MPS: Skill for Claude Code

.agents/skills/mps-aspect-textgen/SKILL.md

mps-aspect-textgen is a skill for Claude Code, Codex from JetBrains/MPS. It costs 131 tokens per session (2,210 once invoked), scanned A, original, Apache-2.0.

A guide for JetBrains MPS TextGen, the part of MPS that turns language models into text files such as source code, configuration files, scripts, XML, or Markdown.

In plain words
What is it for?
Use it when creating or debugging MPS rules that generate text files from models, including file names, extensions, encodings, inserted text, and indentation.
Why use it?
It helps avoid failed or incorrectly formatted generated files by explaining the required models, imports, declarations, indentation, and text layout rules.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is JetBrains/MPS's own configuration. It tells Claude Code and Codex how to work on MPS itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything MPS configures →

About the project

JetBrains MPS is a development environment for creating domain-specific languages, which are programming languages designed for a particular field or task. It provides editors with features such as completion, semantic checks, and type checking, and can generate code in languages including Java and XML.

JetBrains/MPS · 1,656 stars · on GitHub · jetbrains.com

Reuse

Borrowing it

Nothing to install: this file belongs to JetBrains/MPS. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/JetBrains/MPS/master/.agents/skills/mps-aspect-textgen/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/JetBrains/MPS

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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agentmods badge for mps-aspect-textgen

README.md
[![agentmods](https://agentmods.dev/badge/skills/jetbrains/mps/mps-aspect-textgen.svg)](https://agentmods.dev/skills/jetbrains/mps/mps-aspect-textgen)
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<a href="https://agentmods.dev/skills/jetbrains/mps/mps-aspect-textgen"><img src="https://agentmods.dev/badge/skills/jetbrains/mps/mps-aspect-textgen.svg" alt="Measured on agentmods" height="20"></a>
Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,210 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00131 $0.02210
Opus 5 $0.00066 $0.01105
Sonnet 5 $0.00026 $0.00442
Haiku 4.5 $0.00013 $0.00221

Measured 8d ago against content hash 8f0d36f39191, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

mps-aspect-textgen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/mps-aspect-textgen/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MPS TextGen Aspect

TextGen turns a model (usually the output of generation) into plain text files. It is how BaseLanguage becomes .java on disk, and how any text-targeting language serialises its models. Lives in <lang>/languageModels/textGen.mps, language jetbrains.mps.lang.textGen. Rule bodies are BaseLanguage + smodel + textgen-specific statements (append, indent buffer, with indent).

Prerequisite for any insert: the textGen model must exist (mps_mcp_create_model with modelName: "<lang>.textGen" — aspect ID textGen, case-sensitive, no @ suffix; see aspect-model-stereotypes.md) and must import jetbrains.mps.lang.textGen, jetbrains.mps.baseLanguage, and jetbrains.mps.lang.smodel as used languages before the first mps_mcp_insert_root_node_from_json. Missing any of these three causes node inserts to fail with unresolved-concept errors. See step 1 of the Common-Path Workflow.

Critical Directives

  • One ConceptTextGenDeclaration root per concept you want to serialise. Only the file-generating root concept needs extension / filename / encoding; structural concepts inside the file need only textGenBlock.
  • extension is a function body returning a string, not a literal property. It must return a string.
  • TextGen dispatch is concept-exact, not polymorphic. An extending concept that wants the parent's serialisation must declare its own ConceptTextGenDeclaration (even an empty one) — or its output will be silently missing. See references/dispatch-and-base-component.md.
  • The indentation buffer is a per-output-file depth counter. with indent / increase depth / decrease depth and the withIndent flag on NodeAppendPart only mutate the counter — whitespace is emitted only when indent buffer is called. Always pair append \n ; with indent buffer ; on the next line that should be indented. See references/indentation-model.md.
  • Prefer with indent { ... } over paired increase depth ; … ; decrease depth ; — the block form cannot leak depth on an early return or exception. Use the paired form only when the scope is not a block.
  • Use TextGen only when the final artifact is text. If your pipeline ends in a model-to-model transformation targeting another MPS language (e.g. BaseLanguage), you don't need TextGen — that language's own TextGen handles the final step.
  • BinaryWriteOperation (write) cannot be mixed with text appends in the same ConceptTextGenDeclaration. A rule emits either text or bytes, not both.
  • The older $ref{node.reference<target>} syntax is deprecated. Use a NodeAppendPart over a resolved node (or over .name).
  • Edit textGen models through MPS MCP tools (mps_mcp_insert_root_node_from_json, mps_mcp_update_node). Do not hand-edit .mps files.
  • After edits run mps_mcp_check_root_node_problems and rebuild the language; regenerate consumers.

Read the full file on GitHub · 62 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 62 lines · 131 tokens per session scan A 8f0d36f39191

Subscribe to this mod's changes

mps-aspect-textgen is a skill published in the GitHub repository JetBrains/MPS (1,656 stars, last pushed yesterday), licensed Apache-2.0. It adds 131 tokens to every session and 2,210 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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