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Srdf

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earthtojake
srdf

MoveIt2 SRDF authoring, validation, and planning-semantics workflow. Use when creating, editing, inspecting, or validating `.srdf` files, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-paired planning semantics, or SRDF handoff for live review. Use the URDF skill for robot structure, the SDF skill for simulator descriptions, and the cad-viewer skill for rendering and live review links.

Overview

Publisherearthtojake
Repositorytext-to-cad
Skill namesrdf
Stars
16K
Forks
1.7K
Bundled files
8
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.

  • 8 bundled files

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

  • Open source

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

Installation

Install the Srdf 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/earthtojake/text-to-cad.git /tmp/text-to-cad
mkdir -p .claude/skills
cp -r /tmp/text-to-cad/skills/srdf .claude/skills/srdf
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Srdf 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 Srdf 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 Srdf 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.

SRDF

Provenance: maintained in earthtojake/text-to-cad. Use the installed local skill files as the runtime source of truth; the repository link is only for provenance and release review.

Use this skill for MoveIt semantic robot descriptions on top of an existing valid URDF. SRDF defines planning semantics; it does not define physical robot structure. The .srdf file is the source of truth: author and edit the XML directly. There is no gen_srdf() contract.

SRDF correctness is a planning semantics problem. The common failure is not invalid XML; it is a plausible SRDF that gives MoveIt the wrong planning group, wrong tool link, wrong default state, unsafe disabled-collision matrix, or wrong joint units. Because language models are weak at spatial and kinematic reasoning, derive planning groups, end effectors, group states, and disabled collisions from the URDF topology, MoveIt Setup Assistant output, sampled collision analysis, or explicit user data. Do not infer them from visual theme alone — and do not type any link or joint name from memory: extract the URDF's link/joint table first and copy names from it.

Setup

This skill's commands are thin entrypoints over the cadgen distribution, which carries the Python build runtime and the JavaScript it executes. Install it once:

bash
python -m pip install -r requirements.txt

Rendering additionally needs a browser, which pip cannot supply:

bash
python -m playwright install chromium

Format boundary

  • URDF owns physical robot structure: links, joints, geometry, inertials, limits, mimic joints, transmissions, and robot-state publishing.
  • SRDF owns MoveIt semantics: virtual joints, passive joints, planning groups, group states, end effectors, and disabled collision pairs.
  • SDF owns simulator/world semantics: physics, sensors, lights, plugins, worlds, and simulation-specific metadata.

Do not place geometry, inertials, joint origins, link poses, mesh references, physical joint limits, transmissions, or ros2_control interfaces in SRDF.

CAD Viewer Handoff

After completing SRDF work that creates or modifies a .srdf, you must ALWAYS hand the explicit file path to $cad-viewer when that skill is installed. $cad-viewer must start CAD Viewer if it is not already running and return link(s) to the relevant created or updated file(s). If $cad-viewer is unavailable or startup fails, report that instead of silently omitting the handoff.

Required workflow

  1. Start from a valid URDF. Author or fix the URDF first with $urdf and validate it. The SRDF pairs with that URDF by colocation and robot name, and every name in the SRDF must exist in it.
  2. Extract the URDF table. Before writing any SRDF XML, list the URDF's robot name, links, joints (with type, parent, child, limits, mimic flags). Copy names from this table only; never type them from memory. See references/srdf-workflow.md.
  3. Identify the planning task. Record whether the goal is arm IK, gripper control, mobile base planning, dual-arm planning, tool use, or local smoke testing.
  4. Create or update the planning ledger. Use references/planning-ledger.md before writing XML; keep a compact copy as a comment block in the .srdf.
  5. Pair with the URDF by colocation. Save the .srdf in the same folder as its .urdf, with the same <robot name> — that is the only linking mechanism. The validator and the viewer both resolve the pairing by scanning the folder for the URDF whose robot name matches; exactly one URDF per robot name per folder. No metadata element links the files. See references/authoring-contract.md.
  6. Define virtual and passive joints deliberately. Use them when needed by the robot model.
  7. Define planning groups from URDF topology. Prefer chain groups for serial manipulators when base/tip form a real parent-to-child path in the URDF tree (the validator verifies this). Use joint/link/subgroup definitions only when they are deliberate.
  8. Define end effectors after group membership is known. Avoid overlap between an end-effector group and its parent group. Record the actual target/TCP link.
  9. Define group states in URDF-native units. Revolute and continuous values are radians; prismatic values are meters. Do not store degrees in SRDF. Values must lie within URDF limits and must not set fixed or mimic joints.
  10. Generate disabled collisions from evidence. Use adjacency derived from the URDF joint table, MoveIt Setup Assistant sampling, or explicit user-provided collision matrices. Do not invent broad disable lists. See references/disabled-collisions.md.
  11. Validate every created or modified .srdf with cadgen srdf validate; it cross-validates all names, chains, states, and pairs against the paired URDF. Fix findings and re-validate until clean.
  12. Run MoveIt smoke tests when available. Use MoveIt Setup Assistant or a project MoveIt launch directly.
  13. Report assumptions and skipped checks. Include incomplete validation, missing MoveIt environment, manually reasoned collision disables, and inferred target links.

Commands

Run cadgen from the Python environment this skill's requirements.txt was installed into (python -m cadgen.cli <verb> with that interpreter is the PATH-independent equivalent). cadgen doctor <skill-dir> verifies the installed cadgen matches this skill's pin — docs drift silently on a mismatched install. Validation itself needs nothing beyond the Python standard library; only snapshots need the browser. Use cadgen <verb> --help for the complete current interface.

The validator shape is:

bash
cadgen srdf validate path/to/robot.srdf
cadgen srdf validate path/to/robot.srdf --strict
cadgen srdf validate path/to/robot.srdf --json

The validator parses the SRDF, resolves the paired URDF (the same-folder .urdf whose robot name matches; none, several, or an invalid one is an error), and cross-validates: group/joint/link/subgroup name existence, chain path resolvability, subgroup cycles, virtual/passive joints, end-effector topology, group-state membership/limits/completeness, disabled-collision pairs (including Adjacent-reason truthfulness), and misspelled elements. Each phase collects all its findings in one pass (severity, code, XML path), but a structural error stops the cross-file phase — re-run after every fix. One run validates ONE file: --strict treats warnings as failures and --json prints one line of {"ok", "path", "issues": [{"severity", "code", "message", "element", "hint"}], "summary"}, where element is the XML path. It exits nonzero if the target fails. Relative targets resolve from the current working directory.

Hard rules

  • The SRDF lives in the same folder as its URDF and shares its <robot name>; that colocation-plus-name match is the only pairing mechanism, and exactly one URDF per robot name may exist in the folder.
  • Every link, joint, group, and subgroup name must come from the URDF table or a group defined in the same file.
  • Group states use URDF-native units: radians for revolute/continuous, meters for prismatic.
  • Disabled collision pairs require truthful reasons and provenance.
  • End-effector groups should not share links with their parent planning group.
  • Visual rendering review is useful but cannot prove planning correctness.

Snapshot Tool

cadgen snapshot renders the robot to a PNG still, using the same shared CLI and headless browser runtime every rendering skill uses — so a snapshot matches what the CAD Viewer shows.

bash
cadgen snapshot path/to/robot.srdf review.png

Hand it the .srdf; it routes by suffix and renders the paired URDF's geometry. Pose the robot with --joint-values{joint: degrees} JSON, joints you do not name staying at the rest pose (the "jointValues" job field is the same thing in a packet). Robots are authored in metres and are framed on the robot scene scale automatically.

A normal snapshot uses deterministic light CAD lighting and hides grid and axis guides. Pass --render light or --render dark (or photographic Render JSON or a file path) for the shared Render scene. An envelope with no studio resolves Light in the CLI. Set its camera inside Render JSON; top-level --camera, --display, and --joint-values control normal snapshots and cannot be combined with Render. Robot link meshes have no CAD-edge or exploded assembly topology, so those display combinations are rejected clearly.

Link meshes are resolved relative to the description, so they must be present: an unhydrated Git LFS pointer fails as "No link mesh loaded for robot". Run git lfs checkout <mesh dir> first.

An SRDF's geometry comes from the URDF beside it, so it has no snapshot door of its own; the polymorphic cadgen snapshot routes one by suffix. The grammar is cadgen snapshot TARGET [OUT] [flags], the same one every format door uses. Use cadgen snapshot --help for the complete current interface.

References

  • Authoring contract (structure, URDF pairing, golden skeleton): references/authoring-contract.md
  • SRDF workflow (URDF table extraction, edit loop): references/srdf-workflow.md
  • Planning ledger: references/planning-ledger.md
  • Validation and verification recipe: references/validation.md
  • End effectors: references/end-effectors.md
  • Disabled collisions: references/disabled-collisions.md

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 Srdf AI skill do?

MoveIt2 SRDF authoring, validation, and planning-semantics workflow. Use when creating, editing, inspecting, or validating `.srdf` files, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-paired planning semantics, or SRDF handoff for live review. Use the URDF skill for robot structure, the SDF skill for simulator descriptions, and the cad-viewer skill for rendering and live review links.

Why use Srdf on TypingMind?

Because you install it once and use it with any model. Srdf 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 Srdf in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/earthtojake/text-to-cad/tree/main/skills/srdf. 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 Srdf?

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 Srdf?

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

Is the Srdf AI skill free?

Yes. It is published on GitHub by earthtojake 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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