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.
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.
curl -O https://raw.githubusercontent.com/JetBrains/MPS/master/.agents/skills/mps-aspect-accessories/SKILL.mdgit clone --depth 1 https://github.com/JetBrains/MPSWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jetbrains/mps/mps-aspect-accessories)<a href="https://agentmods.dev/skills/jetbrains/mps/mps-aspect-accessories"><img src="https://agentmods.dev/badge/skills/jetbrains/mps/mps-aspect-accessories/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jetbrains/mps/mps-aspect-accessories"><img src="https://agentmods.dev/badge/skills/jetbrains/mps/mps-aspect-accessories.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.01675 |
| Opus 5.5 | $0.00028 | $0.00670 |
| Sonnet 5.5 | $0.00014 | $0.00335 |
| Haiku 4.5 | $0.00007 | $0.00168 |
Grade A, and why
mps-aspect-accessories 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 29d 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.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MPS Module and Model Dependencies, Accessory Models
Loading companion skills
Companion names in this skill are lazy dependencies: load only those relevant to the current task. If this skill came from an MCP server, use the host's skill loader to resolve the companion's unique discovered entry URI on the same host-assigned originating server. If the host has no server-backed skill loader, stop and report that limitation; do not silently fall back to a filesystem copy. If this skill came from a filesystem catalog, load the named sibling from that same catalog at <skills-root>/<skill-name>/SKILL.md, even if remote skill loaders are also available. Do not invent a tool name or server endpoint.
This skill covers the wiring layer of an MPS language — the module descriptor (.mpl) and the per-model imports — and the special role of accessory models and runtime solutions.
Note: accessory wiring does not introduce a new aspect model or stereotype; it edits the existing language descriptor and model imports. When you do need to create a new aspect or stereotyped model, see aspect-model-stereotypes.md for the canonical aspect IDs and @stereotype values.
Critical Directives
- Prefer MCP wiring tools over hand-editing
.mplXML. Hand-editing can silently corrupt the module descriptor. If you must hand-edit (e.g. foraccessoryModels, which has no dedicated MCP tool), make a backup, edit only the targeted block, and rebuild the module immediately afterwards so MPS re-reads the descriptor. - Don't hand-edit
languageVersions/dependencyVersions. These are the consumer-side stamps recording which version of another language a module was last migrated against; MPS maintains them. Use the MPS "Update language/dependency versions" action. - A language's OWN version is a different number, exposed as
languageVersionon every Language module inmps_mcp_get_project_structureand derived from the migration scripts bymps_mcp_update_module(operation = "SYNC_VERSION")(max(fromVersion) + 1, computed for you; there is no way to set it to an arbitrary value). It is the integer a migration script'sfromVersiongates on, and bothMigrationScriptandPureMigrationScriptget it from their node factory when created through a factory-running path — never set it by hand. Never hand-edit it in the.mpl, and never "fix" a migration by refreshing the consumer stamps instead — that marks the migration as already applied. See module-info-fields.md and themps-aspect-migrationsskill. - Generator modules have their own dependency list. Add target-language deps to the generator, not the parent language.
- Used languages auto-import when nodes are inserted via
mps_mcp_insert_root_node_from_json,mps_mcp_update_node. Manually add a used language only for hand-written code or implicit dependencies. - A runtime solution holds the stable part of generation (code that doesn't vary with the model). Generate thin code that calls it; don't regenerate it. No MCP tool wires the language's
<runtime>block — seereferences/runtime-solutions.md.
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/accessory-models.md 1.5 KB
- references/aspect-model-stereotypes.md 8.6 KB
- references/extends-vs-uses.md 411 B
- references/model-level-imports.md 3.2 KB
- references/module-creation.md 5.3 KB
- references/module-info-fields.md 5.4 KB
- references/module-level-deps.md 5.9 KB
- references/module-rename.md 2.1 KB
- references/pitfalls.md 2.3 KB
- references/runtime-solutions.md 9.2 KB
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.
- 29d ago Changed 408b598a0aba
- 1mo ago Changed · +7 lines 15ab01a68202
- 2mo ago First seen · 56 lines · 69 tokens per session scan A 31d01f1a2889
mps-aspect-accessories is a skill published in the GitHub repository JetBrains/MPS (1,666 stars, last pushed yesterday), licensed Apache-2.0. It adds 69 tokens to every session and 1,675 once invoked, about $0.0003 per session on Opus 5.5. 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.
mps-aspect-accessories compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mps-aspect-accessoriesJetBrains/MPS | Skill | 1.7k | yesterday | Apache-2.0 | A | 69 | Claude Code, Codex |
| langiumeclipse-langium/langium-ai | Skill | 31 | 4d ago | MIT | A | 33 | Claude Code |
| lai-gen-evalseclipse-langium/langium-ai | Skill | 31 | 4d ago | MIT | A | 42 | Claude Code |
| laieclipse-langium/langium-ai | Skill | 31 | 4d ago | MIT | A | 52 | Claude Code |
| lai-gen-descriptoreclipse-langium/langium-ai | Skill | 31 | 4d ago | MIT | A | 49 | Claude Code |
| lai-gen-mcpeclipse-langium/langium-ai | Skill | 31 | 4d ago | MIT | A | 43 | Claude Code |
| lai-gen-language-skilleclipse-langium/langium-ai | Skill | 31 | 4d ago | MIT | A | 33 | Claude Code |