Segment Anything Model Guide
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
Add a new ONNX operator or update an existing operator to a new opset version.
$ npx skills add onnx/onnx --skill add-op -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install onnx/onnx add-op --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/onnx/onnx.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/add-op .claude/skills/add-op && rm -rf skills-srcUse ~/.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/
Install the "add-op" agent skill from https://github.com/onnx/onnx/tree/main/.agents/skills/add-op into .claude/skills/add-op/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-op", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/onnx/onnx/tree/main/.agents/skills/add-opType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add onnx/onnx --skill add-op -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install onnx/onnx add-op --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/onnx/onnx.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/add-op .agents/skills/add-op && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "add-op" agent skill from https://github.com/onnx/onnx/tree/main/.agents/skills/add-op into .agents/skills/add-op/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-op", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add onnx/onnx --skill add-op -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install onnx/onnx add-op --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/onnx/onnx.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/add-op .cursor/skills/add-op && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "add-op" agent skill from https://github.com/onnx/onnx/tree/main/.agents/skills/add-op into .cursor/skills/add-op/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-op", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/onnx/onnx.git --path .agents/skills/add-op--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add onnx/onnx --skill add-op -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install onnx/onnx add-op --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/onnx/onnx.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/add-op .gemini/skills/add-op && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "add-op" agent skill from https://github.com/onnx/onnx/tree/main/.agents/skills/add-op into .gemini/skills/add-op/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-op", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install onnx/onnx add-opInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add onnx/onnx --skill add-op -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/onnx/onnx.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/add-op .github/skills/add-op && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "add-op" agent skill from https://github.com/onnx/onnx/tree/main/.agents/skills/add-op into .github/skills/add-op/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-op", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add onnx/onnx --skill add-op -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install onnx/onnx add-op --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/onnx/onnx.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/add-op .opencode/skills/add-op && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "add-op" agent skill from https://github.com/onnx/onnx/tree/main/.agents/skills/add-op into .opencode/skills/add-op/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-op", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
add-opAdd a new ONNX operator or update an existing operator to a new opset version.
Add Op is an agent skill from onnx/onnx. Add a new ONNX operator or update an existing operator to a new opset version. Use when asked to define an operator schema, register an op, add inputs/outputs/attributes to an op, move an op to old.cc, or bump an op's opset version.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/node-test-pattern.md` and `references/reference-impl-pattern.md`).
It sits in AI & LLM Engineering, covering Deep learning. It works with ONNX. The repository describes itself as: Open standard for machine learning interoperability. The licence is Apache-2.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit dc30c0b. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Add Op loads about 1.2k tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 313 words of instructions outside code blocks.
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.
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.
The full file from onnx/onnx at commit dc30c0b, republished under its Apache-2.0 licence (© onnx). 313 words, ~1,186 tokens.
.claude/skills/add-op/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Follow the full procedure in docs/AddNewOp.md.
| Component | File |
|---|---|
| Schema definition | onnx/defs/<domain>/defs.cc |
| Operator set registration | onnx/defs/operator_sets.h |
| Type/shape inference | Inline in schema via .TypeAndShapeInferenceFunction(...) |
| Function body (if applicable) | Inline in schema via .FunctionBody(...) |
| Reference implementation | onnx/reference/ops/op_<lowercase_name>.py |
| Node tests | onnx/backend/test/case/node/<lowercase_name>.py |
| Shape inference tests | tests/python/shape_inference_test.py |
| Version converter adapter (if behavior changed) | onnx/version_converter/adapters/<name>_<from>_<to>.h |
| Upgrade/downgrade tests | tests/python/version_converter/automatic_upgrade_test.py and automatic_downgrade_test.py |
Domain subdirectories under onnx/defs/: math/, nn/, tensor/, logical/, reduction/, rnn/, sequence/, image/, text/, quantization/, controlflow/, optional/, traditionalml/, training/
ONNX_OPERATOR_SET_SCHEMA(
OperatorName,
OPSET_VERSION,
OpSchema()
.SetDoc(OperatorName_verN_doc)
.Input(0, "X", "Description", "T", OpSchema::Single, true, 1, OpSchema::Differentiable)
.Output(0, "Y", "Description", "T", OpSchema::Single, true, 1, OpSchema::Differentiable)
.Attr("attr_name", "Description", AttributeProto::FLOAT, default_value)
.TypeConstraint("T", {"tensor(float)", "tensor(double)", ...}, "Description")
.TypeAndShapeInferenceFunction(InferShapeForOperatorName)
// Function body uses ONNX text format — see the onnxtxt skill for syntax/conventions.
.FunctionBody(R"ONNX(
{
...
}
)ONNX", FUNCTION_OPSET_VERSION));defs.cc to old.cc in the same domain directorydefs.cc with the new opset version numberonnx/defs/operator_sets.hWhen moving a schema to old.cc, avoid significant code/documentation duplication:
Define shape inference functions and function body builders as separate named functions rather than inline lambdas within ONNX_OPERATOR_SET_SCHEMA. The macro expansion makes setting breakpoints on inline lambdas unreliable in debuggers.
// PREFERRED: named function — easy to set breakpoints
static void InferShapeForMyOp(InferenceContext& ctx) {
propagateElemTypeFromInputToOutput(ctx, 0, 0);
// ...
}
ONNX_OPERATOR_SET_SCHEMA(
MyOp, 21,
OpSchema()
// ...
.TypeAndShapeInferenceFunction(InferShapeForMyOp));For test fixtures, prefer the ONNX text format via onnx.parser / C++ OnnxParser. See the onnxtxt skill for the per-file recommendations table, body-subgraph idioms, the argument-order convention, and the unk__* materialization gotcha. (Empirical: PR #7962 cut ~58–70% of test LOC by switching.)
python onnx/defs/gen_doc.py
python onnx/backend/test/stat_coverage.py
python onnx/gen_proto.py # only if proto changed
lintrunner -a --output oneline© onnx, 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
SKILL.md and 2 other files (references) in .agents/skills/add-op of onnx/onnx.
Open the folder on GitHubat commit dc30c0b
Add Op next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Add Op this skillonnx/onnx | 22k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Technology Selectiondotnet/skills | 5.6k | 1 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Quark Torch Quant Perfamd/Quark | 181 | — | ~3k | Automated safety check: Pass | MIT | |
| Model Builderqualcomm/qai-appbuilder | 247 | — | ~4.1k | Automated safety check: Pass | BSD-3-Clause | |
| Embedded AI Deploymentmatlab/agent-skills-playground | 183 | — | ~3.4k | Automated safety check: Pass | Custom licence |
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
dotnet/skills
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX…
amd/Quark
Run, resume, monitor, diagnose, and report Quark Quant-Perf workflows for PyTorch and HuggingFace transformers models.
qualcomm/qai-appbuilder
QAI ModelBuilder. An agent skill from qualcomm/qai-appbuilder.
matlab/agent-skills-playground
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder).
microsoft/onnxruntime
Patterns and pitfalls for the ONNX-domain Attention operator's CUDA implementation in ONNX Runtime: dispatch cascade, eligibility limits, mask and bias kernels, and test routing.
onnx/onnx
Add a function body definition to an ONNX operator, defining how it decomposes into simpler ops.
onnx/onnx
Add or update type and shape inference for an ONNX operator.
onnx/onnx
Read or write ONNX text format ("onnxtxt"). An agent skill from onnx/onnx.
Works with
Categories
Add a new ONNX operator or update an existing operator to a new opset version. Add Op is an agent skill from onnx/onnx. Add a new ONNX operator or update an existing operator to a new opset version.
Add Op fits situations like: asked to define an operator schema; add inputs/outputs/attributes to an op; move an op to old.cc; bump an ops opset version.
Run `npx skills add onnx/onnx --skill add-op -a claude-code`. Or copy the skill folder (.agents/skills/add-op in onnx/onnx) into .claude/skills/add-op in your project. Claude Code loads it when a task matches its description.
Run `npx skills add onnx/onnx --skill add-op -a codex`. Or copy the skill folder (.agents/skills/add-op in onnx/onnx) into .agents/skills/add-op in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add onnx/onnx --skill add-op -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/add-op, .gemini/skills/add-op, .github/skills/add-op and .opencode/skills/add-op in your project.
Going by SKILL.md and its folder, Add Op needs the command-line tools its instructions call (python). Our summary lists: Python 3.
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.
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.
Add Op 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.
About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 572 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Add Op: Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars), Technology Selection (dotnet/skills, 5.6k stars), Quark Torch Quant Perf (amd/Quark, 181 stars) and Model Builder (qualcomm/qai-appbuilder, 247 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
onnx (a GitHub organization) maintains it in onnx/onnx, which has 21,569 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 9, 2026.
Source: onnx/onnx on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.