llm-friendly-context
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
npx skills add shinpr/claude-code-workflows --skill llm-friendly-context --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.
# LLM-Friendly Context The goal is stable downstream execution: the next agent should know what to read, what to do, what counts as success, and when to stop or escalate. An active workflow's declared input contract is already optimized for its specialist. For that handoff, preserve the contract's named fields and declared value forms; the prompt consists of those fields and values. Apply the general prompt-composition rules below only when no input contract exists, and apply the generated-artifact rules to artifacts. ## Core Rules 1. **Use positive, executable instructions** - State what the next agent should do. - Convert quality policies into positive criteria. - Keep a prohibition only when it protects an irreversible boundary or shipped contract. Name the protected condition and the allowed action. - Example: "Preserve existing public API behavior across the documented compatibility cases." 2. **Make vague instructions concrete** - Replace subjective terms with observable conditions, paths, commands, schemas, examples, or decision rules. - Terms that often need clarification when they leave a decision to the next agent: `appropriate`, `proper`, `related`, `existing behavior`,
- Core Rules
- Rewrite Patterns
- Handoff Checklist
- Generated Artifact Checklist
What does the llm-friendly-context skill do?
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
How do I install it?
Run `npx skills add shinpr/claude-code-workflows --skill llm-friendly-context --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 shinpr/claude-code-workflows, a repository with 664 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.