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 jscraik/Agent-Skills --skill skill-factory-skillifygit clone --depth 1 https://github.com/jscraik/Agent-SkillsWrote 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/jscraik/agent-skills/skill-factory-skillify)<a href="https://agentmods.dev/skills/jscraik/agent-skills/skill-factory-skillify"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/skill-factory-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/jscraik/agent-skills/skill-factory-skillify"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/skill-factory-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 | $0.00057 | $0.00873 |
| Opus 5.5 | $0.00023 | $0.00349 |
| Sonnet 5.5 | $0.00011 | $0.00175 |
| Haiku 4.5 | $0.00006 | $0.00087 |
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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skillify
Convert a completed workflow into a reusable skill package with explicit invoke syntax.
Read when: intake and template details are needed: skill template Read when: source workflow context comes from prior agent sessions: session collector intake
Philosophy
- Preserve repeatable behavior, not one-off execution details.
- Optimize for future operator clarity with minimal ambiguity.
- Keep generated skills auditable with explicit inputs, outputs, and validation.
When to use
- Use when a workflow has been repeated enough to justify a reusable skill.
- Use when the user wants a conversation or run converted into durable
SKILL.mdguidance.
Required inputs
- Source workflow context (session transcript, notes, commands used, or
~/.agents/session-collectorbundle evidence). - Target audience and success criteria for the new skill.
- Destination path and category for where the skill should live.
Deliverables
- A complete skill package centered on
SKILL.mdwith clear invoke syntax. - Any required companion files referenced by the skill (scripts, templates, references).
- Validation notes covering contract and structure checks.
- Structured output includes
schema_version: 1when requested or when automation will consume the handoff.
Procedure
- Capture the source workflow and confirm intended reuse scope.
- If the workflow source is a prior session or repeated agent run, prefer
~/.agents/session-collectorbundle evidence and consume bounded extracted evidence rather than raw transcripts. - Extract stable triggers, required inputs, deliverables, and failure boundaries.
- Draft
SKILL.mdusing the template and include explicit procedure/validation/constraints sections. - Add or update supporting references (contract/evals/task profile) needed for governance gates.
- Run the relevant structure checks and iterate until clean.
Reference materials:
What ships with it
8 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.
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 · 90 lines · 57 tokens per session scan A 2597a9d2fc66
skillify is a skill published in the GitHub repository jscraik/Agent-Skills (9 stars, last pushed yesterday), licensed Apache-2.0. It adds 57 tokens to every session and 873 once invoked, about $0.0002 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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