prompt-writer
Methodology for writing or improving prompts and system prompts that drive any LLM. Use when authoring or revising a prompt for a model task — grouping, classification, extraction, generation, copywriting, labeling, agent instructions, prompt templates, skill instructions — to decide how much to constrain the model based on the task type (open-ended vs single-correct-answer) and write the most fitting instructions. Triggers: "write a prompt", "help me write or improve a prompt", "how should I change this prompt", "this prompt isn't working", "write instructions for the model", "prompt-writer".
npx skills add hAcKlyc/MyAgents --skill prompt-writer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Prompt Writer A prompt's job is not to spell out every rule. The context window is a public good, so aim for the smallest set of high-signal tokens that maximize the likelihood of the output you want. The more rules you write, the more you box the output into the range of things you happened to think of. Assume the model is already very smart and only add context it doesn't already have — challenge every line: does this paragraph justify its token cost, or can I assume the model knows this? ## First, set the degrees of freedom The most important decision is how much latitude to give the model: match the level of specificity to the task's fragility and variability. Picture the model exploring a path. On a narrow bridge with cliffs on both sides there is only one safe way forward, so give exact instructions and specific guardrails — this is low freedom, and it fits schemas, data formats, migrations, API calls, anything where a small error makes the output unusable. In an open field with no hazards many paths lead to success, so give general direction and trust the model to find the route — this is high freedom, and it fits grouping, generation, copywriting, subjective judgment, any
- First, set the degrees of freedom
- Find the right altitude
- Principles for both modes
- Examples do more than rules
- High-freedom tasks
- Low-freedom tasks
- Review before you ship
- When a prompt isn't working
- Worked example: rules vs examples on the same task
- Source material
What does the prompt-writer skill do?
Methodology for writing or improving prompts and system prompts that drive any LLM. Use when authoring or revising a prompt for a model task — grouping, classification, extraction, generation, copywriting, labeling, agent instructions, prompt templates, skill instructions — to decide how much to constrain the model based on the task type (open-ended vs single-correct-answer) and write the most fitting instructions. Triggers: "write a prompt", "help me write or improve a prompt", "how should I change this prompt", "this prompt isn't working", "write instructions for the model", "prompt-writer".
How do I install it?
Run `npx skills add hAcKlyc/MyAgents --skill prompt-writer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From hAcKlyc/MyAgents, a repository with 795 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.