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.
npx skills add CocoRoF/geny-executor --skill skillifygit clone --depth 1 https://github.com/CocoRoF/geny-executorWrote 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/cocorof/geny-executor/skillify)<a href="https://agentmods.dev/skills/cocorof/geny-executor/skillify"><img src="https://agentmods.dev/badge/skills/cocorof/geny-executor/skillify/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/cocorof/geny-executor/skillify"><img src="https://agentmods.dev/badge/skills/cocorof/geny-executor/skillify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00036 | $0.01222 |
| Opus 5.5 | $0.00014 | $0.00489 |
| Sonnet 5.5 | $0.00007 | $0.00244 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
Skillify 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 1mo 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skillify — capture a repeated workflow as a skill
You are going to interview the user, distill what they keep doing
into a SKILL.md, and write it to the right place on disk. The output
lives at ~/.geny/skills/<id>/SKILL.md (user-scope) or
<project>/.geny/skills/<id>/SKILL.md (project-scope) depending on
how broadly the workflow applies.
Step 1 — Sniff the context
Before asking anything, glance at the recent conversation. The workflow being captured is probably something the user just did (or just asked to redo). If you can already infer the shape, lead with a one-sentence summary and ask the user to confirm.
# Where would the project-scope skill go?
[ -d .geny/skills ] || mkdir -p .geny/skills
echo ".geny/skills/ ready under $(pwd)"
Step 2 — Interview
Ask, in this order, one question at a time. Wait for an answer before the next question. Don't ask all at once — operators get overwhelmed and answer poorly.
-
What should this skill do, in one sentence? This becomes the
descriptionfrontmatter field. Push back gently if the answer is vague — "produces a report" is too broad; "produces a markdown summary of changed files between two git refs" is right. -
What's a short id? kebab-case, ≤ 32 chars, must match
[a-z0-9][a-z0-9_-]*. Suggest one based on the description if the user shrugs. -
What arguments does it take? Ask for argument names and a one-line hint. If none, that's fine — many skills are parameterless.
-
Which tools does it need? Pick from the host's actual tool roster (Read / Write / Bash / Edit / Grep / Glob, plus any custom). Default to
[Read, Bash]if the user is unsure. -
When should the model use it? This is the
when_to_usefield — extra discovery copy beyond the description. Examples: "When the user asks for a release-note draft." -
User scope or project scope? User scope if it applies regardless of which repo they're in (e.g. "PR draft generator", "verify"). Project scope if it depends on this codebase's layout (e.g. "run the project's specific test sweep").
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.
- 1mo ago First seen · 132 lines · 36 tokens per session scan A efdb777bc85e
Skillify is a skill published in the GitHub repository CocoRoF/geny-executor (2 stars, last pushed 6d ago), licensed Apache-2.0. It adds 36 tokens to every session and 1,222 once invoked, about $0.0001 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 2026-08-31.
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