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 bastos/skills --skill write-a-promptgit clone --depth 1 https://github.com/bastos/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/bastos/skills/write-a-prompt)<a href="https://agentmods.dev/skills/bastos/skills/write-a-prompt"><img src="https://agentmods.dev/badge/skills/bastos/skills/write-a-prompt.svg" alt="Measured on agentmods" 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 | $0.00113 | $0.01206 |
| Opus 5 | $0.00056 | $0.00603 |
| Sonnet 5 | $0.00023 | $0.00241 |
| Haiku 4.5 | $0.00011 | $0.00121 |
Grade A, and why
write-a-prompt 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 8d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write a Prompt
Turn the user's intent and available context into one prompt they can paste into a new task. Do not execute the task described by that prompt.
Treat OpenAI's Prompting guide as the source of truth. Read the current page when web access is available and current guidance matters. Do not block prompt writing when the page is unavailable; follow the principles below.
Workflow
-
Determine the target surface.
- Use Chat for questions, ideas, short drafts, and everyday decisions.
- Use Work for multi-source, tool-using, multi-step, or larger deliverables.
- Use Codex for codebases, code changes, debugging, tests, and developer tools.
- Follow an explicitly named target. Otherwise infer it from the request without asking unless the choice materially changes the prompt.
-
Extract only context that can change the result.
- Carry forward relevant requirements, decisions, examples, reproduction steps, file paths, constraints, and unresolved facts from the conversation.
- Make the prompt self-contained when the target will not have access to this conversation.
- Name useful files, images, connected sources, or tools and say what to take from each.
- Omit irrelevant dialogue, obsolete directions, raw secrets, and unsupported assumptions.
-
Write from the result the user needs. Add only the useful parts:
- Goal: state the outcome first.
- Context: include information or sources that affect the result.
- Output: specify the audience, format, length, or detail level when useful.
- Boundaries: preserve the one or two constraints that prevent real problems.
- Verification: request a final check proportional to the task's importance.
Do not force these parts into headings or a rigid template. A short prompt is preferable when it is sufficient. Describe process only when the process itself matters.
-
Tailor the prompt to the task.
- For current information, request web search and source links.
- For Work, name the reviewable deliverable, relevant sources, audience, and approval boundary before sending, publishing, or changing shared information.
- For Codex, include the desired behavior, relevant code or reproduction, important compatibility constraints, and how to verify the change. Ask for a plan first only when the approach needs review.
- For important outputs, ask the target to flag missing or conflicting information instead of guessing.
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.
- 8d ago First seen · 104 lines · 113 tokens per session scan A 54ecc2342799
write-a-prompt is a skill published in the GitHub repository bastos/skills (7 stars, last pushed 1mo ago), licensed MIT. It adds 113 tokens to every session and 1,206 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 2026-08-31.
Other skills, from other repositories
prompt-engineering
Provides workflows to write, debug, and optimize prompts for LLMs, including few-shot example selection, chain-of-thought structuring, system prompt design, and template composition. Use when the user asks to write or improve a prompt, wants help with few-shot examples, chain-of-thought, system prompts, prompt…
loom-prompt-engineering
Designs and optimizes prompts for large language models including system prompts, agent signals, and few-shot examples.
image-prompt-optimizer
A skill focused on improving prompts for image-generation tools, with instructions covering its goals, process, outputs, and operating modes.
metaprompt
Generate a complete, ready-to-use prompt for a target model and harness. Triggers: metaprompt, generate a prompt for, write me a prompt, create a system prompt, prompt engineer this, optimize this prompt.
gh-issues
Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5]…
oracle
Best practices for using the oracle CLI (prompt + file bundling, engines, sessions, and file attachment patterns).