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mattpocock
ask-matt

Ask which skill or flow fits your situation. A router over the skills in this repo.

Overview

Publishermattpocock
Repositoryskills
Skill nameask-matt
Stars
264.4K
Forks
22.3K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mattpocock on GitHub. Read the source before you install it.

Installation

Install the Ask Matt AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mattpocock/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/engineering/ask-matt .claude/skills/ask-matt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ask Matt in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ask Matt on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ask Matt is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Ask Matt

You don't remember every skill, so ask.

A flow is a path through the skills. Most paths run along one main flow, and two on-ramps merge onto it. Everything else is standalone, or a vocabulary layer that runs underneath.

The main flow: idea → ship

The route most work travels. You have an idea and want it built.

  1. /grill-with-docs sharpens the idea by interview. Start here whenever you are working in a working directory: it's stateful, retaining what it learns in CONTEXT.md and ADRs. (No working directory? Use /grill-me instead, covered under Standalone. Both run the same /grilling primitive; grill-with-docs is the one that leaves a paper trail, which makes it the better of the two whenever a repo is there to leave it in.)

  2. Branch: can you settle every question in conversation? If a question needs a runnable answer (state, business logic, a UI you have to see), detour through a prototype, bridged by /handoff in both directions (a prototype lives in its own directory, which is exactly what /handoff is for; see Phase boundaries):

    • /handoff out, then open a fresh session against that file,
    • /prototype to answer the question with throwaway code,
    • /handoff back what you learned, and reference it from the original idea thread.
  3. Branch: is this a multi-session build?

    • Yes/to-spec (turn the thread into a spec), then /to-tickets to split it into tracer-bullet tickets, each declaring its blocking edges. On a local tracker that's one file per ticket under .scratch/<feature>/issues/, worked blockers-first by hand; on a real tracker the edges become native blocking links, so any ticket whose blockers are done can be grabbed: kick off /implement per ticket, /clearing context between each one. Each ticket is self-contained, so the last one's context is disposable.
    • No/implement right here, in the same context window.

    Either way, /implement builds each issue by driving /tdd internally (one red-green slice at a time), then closes out by running /code-review, a two-axis review (Standards + Spec) of the diff, before committing. Reach for /tdd on its own when you just want to build a concrete behaviour test-first without a full spec, and /code-review on its own whenever you want to review a branch or PR against a fixed point.

Context hygiene

Keep steps 1–3 in one unbroken context window (don't compact or clear until after /to-tickets) so the grilling, spec, and tickets all build on the same thinking. Each /implement then starts fresh, working from the ticket.

The limit on this is the smart zone: the window (~150k tokens on state-of-the-art models) within which the model still reasons sharply. If a session approaches it before /to-tickets, don't push on degraded; /compact at the nearest phase boundary and carry on (see Phase boundaries).

On-ramps

A starting situation that generates work, then merges onto the main flow.

  • Bugs and requests piling up/triage. It moves issues through triage roles and produces agent-ready issues, which /implement later picks up.

    Triage is only for issues you didn't create: bug reports, incoming feature requests, anything that arrives raw. Tickets that /to-tickets produced are already agent-ready, so don't triage them.

  • Something's broken/diagnosing-bugs. For the hard ones: the bug that resists a first glance, the intermittent flake, the regression that crept in between two known-good states. It refuses to theorise until it has a tight feedback loop (one command that already goes red on this bug), then fixes with a regression test. Its post-mortem hands off to /improve-codebase-architecture when the real finding is that there's no good seam to lock the bug down.

  • A huge, foggy effort: a greenfield project or a huge feature build, too big for one session/wayfinder, the most cognitively demanding flow here. When the way from here to the destination isn't visible yet, it charts a shared map of decision tickets on the issue tracker and resolves them one at a time, producing decisions, not deliverables, until the fog is pushed back and the way is clear. Where /grill-with-docs sharpens an idea you can hold in one session, wayfinder is for the idea you can't, and it's slower and denser, so save it for exactly that, never a well-scoped feature.

    When the map clears, it hands off, it doesn't build: merge onto the main flow at /to-spec, which collapses the map's linked decisions into a buildable plan, then /to-tickets and /implement as usual. Looping the map straight into /implement skips that collapse and throws the linked detail away, so go straight to /implement only when the effort turned out genuinely small.

Codebase health

Not feature work, just upkeep.

  • /improve-codebase-architecture runs whenever you have a spare moment to keep the codebase good for agents to operate in. It surfaces deepening opportunities; picking one generates an idea you can take into the main flow at /grill-with-docs. It's the survey that finds the candidates; /codebase-design (below) is the bench you design the chosen one on.

Vocabulary underneath

Two model-invoked references that run beneath the other skills, each the single source of truth for its vocabulary. Reach for them directly when the words, not the process, are the problem; or let the skills above pull them in.

  • /domain-modeling: sharpen the project's domain language: challenge a fuzzy term, resolve an overloaded word ("account" doing three jobs), record a hard-to-reverse decision as an ADR. It's the active discipline /grill-with-docs drives to keep CONTEXT.md a clean glossary.
  • /codebase-design is the deep-module vocabulary (module, interface, depth, seam, adapter, leverage, locality) for designing a module's shape: a lot of behaviour behind a small interface at a clean seam. /tdd and /improve-codebase-architecture both speak it.

Phase boundaries

A phase is a chunk of work inside a session: the grilling, the implementation, the QA. At the boundary between two of them you have five options, and picking between them is the fuzziest decision in this whole map:

  • Continue: stay put. Costs nothing, loses nothing.
  • /clear: empty the window, when nothing here matters to what's next.
  • /handoff writes a portable markdown file. Narrow: only for a new harness, a new directory, a colleague, or forking a side task mid-phase. What it buys is portability.
  • Subagent: send a tightly-scoped task to its own window and get a report back.
  • /compact compresses this context and seeds a fresh session with it. The default, at the bottom of the tree rather than the first reach.

Read PHASE-BOUNDARIES.md for the ordered tree: the five questions, the reasoning behind each branch, and why the primary-source cost makes Continue the one to rule out first. Make the decision at a boundary; mid-phase, continue or split the rest into subagents.

Standalone

Off the main flow entirely.

  • /grill-me: the same relentless interview as /grill-with-docs, but stateless: it saves nothing locally and builds no CONTEXT.md. Reach for it when you are not working in a working directory (sharpening a plan, a design, a piece of writing, anything with no repo under it). If you are in a working directory, use /grill-with-docs instead: it runs the same interview and leaves a paper trail, so it is strictly the better one.
  • /grilling is the interview primitive itself: rounds, the frontier, facts are the agent's job and decisions are yours. /grill-me and /grill-with-docs are the two named ways in, and /triage, /wayfinder and /improve-codebase-architecture all run it internally. Reach for it directly only when you want the interview with no wrapper around it.
  • /resolving-merge-conflicts works an in-progress merge or rebase conflict hunk by hunk, resolving by intent traced to each side's primary source rather than by picking lines, then finishes the operation. It never runs --abort. Standalone and off every flow: reach for it when you are already mid-conflict.
  • /prototype is a small, throwaway program that answers one design question: does this state model feel right, or what should this UI look like. Throwaway is a constraint on how the code is written, not a promise to destroy it: the answer folds into the real code, and the prototype itself is kept as a primary source on a prototype/<name> branch out of main, pointed at from the implementation issue. It's the detour in step 2 of the main flow, but reach for it any time a design question is hard to settle on paper.
  • /research: delegate reading legwork to a background agent: it investigates a question against primary sources, then leaves a cited Markdown file in the repo. Keep working while it reads. The file it produces is something to take into the main flow at /grill-with-docs, since research feeds the thinking rather than replacing it.
  • /to-questionnaire comes in when the thing blocking you isn't in your head or the codebase but in someone else's, and it writes them a questionnaire to fill in. It's the inverse of /grill-me: instead of interviewing you about the subject, it interviews you about the send (who it's going to, what you need back) and aims the questions at the gap. What comes back is material for /grill-with-docs or /to-spec.
  • /wizard is for the steps only a human can take: provisioning infrastructure, setting up credentials or CI secrets, clicking through an unfamiliar third-party dashboard, running a one-off migration or cutover. It generates an interactive bash script that opens each URL, captures each value, and writes it into .env and GitHub secrets, so the procedure stops being something you re-explain to an agent every time. Model-invoked, so the agent reaches for it the moment it hits a wall only you can pass. If the agent could just do it itself, it should; this is for where a human is genuinely in the loop.
  • /wait-what is the corrective for a message that didn't land. Use it mid-conversation, inside any other skill, and the agent re-pitches what it just said with the context you were missing, in plain English, using the CONTEXT.md vocabulary. It works after the fact; /grill-with-docs is the upfront cure, because a shared language agreed early is what stops the jargon arriving at all.
  • /teach: learn a concept over multiple sessions, using the current directory as a stateful workspace.
  • /writing-for-agents is the reference for writing documents agents consume: skills, AGENTS.md, pointed-at docs.

Precondition

/setup-matt-pocock-skills: run before your first engineering flow to configure the issue tracker, triage labels, and doc layout the other skills assume. Custom issue trackers also work.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ask Matt AI skill do?

Ask which skill or flow fits your situation. A router over the skills in this repo.

Why use Ask Matt on TypingMind?

Because you install it once and use it with any model. Ask Matt is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ask Matt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattpocock/skills/tree/main/skills/engineering/ask-matt. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ask Matt?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ask Matt?

As many as you like. As long as a model supports skills, you can use Ask Matt with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ask Matt AI skill free?

Yes. It is published on GitHub by mattpocock under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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