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 Benknightdark/neo-skills --skill generate-skillgit clone --depth 1 https://github.com/Benknightdark/neo-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/benknightdark/neo-skills/generate-skill)<a href="https://agentmods.dev/skills/benknightdark/neo-skills/generate-skill"><img src="https://agentmods.dev/badge/skills/benknightdark/neo-skills/generate-skill/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/benknightdark/neo-skills/generate-skill"><img src="https://agentmods.dev/badge/skills/benknightdark/neo-skills/generate-skill.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 | $0.00061 | $0.00989 |
| Opus 5 | $0.00030 | $0.00495 |
| Sonnet 5 | $0.00012 | $0.00198 |
| Haiku 4.5 | $0.00006 | $0.00099 |
Grade A, and why
generate-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 11d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Generator Specification
Perceive
- Receive the user's request to create, update, convert, review, or optimize an Agent Skill.
- Identify the target task, usage scenarios, pain points, expected outputs, target agent client, and whether the user already has source material such as docs, runbooks, examples, code, prompts, or previous failures.
- If high-impact information is missing, ask concise follow-up questions before generating final files. Do not invent domain rules that should come from the user or existing project material.
Reason
- Load Official Agent Skills Reference: Load and analyze
.agents/skills/generate-skill/reference/AgentSkillsOfficialReference.mdfirst. Treat it as the source of truth forSKILL.mdfrontmatter, directory structure, progressive disclosure, description triggering, scripts, references, assets, evals, and client implementation considerations. - Load Reference Patterns: Load and analyze
.agents/skills/generate-skill/reference/SkillCategory.mdto understand 5 core design patterns:- Tool Wrapper: Suitable for encapsulating APIs, libraries, or team development conventions.
- Generator: Suitable for consistently producing structured documents in specific formats (e.g., reports, templates).
- Reviewer: Suitable for systematically checking the quality of code or outputs (e.g., security, style).
- Inversion: Suitable for guided requirement gathering, ensuring the Agent does not guess answers prematurely.
- Pipeline: Suitable for complex tasks that require a strict execution order and cannot skip steps.
- Load Reference Templates: Load and analyze the standard templates under
.agents/skills/generate-skill/templates/(includingSKILL.md,evals.json,eval_queries.json, andpep723.py) to provide standard, high-quality boilerplate content to the user. - Load ReAct Guidelines: Load and analyze
.agents/skills/generate-skill/reference/ReAct_vs_CLI.mdwhen the skill involves local exploration, CLI behavior, autonomous debugging, cross-file analysis, CI/CD assistance, or another agentic operating-system workflow. - Requirement Matching: Based on the user's requirement, choose the most suitable pattern or combination of patterns. Use official Agent Skills format as the baseline; Perceive/Reason/Act is optional structure, not a mandatory official requirement.
- Progressive Disclosure Planning: Decide what belongs in
SKILL.mdversusreferences/,scripts/,assets/, andevals/. KeepSKILL.mdconcise and load detailed material only when needed. - Description & Validation Planning: Draft a trigger-focused
description, identify likely should-trigger and should-not-trigger prompts, and plan output quality checks for important or shareable skills.
What ships with it
7 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.
- 11d ago First seen · 44 lines · 61 tokens per session scan A 5c89048f1cd2
generate-skill is a skill published in the GitHub repository Benknightdark/neo-skills (7 stars, last pushed 4d ago), licensed MIT. It adds 61 tokens to every session and 989 once invoked, about $0.0003 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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