memory forget
Run:
/memory-status
Memory status
Run:
/skill-creator
Skill creator
Create or update an OpenCode skill using the bundled skill-creator workflow
/skill-registry
Skill registry
Rebuild the OpenCode skill registry for the current project and installed skills
/agentation-fix
agentation-fix
Session-2 fix loop for Agentation — read structured annotations from the dev overlay and apply targeted UI fixes.
/apply-design-md
apply-design-md
Consume the project's design contract — a .design file or DESIGN.md — and thread its tokens through UI code (CSS, Tailwind, or design-system components).
/fork-pov
fork-pov
Fork pov.md for installer taste, or append a one-liner to gotchas.md after a real agent failure.
/motion-audit
motion-audit
Audit animation timing, easing, springs, and transitions — decide first whether motion should exist, then apply the motion cluster.
Make any song you can imagine
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