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 redhuntlabs/wizard --skill inferring-a-spell-from-examplesgit clone --depth 1 https://github.com/redhuntlabs/wizardWrote 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/redhuntlabs/wizard/inferring-a-spell-from-examples)<a href="https://agentmods.dev/skills/redhuntlabs/wizard/inferring-a-spell-from-examples"><img src="https://agentmods.dev/badge/skills/redhuntlabs/wizard/inferring-a-spell-from-examples/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/redhuntlabs/wizard/inferring-a-spell-from-examples"><img src="https://agentmods.dev/badge/skills/redhuntlabs/wizard/inferring-a-spell-from-examples.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 | $0.00056 | $0.02575 |
| Opus 5 | $0.00028 | $0.01288 |
| Sonnet 5 | $0.00011 | $0.00515 |
| Haiku 4.5 | $0.00006 | $0.00258 |
Grade A, and why
inferring-a-spell-from-examples 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 9d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inferring a Spell from Examples
What this does
Reads a transcript (a saved chat session, a meeting notes file, or the current chat) and infers a skill from it. Produces a draft SKILL.md and hands it off to the regular meta-builder at Stage 2.
This skill is invoked by /capture-this-chat and by /build-spell --from-transcript <path>. It never runs alone — it always hands off to building-a-spell.
When to use
- The user runs
/capture-this-chator/build-spell --from-transcript - A transcript or chat-context blob has been provided as input
- The user wants to convert demonstrated behavior into a reusable skill
What you bring (Inputs)
- A transcript blob (markdown text in the normalized format, see
docs/capturing-chats.md) - The provenance of the transcript (a file path, a chat session ID, or both)
What you get (Output)
A context dictionary plus a draft SKILL.md, handed back to building-a-spell Stage 2 (kind-route → specialist → try-it → save). The user sees a strawman with Approve · Refine · Re-do as interview choices.
How it works (Steps)
This skill runs three sequential passes. Each pass is a hard gate.
Stages
Stage 1: Suitability check (Pass 1)
Read the transcript. Decide one of three outcomes:
| Outcome | Triggers | Action |
|---|---|---|
BUILDABLE |
≥ 5 substantive turns AND a discernible repeating pattern (steps, rules, output shape) | Continue to Stage 2 |
TOO-THIN |
< 5 substantive turns, OR no repeated structure (one-shot Q&A) | Stop. Tell user: "Not enough structure to infer a skill. Want to try the regular interview? Run /build-spell." |
TOO-BROAD |
≥ 2 distinct tasks tangled (e.g. research + email drafting in one transcript) | Stop. Tell user: "I see two tasks here: A and B. Pick one to capture, or run them through the regular interview separately." |
A "substantive turn" excludes: greetings, acknowledgments, single-word confirmations, error messages.
Output of Stage 1: { outcome: "BUILDABLE" | "TOO-THIN" | "TOO-BROAD", reason: string }. If outcome is not BUILDABLE, halt.
What ships with it
4 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.
- 9d ago First seen · 204 lines · 56 tokens per session scan A c86ff8d8188f
inferring-a-spell-from-examples is a skill published in the GitHub repository redhuntlabs/wizard (9 stars, last pushed 4mo ago), licensed MIT. It adds 56 tokens to every session and 2,575 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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