LLM Mart Basic
@llm-mart · Joined Jun 2026
Use when a user says "minimize this ty ecosystem change", "reproduce this ecosystem result", "investigate a primer difference", "investigate a mypy_primer difference", "investigate a mypy-primer difference", or asks to reproduce, investigate, or minimize behavior changes in ty ec
Use when a user says "summarise ecosystem results", "summarize this ty ecosystem report", "what changed in this ecosystem run?", or asks to summarise or summarize ty ecosystem results for a Ruff PR from a PR number, PR URL, GitHub ecosystem-results comment, or detailed HTML repor
Add or review RustFS `tracing` events with the repository field shape, level policy, privacy boundaries, and guardrails. Use when a change adds or edits a tracing macro/instrumentation site or the logging guardrail script.
Finds or publishes a pkg.pr.new canary release for a Storybook branch. Use when the user wants the canary package specifier for a branch or needs to trigger the canary workflow manually.
Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.
Debug Streamlit frontend and backend changes using make debug with hot-reload. Use when testing code changes, investigating bugs, checking UI behavior, or needing screenshots of the running app.
Maps the `hunkdiff/extension` authoring surface for Hunk, the terminal diff viewer — hiding or reordering reviewed files, docked panes, alternate file views, commands and key bindings, dialogs, workspace writes, themes, syntax languages, VCS backends, lifecycle events. Use when w
Interacts with live Hunk diff review sessions via CLI. Inspects review focus, navigates files, hunks, and exact lines, reloads session contents, adds inline review comments, and paints attention marks on character ranges. Use when the user has a Hunk session running or wants to r
AI-generated documentation for GitHub repositories
Creates and removes isolated Git worktrees under a consistent repository sibling directory. Use when starting feature or fix work in a dedicated worktree, or cleaning up a finished worktree.
Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed URLs. Use when asked to "make this agent-ready", "improve Agent Score", "fix llms.
Creates and improves portable Agent Skills with a validator, routing scenarios, and evidence-based keep, cut, merge, or retire decisions. Use when asked to "write a skill", "update all skills", "audit my SKILL.md", "remove redundant instructions", or fix skill triggering. For AGE
Runs a changesets npm release through the version PR, CI publish, and registry verification. Use when asked to "release this package", "autoship", "merge Version Packages", or diagnose a release that did not publish. For feature PRs use pr-creator or pr-babysitter.
Audits agentic products for tool parity, authority, approval payloads, recovery, and trust using 27 rules and a ship verdict. Use when asked for an "AX audit", to review an agent approval flow, or whether an agent can operate the product. For human-facing API ergonomics use dx-au
Recovers decisions, previous fixes, research, and subsequent actions from past AI conversations. Use when asked to "search past chats", "we fixed this before", "what followed this prompt", "why did the plan change", or use Claude Code Search for historical context. Supports local
Designs module contracts, deepens existing boundaries, and installs enforceable repository guardrails. Use when asked to "design the architecture", "simplify our modules", or "harden the repo". For one feature plan use planning; for diff cleanup use tidy; for tenancy use multi-te
Applies the house explanation style: concrete terms, optional analogy, no minimizers or promotional vocabulary, and verbatim technical identifiers. Use when asked for "ELI5", "plain English", "re-pitch that", or "stop using jargon". For product copy use copywriting; for documenta
Designs tenant isolation, hostname routing, custom-domain lifecycle, and plan limits on Cloudflare or Vercel. Use when asked to "isolate tenant data", "support custom domains", "build a white-label platform", or assess PSL registration. For general module structure use codebase-a
Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria. Use when asked to "plan this feature", "stress-test this plan", "grill me", or "split this into tickets". For architecture use
Monitors or repairs an open GitHub PR: CI failures, conflicts, review threads, and merge readiness, reporting state changes. Use when asked to "watch this PR", "fix CI", "resolve conflicts", or "address review comments". For PR metadata use pr-creator; for npm release PRs use aut
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.
A green PR, a controller reporting success, and not one line of the new code running
/close-out
Close out
Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/audit-infra
Audit infra
Audit infra security: secrets, deps, CI/CD, webhooks, AI/skill files
/audit-solana
Audit solana
Audit Solana program code for exploitable bugs and write a findings report
/benchmark
Benchmark
Compare per-instruction CU with the stored baseline to catch regressions
/build-app
Build app
Build the web client (Next.js, Vite, React) and check env, types and bundle
/build-program
Build program
Build Solana programs (Anchor, Pinocchio, native), incl. verifiable builds
/build-unity
Build unity
Build the Unity project in batchmode for WebGL, desktop, Android or PSG1
/cleanup
Cleanup
Turn a solana-ai-kit fork into a project: set up CLAUDE.md, remove kit files
/commit-claude-config
Commit claude config
Un-ignore and commit the kit config dir, instruction file, .mcp.json and .gitmodules
/debug-user-tx
Debug user tx
Replay a user's failing transaction on forked state and map the error to source
/deploy
Deploy
Deploy a program to devnet, or to mainnet after the user's explicit go-ahead
/diff-review
Diff review
Review the branch diff for Solana security issues, CU waste and AI slop
/doctor
Doctor
Read-only check of toolchain and kit config, with one fix-it command per failure
/dream
Dream
Consolidate MEMORY.md and Project Learnings: dedupe, resolve conflicts, prune
/explain-code
Explain code
Explain Solana code with a diagram and a step-by-step walkthrough
Make any song you can imagine
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