working-with-llms
Mandatory workflow for creating LLM-facing content. Follow the 4-step process (objective → draft → verify → adjust) before writing any prompt, skill, tool description, or system instruction. Triggers on requests to create or revise skills, prompts, agent workflows, or any content that will be sent to an LLM repeatedly.
npx skills add majiayu000/claude-skill-registry --skill working-with-llms-bearflinn-claude-stuff --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.
# Working with LLMs ## Workflow Follow this sequence for all LLM-facing content. Do not skip steps. ### Step 1: State the Objective Before writing anything, state the desired outcome explicitly in your response: ``` **Objective:** [One sentence describing what the LLM should do when this content is applied] ``` This checkpoint is visible to the user. Every instruction that follows must directly serve this objective. ### Step 2: Draft Write instructions that serve the objective. Draft as you normally would, but do not present to the user yet - the draft must go through at least one iteration/refinement step before presenting. ### Step 3: Verify Before presenting to the user, ALWAYS launch a sub-agent to explicitly verify draft contents against these criteria: - Is this actionable? (Commands behavior, not describes principles) - Does the model need this? (Would it behave worse without it?) - Each instruction is imperative (do X) not descriptive (X is important) - No speculative "don't" instructions - only prohibitions earned by observed behavior - Context directly serves the objective, not "nice to know" - If guarding against a pattern, there's an explicit verification step, not just
- Workflow
- Step 1: State the Objective
- Step 2: Draft
- Step 3: Verify
- Step 4: Make Adjustments
- Principles Reference
What does the working-with-llms skill do?
Mandatory workflow for creating LLM-facing content. Follow the 4-step process (objective → draft → verify → adjust) before writing any prompt, skill, tool description, or system instruction. Triggers on requests to create or revise skills, prompts, agent workflows, or any content that will be sent to an LLM repeatedly.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill working-with-llms-bearflinn-claude-stuff --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 majiayu000/claude-skill-registry, a repository with 534 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.