AGENT SKILL

prompting

Use when writing, reviewing, or tightening a prompt, skill, agent, or system prompt for this marketplace: why a prompt opens with its purpose, how to write and use an iron law without misusing it, and maker notes on where models over- or under-do. Triggers: how should I phrase this prompt, tighten this system prompt, why does the model ignore this, should this be a rule, iron law, review this prompt, napis prompt. The quality bar for a skill is the skill-standards skill; the order of adding one is add-plugin.

License 许可
GPL-3.0
最近更新
2026-11-13
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01 前言 Front Matter

name
prompting
description
Use when writing, reviewing, or tightening a prompt, skill, agent, or system prompt for this marketplace: why a prompt opens with its purpose, how to write and use an iron law without misusing it, and maker notes on where models over- or under-do. Triggers: how should I phrase this prompt, tighten this system prompt, why does the model ignore this, should this be a rule, iron law, review this prompt, napis prompt. The quality bar for a skill is the skill-standards skill; the order of adding one is add-plugin.

03 SKILL.md 正文

Prompting

A prompt is a handover to a reader who has none of your context. It works when that reader knows why the task exists, what is out of scope and what done looks like, because then it decides well in the case the prompt never named. This guide is for the person who writes or reviews our prompts and wants to know why a line is there before how to phrase it. It is not a per-model rewriting manual: we keep no per-model table because we have measured none, and a table repeated from a vendor's page is a guess dressed as a rule. The shape of a skill is skill-standards.

Why before how

  • Open with the purpose. Who it serves, the outcome, what it refuses to do. The reader reads every later rule through that sentence, and a rule it cannot place is applied at random.
  • Give each instruction its reason. "Run the real path, because a green gate only reads files" lets the reader handle the near case; "always run the real path" is applied to a typo fix. A rule whose reason you cannot write is deleted.
  • Say what done looks like. Without it the reader stops early or never.
  • Ask for the smallest thing that does the job, and for end-to-end proof with the least work, never a test that restates the code. A reader that adds unasked tests, docs and refactors is doing what the prompt left open.
  • Prefer one positive example to a list of "never" lines. A prohibition tells the reader what to avoid and nothing about what to do.
  • Plain imperatives, no capitals for emphasis. Emphasis is read as "apply wider than you think" and the rule leaks into cases it was not written for.
  • A review prompt asks for every finding, then a second pass filters. "Only the important ones" is obeyed literally and finds less.

Iron laws

An iron law is a rule that holds every time, with no judgement left to the reader. Use one rarely.

  • It fits where a miss is expensive or irreversible and the line is crisp: no deploy of an unreviewed change, no secret in a commit, no write outside the worktree. If a judgement call is still needed, it is guidance, not a law.
  • Write it with its reason in one sentence: the law and the harm it prevents. The reason lets the reader see what the law is about, so it neither stretches it nor routes around it.
  • Enforce it where a miss is costly with a hook or a gate, and say so in the prompt. Prose is forgotten under pressure; a hook is not. The prompt then tells the reader why the hook exists, so a block is understood and not fought.
  • Keep the count small. Ten laws are ten places to pause, and the reader treats all of them as suggestions or stops on every one.

Misuse looks like this: a prohibition with no reason ("NEVER touch the database"), shouted, which makes the reader refuse the harmless read as well; "always ask before X" as a blanket, which makes an unattended agent stall; a law that is really a preference; and a law stated only in the prompt when a hook could hold it.

Maker notes

What we have seen models do when a prompt leaves a gap. These are observations to check against your own eval, not rules, and none is a claim about one model.

  • Recent models over-apply emphasis and over-read a prohibition; hard "never" boundaries make some stop and ask where the person wanted them to go on.
  • At low effort a model reports done without a real check, or adds tests, docs and files nobody asked for. Fix with a definition of done and "mention extras at the end", not with more emphasis.
  • A model told to verify, to think carefully or to use a subagent to check does so at a cost, even when it already would have. Add such a line only when an eval shows the miss.
  • A prompt written for a strong model may leave a smaller one without the steps it needs. Test on the model that will run it.

When a line is kept on a note like these alone, the eval has not run; say so. Behaviour changes with the model version, so the eval is the only record of what a line does.

Red flags

  • When a prompt is full of capitals and "never" lines, rewrite it as purpose plus reasons, because emphasis without a reason is applied too wide.
  • When a rule must hold every time and lives only in prose, name the hook that holds it, because prose is forgotten under pressure.
  • When you cannot write a line's reason, delete the line, because it is a habit and not a rule.

Say it in the reply

Per prompt: the purpose it now opens with, each rule kept with its reason in a clause, which rules are iron laws and which hook holds them, and what was deleted and why. Say what the eval has and has not measured.

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Use when running a web search through the person's own SearXNG instance with qsm-web searxng: choosing a search profile or engines, the instance, time range or language, reading its JSON, a suspended engine. Triggers: search with searxng, qsm-web searxng, search profile, niche search, academic search, IT search, vyhledavaci profil, searxng is down, which engines. The research loop around it is the web-ladder skill.

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Use when the source code of an open-source library or repository is needed on disk to read: the docs are silent, the behaviour must be checked in code, the version the project pins. Runs qsm-web opensrc get with a package spec or a repository address. Triggers: get the source of this package, clone this library, read the library's code, qsm-web opensrc, stahni zdrojak knihovny. Library docs are the Context7 skill; the research loop is the web-ladder skill.

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Use when one page needs a real browser through qsm-web browserbox: content built by script, a page that blocks plain fetching, a captcha to solve or hand to the person, a scripted sequence of clicks, a login the person is present for. Triggers: open it in a browser, the page is empty without JavaScript, captcha, take over the browser, run these steps on the page, log in to this site, browserbox. When to reach for a browser at all is the web-ladder skill.

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Use when the user wants a review of how they use Claude Code, or setup hands over after a first install: review my Claude Code usage, audit my setup, what does my setup cost, where did my tokens go, clean up my Claude Code, usage report, zkontroluj moje pouzivani. One walkthrough of four stages (machine, work, habits, extensions), questions after each, then one plan. A question about one topic (which hooks are slow) goes to that topic's skill; this session's tokens alone is `/qsm-usage`.

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