This repository collects focused HyperFrames skills that are useful to share but are too specialized for the curated public skill set. Contributions should be small enough for a reviewer to understand the complete behavior and trust boundary.
- Search the repository for an existing skill that covers the same workflow.
- Search existing issues, and open a skill proposal before investing in a substantial new skill.
- Keep the skill self-contained. Do not add shared runtime code under
skills/or at the repository root. - Confirm that you have the right to redistribute every dependency and asset.
- Do not submit credentials, customer data, private URLs, or generated output.
Create one lowercase kebab-case directory under skills/:
skills/
└── my-specific-workflow/
├── SKILL.md
├── scripts/ # optional
├── references/ # optional
└── assets/ # optional
SKILL.md must begin with YAML frontmatter whose name exactly matches the
directory:
---
name: my-specific-workflow
description: Use when an agent needs to do a specific HyperFrames workflow.
---The instructions should explain:
- when to use and when not to use the skill;
- required inputs, tools, dependencies, and credentials;
- the workflow and its expected outputs;
- network calls, paid operations, file changes, and other side effects;
- how the agent and reviewer can verify success.
Use relative links for files owned by the skill. An agent reading only that skill directory should have everything needed to follow it.
Add new and renamed skills to the Available skills table in README.md.
Link the skill name as skills/<skill-name>/ and describe the concrete use case
in one sentence. Remove the empty-catalog message when adding the first skill.
Pull requests will not be merged if they contain:
- secrets, tokens, personal data, private endpoints, or real credentials;
- obfuscated, minified, vendored, generated, or unexplained executable code;
- compiled executables, dynamic libraries, bytecode, or archives that hide reviewable source;
- symlinks, install-time execution, or undeclared downloads;
- silent telemetry, tracking, or data exfiltration;
- destructive actions without a safe default and explicit user confirmation;
- paid or externally visible actions without explicit user confirmation;
- broad filesystem, shell, or network access that the workflow does not need;
- unpinned dependencies where an upstream change could alter behavior;
- instructions that weaken authentication, authorization, sandboxing, or other security controls.
Scripts must be readable source, minimal, and directly necessary for the skill. Prefer standard tools over adding dependencies. If a network service is needed, name the service, the data sent to it, the credentials it uses, and whether it can incur cost.
AI-assisted contributions are welcome, but the submitter remains responsible for every instruction and script. Do not submit behavior you have not read, understood, and tested.
Run the repository validator:
bash .github/scripts/validate-skills.shThen test the skill with a fresh agent session that has access only to the skill and the dependencies documented in it. Exercise the normal path and at least one failure or cancellation path. Do not use production credentials or sensitive data in test fixtures or evidence.
Fork the repository, create a new branch from master, and open a pull request
against this repository. Keep it scoped to one skill or one coherent fix. In
the pull request:
- explain the use case and why it belongs in the community collection;
- enumerate commands, network destinations, credentials, costs, and side effects;
- describe the tests you ran and include non-sensitive evidence;
- disclose dependencies and licenses;
- call out any residual risk a user should understand.
All required checks must pass and a code owner must approve the exact head
commit. Resolve review threads before merge. Do not push directly to master.
By participating, you agree to follow the Code of Conduct. Contributions are licensed under the repository's Apache 2.0 license.