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 building-a-discipline-spellgit 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/building-a-discipline-spell)<a href="https://agentmods.dev/skills/redhuntlabs/wizard/building-a-discipline-spell"><img src="https://agentmods.dev/badge/skills/redhuntlabs/wizard/building-a-discipline-spell/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/building-a-discipline-spell"><img src="https://agentmods.dev/badge/skills/redhuntlabs/wizard/building-a-discipline-spell.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 | $0.00037 | $0.01043 |
| Opus 5 | $0.00018 | $0.00522 |
| Sonnet 5 | $0.00007 | $0.00209 |
| Haiku 4.5 | $0.00004 | $0.00104 |
Grade A, and why
building-a-discipline-spell 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 10d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building a Discipline Spell
What this does
Specialist builder for kind: discipline spells. A discipline is a non-negotiable rule the agent (or the user) keeps slipping on. This skill produces a SKILL.md tuned to enforce the rule against the agent's own rationalization.
When to use
- Routed to from
building-a-spellStage 2 whenkind: discipline - User describes a "rule I keep skipping" or "I want the AI to never do X"
What you bring (Inputs)
- The non-negotiable rule (one sentence)
- Why it matters (the cost of skipping)
- The rationalizations used to skip it
- The user's domain
What you get (Output)
A draft SKILL.md with all required discipline sections, ready for pressure-testing-a-spell to harden.
How it works (Steps)
This is a workflow chain. Stages are explicit.
Stages
Stage 1: Sharpen the rule
If the rule has any of these words, push back: "should", "try to", "consider", "when possible", "usually". A discipline rule is a hard rule.
Re-write the rule until it's:
- One sentence
- Imperative voice
- Verifiable (you can tell from output whether it was followed)
Stage 2: Inventory the excuses
Ask the user (or extract from prior turns):
- "What's the exact thing you (or the AI) tells yourself when about to skip this rule?"
Capture verbatim. Don't paraphrase. Aim for 4-6 excuses.
For each excuse, write the counter — sharp enough to actually stop the action.
Stage 3: List the warning signs
What patterns in the agent's own reasoning would predict the rule is about to break? Examples:
- "About to claim done without verifying"
- "About to write code without opening the test file"
- "Reasoning includes the words 'obviously' / 'just' / 'trivially'"
These warning signs let the agent self-detect.
Stage 4: Place the hard gate
Identify the latest possible moment in the workflow where the rule could be enforced. Place a <MUST-STOP> block there with explicit "if this isn't true, STOP" language.
Discipline skills have ONE gate, placed late. Multiple gates dilute the effect.
What ships with it
1 file 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.
- 10d ago First seen · 126 lines · 37 tokens per session scan A 7b8d934447c9
building-a-discipline-spell is a skill published in the GitHub repository redhuntlabs/wizard (9 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 1,043 once invoked, about $0.0002 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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