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 ai-creed/ai-shakespii --skill authoring-skillsgit clone --depth 1 https://github.com/ai-creed/ai-shakespiiWrote 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/ai-creed/ai-shakespii/authoring-skills)<a href="https://agentmods.dev/skills/ai-creed/ai-shakespii/authoring-skills"><img src="https://agentmods.dev/badge/skills/ai-creed/ai-shakespii/authoring-skills/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/ai-creed/ai-shakespii/authoring-skills"><img src="https://agentmods.dev/badge/skills/ai-creed/ai-shakespii/authoring-skills.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 | $0.00058 | $0.01524 |
| Opus 5.5 | $0.00023 | $0.00610 |
| Sonnet 5.5 | $0.00012 | $0.00305 |
| Haiku 4.5 | $0.00006 | $0.00152 |
Grade A, and why
authoring-skills 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 2mo 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
authoring-skills
Intent
Turn a human's idea into a finished Agent Skill through a structured loop: interview the human for the raw material, draft against the anatomy contract, critique with a rubric of qualities no linter can check, and refine until the harness — not taste — says the skill works. The using-shakespii skill teaches how to drive the CLI; this skill decides what the new skill should say.
Inputs
- The idea: a problem statement, requirement, or repeated workflow the human wants captured as a skill.
- A writable parent directory for the new skill.
- Optional: raw material the human already has — notes, transcripts, a real worked example, memory excerpts.
Preconditions
- The shakespii CLI resolves (
shakespii --versionsucceeds); setup lives in the using-shakespii skill's Preconditions. - The using-shakespii skill is available — every CLI mechanic here (fix loop, eval runs, trigger measurement) delegates to it.
- A human is reachable for the interview, or the task prompt already supplies and approves the interview's answers.
Procedure
Phase 1 — Interview. Ask one question at a time, multiple-choice where the options are enumerable, until every anatomy section has raw material:
- Intent: what problem, for whom, and what does a successful use look like?
- Triggers: at least five real requests that should fire the skill, and at least three lookalikes that must not.
- Inputs and preconditions: what the skill consumes; binaries, paths, and environment it assumes.
- Procedure: walk one real occurrence of the workflow end to end.
- Example: one real input with its real output — not an invented pair.
- Failure modes: what has gone wrong when this was done by hand.
The interview ends when you can state the kebab-case name, the purpose, and the trigger list back and the human confirms them — or when the task prompt already supplied and approved all three. In a non-interactive run where the prompt leaves questions open, ask them all in one batch as your final output instead of guessing.
What ships with it
6 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.
- 2mo ago First seen · 151 lines · 58 tokens per session scan A 25d2b8025e80
authoring-skills is a skill published in the GitHub repository ai-creed/ai-shakespii (2 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 1,524 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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