Agent skill

Project Brain

by mendixlabs in mendixlabs/mxcli

Project-specific knowledge mxcli cannot compute — the requirements and slices being built from (a spec, a prototype, a conversation), why a pattern was chosen here, what is still undecided, which…

Apache-2.0Auto-check passedDevelopment

Install Project Brain

skills CLI
$ npx skills add mendixlabs/mxcli --skill project-brain -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mendixlabs/mxcli project-brain --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mendixlabs/mxcli.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/mendix/project-brain .claude/skills/project-brain && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
project-brain
GitHub stars
128
Token cost
~4.9k tokens
SKILL.md length
2,688 words
Files
1
Skills in repo
75
Repo updated
First seen
Licence
Apache-2.0

At a glance

Project-specific knowledge mxcli cannot compute — the requirements and slices being built from (a spec, a prototype, a conversation), why a pattern was chosen here, what is still undecided, which…

  • Works in 2 steps: You have had to correct the same thing… → You chose between real alternatives and…
  • Starting from requirements that live outside git
  • SKILL.md covers The rule that makes it work, Reading it, Writing to it and Recording requirements and…, plus 10 more sections
  • Calls jq

What it does

Project Brain is an agent skill from mendixlabs/mxcli. Project-specific knowledge mxcli cannot compute — the requirements and slices being built from (a spec, a prototype, a conversation), why a pattern was chosen here, what is still undecided, which marketplace version broke what. Use when starting from requirements that live outside git, before designing something that looks like it was decided before, when you have had to correct the same thing twice, and when an mxbuild error is resolved by something non-obvious.

Its SKILL.md is about 4.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. It works with Git. The repository describes itself as: Mendix cli tool, a headless way to work with Mendix projects. Enables Mendix projects for use with 3rd party agentic coding tools like Claude Code and Copilot. Includes a… The licence is Apache-2.0.

When your agent uses it

  • Starting from requirements that live outside git
  • Before designing something that looks like it was decided before
  • You have had to correct the same thing twice
  • When an mxbuild error is resolved by something non-obvious

Example prompts

  • “/project-brain”

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. You have had to correct the same thing twice. The second correction is
  2. You chose between real alternatives and the losing one would look

What it can do on your machine

Read from SKILL.md and the folder at commit a924d11. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Project Brain loads about 4.9k tokens when it runs. Until then it costs about 120 tokens; SKILL.md has 2,688 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~4.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mendixlabs/mxcli at commit a924d11, republished under its Apache-2.0 licence (© mendixlabs). 2,688 words, ~4,853 tokens.

Download SKILL.mdSave it as .claude/skills/project-brain/SKILL.md (or your agent's skills folder).
name
project-brain
description
Project-specific knowledge mxcli cannot compute — the requirements and slices being built from (a spec, a prototype, a conversation), why a pattern was chosen here, what is still undecided, which marketplace version broke what. Use when starting from requirements that live outside git, before designing something that looks like it was decided before, when you have had to correct the same thing twice, and when an mxbuild error is resolved by something non-obvious.

Project brain

The brain holds what mxcli cannot compute about this project. Two halves:

  • Decisions — why a pattern was chosen here, which marketplace version broke what, what a recurring mxbuild error means in this app.
  • Open questions — what is not decided yet, so it is not silently forgotten and rediscovered expensively later.
  • The plan — the requirements being built from and the slices they are grouped into, when the source is a specification document, a prototype or a conversation rather than GitHub issues.

The plan half matters because hours of work can otherwise leave no trace: a Word document and a chat transcript are not in git, so a session that resumes later has no idea what it was building towards, and neither does the next person.

It lives in docs/brain/, is committed, and is reviewed in a pull request like any other change.

The rule that makes it work

Anything mxcli can answer does not belong here. Entities, microflows, pages, bindings, references, callers, dead assets — all queryable. A note that transcribes any of them is a note that will disagree with the project the moment someone edits the model, and it will disagree silently.

Before writing anything down, ask whether a command answers it:

bash
mxcli -p app.mpr -c "list entities"
mxcli -p app.mpr -c "list callers of MyModule.ACT_Thing"
mxcli -p app.mpr -c "describe microflow MyModule.ACT_Thing"

If one does, do not record it. Record only the negative space — the reason, the constraint, the history that no query can reach.

Reading it

docs/brain/
  project.md           cross-cutting decisions
  modules/<Module>.md  decisions anchored to one module
  plan/<slice>.md      requirements for one deliverable slice

When building: read project.md, plus the shard for each module you are about to touch. That set is known before the work starts.

When planning, or when picking up work: read the plan. mxcli brain plan first — it says which slices are outstanding — then the shard for the slice you are working on.

Never read the whole directory. A large project has dozens of shards, and reading them all reinstates exactly the context cost the split removed. If you do not know which modules you are touching yet, read project.md and come back.

mxcli brain brief produces that set for you, so the rule above does not depend on judgement:

mxcli brain brief --slice 07-planning     # project + the modules that slice's
                                          # requirements anchor into + its plan
mxcli brain brief --module Sales          # project + Sales, no plan

The modules are derived from the slice's requirement anchors — you do not tell it which modules the slice touches, because that is what you opened the brief to find out. The pack goes to stdout and its size to stderr, so it pipes.

This matters most when each slice runs in its own session or sub-agent: the pack is then re-read from a cold start every slice, and reading the whole store instead is roughly three times the tokens.

Writing to it

An agent captures; a person promotes. Capturing is free and reversible; promotion is the human's call about what is worth committing.

bash
mxcli brain capture "Orders are committed by Finance, not Sales" \
  -a @Sales.Order -a @Finance.ACT_Post -p app.mpr

The first line becomes the entry's title and the rest becomes its body, so a one-argument capture can still carry an explanation:

bash
mxcli brain capture "Marketplace Administration 4.5.0 breaks the login flow
It changes Account's password-policy handling; we pinned 4.3.2 until the
custom login microflow is reworked." -a @Administration.Account -p app.mpr

Then leave it. mxcli lint reminds the developer that something is staged.

Recording requirements and slices

When the source of truth is outside git — a specification document, a prototype, a long conversation — record it as requirements grouped into slices before building. Otherwise the work is invisible: not in an issue, not in a commit message, and gone from the session that resumes tomorrow.

bash
mxcli brain capture "Orders must be approvable by a manager" \
  --slice 02-approvals -a @Sales.ACT_Order_Approve -p app.mpr

--slice is the only signal needed. It files the entry in plan/02-approvals.md and makes it a requirement rather than a decision.

Slices are ordered by name, so a numeric prefix is how a roadmap is sequenced: 01-accounts, 02-approvals, 03-reporting. That is your choice, not something mxcli maintains.

A requirement's anchor points forward

This is the difference that matters, and it is why requirements are not simply more decisions:

Anchor pointsAn anchor that does not resolve means
decisionbackward, at what existsthe decision is stale — check fails
requirementforward, at what is intendednot built yet — normal, check passes

So anchor a requirement at what you are going to build. @Sales.ACT_Order_Approve before that microflow exists is correct, not a mistake.

Never anchor a requirement at a bare module. @Sales resolves the instant the module exists — long before any of the work inside it — so the requirement reports built with nothing done. mxcli brain capture --requirement refuses it and names the alternative, because the failure is silent and flattering: the plan shows progress that has not happened and nothing else disagrees. Anchor at a document the slice actually creates. (Measured on a real project: two requirements anchored at a module both read as built after slice 01.)

A module role is a fine anchor and resolves like any document — a security requirement anchored at the roles it creates is measured correctly. Anchoring at the documents whose access rules the roles govern works too, and says something slightly different; either is legitimate.

A theme has no model element to anchor at (it is files under theme/, which is the point of mxcli theme). Anchor the branding requirement at the branded layout the slice adds — the model-side half of the same work.

Progress is derived, never written
bash
mxcli brain plan -p app.mpr
SLICE           BUILT  PLANNED   UNANCHORED
01-accounts         1        0
02-approvals        0        1            1

1 of 3 requirements built, across 2 slice(s).

A requirement is built when its anchors resolve against the model. Nothing in the file says "done" — building the thing is what moves the number.

Never write a status into a requirement, and never keep a checklist beside it. A hand-maintained status is wrong the moment someone builds something, and nothing will tell you.

A requirement with no anchor is counted separately as unanchored: it cannot be measured. That is a prompt to anchor it once you know what will implement it, not an error.

Slices have a generous cap, and that is the slicing discipline

A slice holds source material, so its budget is much larger than a decision shard's — and it is not loaded every session. But it is still a budget: a slice too long to read is a slice that should be split.

When to capture a decision

Capture is easy to postpone forever, so it needs a trigger rather than good intentions. Two, and the first is the reliable one:

  1. You have had to correct the same thing twice. The second correction is the signal: it will happen a third time to someone else. Capture what the right answer is and why, anchored at whatever you were working on.
  2. You chose between real alternatives and the losing one would look reasonable to the next person. Record the choice and what ruled the other out — a decision without its reason gets re-litigated.

If you are unsure whether something qualifies, capture it. Staging costs nothing and is reversible; a person decides what is worth committing.

Recording what is NOT decided

An open question is a decision that has not been made yet. Record it rather than carrying it in your head — the conversation ends, and the question is expensive to rediscover.

bash
mxcli brain capture "Do approvers see rejected orders?
The spec is silent. Affects the overview page and the access rules." \
  --open -a @Sales.Order -p app.mpr

A question's anchors are not checked. It may name something that does not exist — often the question is precisely whether it should — so the staleness rule that keeps decisions honest does not apply to it.

--open combines with --slice: a question about a slice's scope is filed with that slice, and is counted apart from its requirements. An unanswered question is not outstanding scope, so it never inflates the slice.

Answering it turns it into a decision, in place:

bash
mxcli brain resolve <id> "Yes, for 30 days
Agreed with the product owner; drives the overview filter and the access rule."

The entry keeps its id and its position, and the question survives as the answer's context. From that moment its anchors are checked, like any other decision.

mxcli brain check and mxcli lint both report unanswered questions until someone resolves one. That is deliberate: a question nobody answers is the one kind of entry that gets more expensive the longer it sits.

Write the anchor, not the name

@Sales.Order.Status is what makes an entry routable (its module decides the file) and checkable (mxcli brain check verifies it still resolves). The same fact written as prose — "the Status attribute on the Sales order entity" — is neither.

AnchorNames
@Salesa module
@Sales.Ordera document: entity, microflow, page, workflow, …
@Sales.Order.Statusa member: an attribute

An entry's first anchor decides its shard. An entry with no anchor is cross-cutting and goes to project.md.

An entry may anchor into more than one module — "Sales.Order is committed by Finance.ACT_Post" genuinely spans two — and that is fine as long as one anchor belongs to the shard it is filed in.

Checking it

bash
mxcli brain check -p app.mpr            # every shard
mxcli brain check --changed -p app.mpr  # only shards this branch touched

Two independent things are checked, and only some outcomes are failures:

OutcomeMeaningFails?
resolvedthe anchor names something that is thereno
not foundthe anchor names nothing — the entry is staleyes
not indexablethe target exists but its document type is not in the catalog's indexno
misfiledno anchor belongs to the shard the entry sits inyes

"Not indexable" is not a problem to fix. Treating it as missing would demand edits to entries that are perfectly current.

Misfiling is a separate axis, not a fourth anchor state: every anchor can resolve and the entry still be in the wrong file.

Size

Each shard has a line budget, and promote refuses rather than letting a shard grow past it. project.md is the tightest — it is the only file loaded every session.

bash
mxcli brain show -p app.mpr

Sizes are computed on every run and deliberately not written down anywhere. A figure in prose is stale the next time anyone promotes.

If a promotion is refused, the answer is to condense or drop, not to raise the cap: the cap is what stops the store becoming a file nobody reads.

Show full SKILL.md (1,127 more words)Show less

Commands

CommandDoes
mxcli brain init -p app.mprCreates docs/brain/. Refuses a docs/brain/ it did not write
mxcli brain capture "<text>" [-a @Anchor]…Queues an entry. Never commits
mxcli brain staged [--since <id>] [--slice <n>] [--fail-if-empty]Lists the queue with the shard each entry would land in. --since is the slice boundary — see below
mxcli brain promote <id> [--to <shard>]Writes it into its shard. The human step
mxcli brain drop <id>Removes it from the queue or from its shard
mxcli brain capture "<text>" --slice <name> [-a @Anchor]…Queues a requirement of that slice
mxcli brain capture "<text>" --open [-a @Anchor]…Queues an open question; its anchors are not checked
mxcli brain resolve <id> "<answer>"Answers a question, turning it into a decision in place
mxcli brain plan [--slice <name>]The roadmap: each slice's requirements counted against the model
mxcli brain brief --slice <name> | --module <M>The reading pack: exactly the shards that work needs
mxcli brain check [--changed]Anchors still resolve, entries in the right shard, plus slice progress
mxcli brain show [<shard>]Entries, lines and headroom per shard

Renaming

mxcli rename updates the brain's anchors along with the model's own cross-references, and says how many it touched. You do not have to fix them by hand, and --dry-run previews the brain's share too.

This is done at the rename because it cannot be done afterwards. A decision's anchor points backward, so a stale one is reported NOT FOUND — but a requirement's points forward, so a stale one just counts as PLANNED, which is exactly what a forward anchor failing is supposed to mean. Once the old name is gone there is no way to tell "never built" from "built, then renamed".

If you rename an element some other way — in Studio Pro, or by hand — run mxcli brain check afterwards and expect the plan's counts to have moved.

What not to record

  • Anything show, describe or the catalog answers — it will drift.
  • Counts and sizes of anything, including the brain itself.
  • Status. Whether a requirement is done is computed by mxcli brain plan. A "✅" written beside one is wrong as soon as anyone builds anything.
  • Sprint chatter and task assignment. Requirements and their slices, yes; who is doing what this week, no — that belongs in an issue tracker.
  • A restatement of Mendix documentation. Record what is true here.

Handing a slice to another agent

Every command above takes --json, so a dispatcher can act on the answers rather than read them. Two shapes are worth knowing.

Give the agent its pack. mxcli brain brief --slice <name> is one bounded read instead of a directory the agent has to navigate.

Check that it recorded something. With one agent per slice the brain stops being a record and becomes the only channel between slices — the next agent has no memory of this one, so a capture that never happened is a decision lost rather than a note lost. Note the boundary before dispatching and ask afterwards:

before=$(mxcli brain staged --json | jq -r .last_id)
# ... the slice's agent runs, and captures ...
mxcli brain staged --since "$before" --fail-if-empty --json

--since rather than --slice is deliberate: capture --slice is what makes an entry a requirement, so a decision found while building a slice carries no slice at all — and a slice's findings are mostly decisions. The queue is append-only, so its own order is the honest boundary. last_id comes back even when nothing matched, so a slice that recorded nothing still hands the next one a boundary.

Project brain (mxcli brain init/capture/staged/promote/drop/check/show)

an opt-in store in docs/brain/ for the project knowledge mxcli cannot compute. The governing rule is that anything derivable from the model is answered by a command and never written down — a note that transcribes the model disagrees with it silently. Records shard by anchor scope: an entry's first anchor names its file (@Sales.Order → modules/Sales.md), an anchorless entry is cross-cutting (project.md), and there is no index to maintain because the module prefix is the file name. That is what makes the cap per-shard rather than a project-wide budget, and lets a session load project.md plus the modules it is touching. check answers two independent questions: each anchor is resolved / not found / not indexable — only the middle one fails, and the third exists because the catalog's objects view covers the describable types only, so a scheduled event would otherwise read as missing (separated with FindDocumentUnit, which cannot miss a kind because it never asks what kind anything is). Misfiling is a second axis, not a fourth state: every anchor can resolve and the entry still be in the wrong file, and it is only decided when something resolved — judging it on an all-not-indexable entry reintroduced the same false staleness through the other axis (caught by a test, with the guard stubbed as the control). An agent captures to a git-ignored queue and a person promotes; the queue is deliberately not sharded, because routing it would force the file decision before a human has looked at the entry. mxcli lint prints the unpromoted-queue count, because a report only brain check prints is a report nothing demands. Sizes are computed by brain show and never written into a committed file. A second record kind, requirement, lives in plan/<slice>.md and inverts the anchor's meaning: a decision's anchor points backward (not resolving = stale, fails), a requirement's points forward (not resolving = not built yet, passes). Measured: filed as an ordinary entry, one unbuilt requirement takes brain check to exit 1 — which is why it is a separate kind rather than more entries in the same files. That inversion is also what makes brain plan a real progress report: a requirement is built when its anchors resolve, so creating the microflow it names moves the count with the plan file untouched (measured 0/1 → 1/0). A status written beside a requirement is therefore refused by the skill, not just discouraged. Slices are ordered by name (01-accounts), span modules by design (so misfiling does not apply), and carry a generous cap that enforces the slicing discipline — a slice too long to read should be split. A third kind, open question (--open), records what is not decided; its anchors are deliberately not checked, since the question is often whether the thing should exist at all — measured, the identical anchor exits 1 as a decision and 0 as a question. brain resolve converts one into a decision in place, keeping its id and position and starting to check its anchors, which is the transition the kind exists for. Unanswered questions are reported by brain check and by mxcli lint. The skill also gives capture a trigger rather than good intentions — a correction you have had to make twice — because the decisions half otherwise under-fills while the plan half fills at bootstrap. bootstrap-app asks for requirements at the interview and records them by default. Package: cmd/mxcli/brain/. See docs-site/src/tools/project-brain.md and docs/11-proposals/PROPOSAL_project_brain.md

© mendixlabs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/mendix/project-brain of mendixlabs/mxcli.

Open the folder on GitHubat commit a924d11

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Works with

Categories

Questions about Project Brain

What does Project Brain do?

Project-specific knowledge mxcli cannot compute — the requirements and slices being built from (a spec, a prototype, a conversation), why a pattern was chosen here, what is still undecided, which…. Project Brain is an agent skill from mendixlabs/mxcli. Project-specific knowledge mxcli cannot compute — the requirements and slices being built from (a spec, a prototype, a conversation), why a pattern was chosen here, what is still undecided, which marketplace version broke what.

When should I use Project Brain?

Project Brain fits situations like: starting from requirements that live outside git; before designing something that looks like it was decided before; you have had to correct the same thing twice; when an mxbuild error is resolved by something non-obvious.

How do I install Project Brain in Claude Code?

Run `npx skills add mendixlabs/mxcli --skill project-brain -a claude-code`. Or copy the skill folder (.claude/skills/mendix/project-brain in mendixlabs/mxcli) into .claude/skills/project-brain in your project. Claude Code loads it when a task matches its description.

How do I install Project Brain in Codex?

Run `npx skills add mendixlabs/mxcli --skill project-brain -a codex`. Or copy the skill folder (.claude/skills/mendix/project-brain in mendixlabs/mxcli) into .agents/skills/project-brain in your project. Codex loads it when a task matches its description.

Can I use Project Brain in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mendixlabs/mxcli --skill project-brain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/project-brain, .gemini/skills/project-brain, .github/skills/project-brain and .opencode/skills/project-brain in your project.

What does Project Brain need to run?

Going by SKILL.md and its folder, Project Brain needs the command-line tools its instructions call (jq).

Does Project Brain access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Project Brain safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Project Brain use?

Project Brain is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Project Brain use?

About 4.9k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Project Brain?

Skills that share tags, products or a category with Project Brain: Finishing a Development Branch (obra/superpowers, 296k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Codebase Knowledge Graph Q&A (Egonex-AI/Understand-Anything, 85k stars) and Code Design Rationale Investigator (cursor/plugins, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Project Brain?

mendixlabs (a GitHub organization) maintains it in mendixlabs/mxcli, which has 128 GitHub stars. The repository holds 75 skills in this directory. The repository was last updated on October 7, 2026.

Source: mendixlabs/mxcli on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.