create-skill

A skill-creation workflow that turns an agent prompt, Gemini Gem, or idea into a structured skill for the Hypergraph Coding Agent Framework. It creates the expected skill folder and supporting structure.

In plain words
What is it for?
Use it to package a prompt or idea as a workspace or global skill, including optional folders for scripts, examples, templates, and other resources.
Why use it?
It gives a consistent format for reusable agent instructions instead of leaving them as an unstructured prompt.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/tjmustard/hypergraph-coding-agent-framework/hyper-create-skill
Any agent
npx skills add tjmustard/Hypergraph-Coding-Agent-Framework --skill hyper-create-skill
Clone the repo
git clone --depth 1 https://github.com/tjmustard/Hypergraph-Coding-Agent-Framework

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 654 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00045 $0.00654
Opus 5 $0.00023 $0.00327
Sonnet 5 $0.00009 $0.00131
Haiku 4.5 $0.00005 $0.00065

Measured yesterday against content hash 0e8abd883b17, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create-skill 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 yesterday.

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/hyper-create-skill/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Skill

Follow these steps to predictably convert a Gemini Gem or generic agentic prompt into a properly formatted structural skill for the Hypergraph Coding Agent Framework.

When to use this skill

  • When the user provides an agentic prompt, a "Gemini Gem", or a raw textual description and asks you to create a "skill" out of it.
  • When the user runs the /hyper-create-skill slash command.

How to use it

  1. Gather Inputs:

    • Ensure you have the full content of the agentic prompt / Gemini Gem.
    • Determine a short, hyphen-separated name for the skill (e.g., code-review or api-design).
    • Determine a concise, third-person description of what the skill does (e.g., "Generates unit tests for Python code using pytest conventions.").
  2. Create the Directory Structure:

    • Create the primary skill folder at .agents/skills/<skill-name>/ (Workspace scope) or ~/.gemini/antigravity/skills/<skill-name>/ (Global scope). Default to workspace scope unless otherwise specified.
    • Create the standard optional subdirectories:
      • scripts/ (for helper scripts)
      • examples/ (for reference implementations)
      • resources/ (for templates and assets)
  3. Draft the SKILL.md File:

    • Create the main instruction file at the root of the skill folder: SKILL.md.
    • Mandatory Frontmatter: Start the file with the strict YAML frontmatter exactly as shown in this skill's resources/SKILL_TEMPLATE.md.
    • Structure the Content: Adapt the prompt into the standard markdown format using the template as a guide. Ensure you include the ## When to use this skill and ## How to use it sections.
  4. Organize and Create Auxiliary Files:

    • Identify if the input prompt/Gem includes secondary materials (scripts, examples, JSON schemas, templates, etc.).
    • Create any identified script files in the scripts/ subdirectory (ensure executable permissions if applicable).
    • Create any identified example files in the examples/ subdirectory under the new skill.
    • Create any identified template or asset files in the resources/ subdirectory under the new skill.
    • Explicitly reference these auxiliary files from within the newly generated SKILL.md file using relative paths or explicit instructions.

Read the full file on GitHub · 44 lines

Files

What ships with it

2 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.

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. yesterday First seen · 44 lines · 45 tokens per session scan A 0e8abd883b17

Subscribe to this mod's changes

create-skill is a skill published in the GitHub repository tjmustard/Hypergraph-Coding-Agent-Framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 654 once invoked, about $0.0002 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 2026-08-31.

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