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 breeze-r/claude-prompt-craft-skill --skill prompt-craft-engit clone --depth 1 https://github.com/breeze-r/claude-prompt-craft-skillWrote 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/breeze-r/claude-prompt-craft-skill/prompt-craft-en)<a href="https://agentmods.dev/skills/breeze-r/claude-prompt-craft-skill/prompt-craft-en"><img src="https://agentmods.dev/badge/skills/breeze-r/claude-prompt-craft-skill/prompt-craft-en/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/breeze-r/claude-prompt-craft-skill/prompt-craft-en"><img src="https://agentmods.dev/badge/skills/breeze-r/claude-prompt-craft-skill/prompt-craft-en.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 | $0.00112 | $0.02076 |
| Opus 5 | $0.00056 | $0.01038 |
| Sonnet 5 | $0.00022 | $0.00415 |
| Haiku 4.5 | $0.00011 | $0.00208 |
Grade A, and why
prompt-craft-en 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 12d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Craft — Prompt Design & Optimization
Turn the user's intent into a clear, reusable, ready-to-run prompt. The methodology is a field-tested four-element framework: Goal, Context, Output, Boundaries.
A good prompt needs no special syntax or fixed template. Add elements only when they help — not every one, every time.
Workflow
When the user asks you to write or optimize a prompt, follow these steps.
1. Identify the task type
| Type | Traits | Template |
|---|---|---|
| Everyday | A question, brainstorming, a draft, a comparison, a small plan | Short prompt, 1–3 sentences |
| Deliverable | Multiple sources/steps, produces a file, shown to others | Full four elements + final check |
| Code | Working on code, fixing a bug, writing tests, refactoring | Behavior + repro/location + constraints + how to verify |
| Agent / system | System prompts, automation, scheduled runs | Four elements + approval boundaries + failure handling |
2. Fill gaps quickly
If the user hasn't given enough to pin down a key element, ask at most one most-important question (Audience? Purpose? What must not change?). When there's basically enough, just start — write your assumptions as annotations next to the prompt instead of asking round after round.
3. Produce the prompt
- Put the final prompt in a code block for easy copying.
- Write the prompt in the user's target language (English for English models/contexts; otherwise the user's language).
- Add 2–4 sentences of notes: why it's organized this way, where it can be trimmed or adjusted.
- For complex tasks, offer two versions: a lean one and a full one.
4. When optimizing an existing prompt
Diagnose before rewriting. Check for the common ailments, in priority order:
- Unclear result: lots of steps, but no statement of what to produce or for whom → rewrite around the result.
- Context noise: irrelevant sources/background stuffed in → keep only what changes the result.
- Missing boundaries: doesn't say what's off-limits or what needs approval → add the 1–2 that matter most.
- Over-control: every step nailed down, no room to adjust → delete procedural instructions, keep the constraints.
- No verification: an important task with no final check → add a closing self-check.
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.
- 12d ago First seen · 190 lines · 112 tokens per session scan A e20d885d8d19
prompt-craft-en is a skill published in the GitHub repository breeze-r/claude-prompt-craft-skill (11 stars, last pushed 2mo ago), licensed MIT. It adds 112 tokens to every session and 2,076 once invoked, about $0.0006 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 2026-08-30.
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