Use when one prompt must give the same right answer across reruns, models, and pasted-in hostile input: forcing a fixed schema, picking the few-shot set, ordering the prompt blocks, or the inline cases you run while tuning. NOT the agent loop, tools, or retrieval (that is `building-agents`), NOT a standing CI eval harness (that is `agent-eval`).
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Prompt engineering: one robust prompt
You are tuning a single prompt so it produces the same correct output across reruns, across models, and against adversarial input. This is the craft layer — the prompt artifact itself: its block order, its few-shot set, its output contract, and the small eval that proves it. The systems layer (loop, tools, retrieval) is `../building-agents/SKILL.md`.
## Prompt skeleton (this order)
Order the blocks so the model reads identity and task before it sees the (untrusted) input. Each block earns its place:
1. **Role** — one line. Sets vocabulary and default behavior. Why: "You are a triage classifier" collapses a huge answer space cheaply.
2. **Task** — the imperative, singular. Why: one prompt, one job; split compound tasks into separate calls.
3. **Context** — the facts the model needs and nothing else. Why: extra context is extra distraction and extra tokens.
4. **Constraints** — phrased positively (do X), with the hard rules last so they stay in recent attention. Why: "respond only with the category" beats "don't explain".
…
The line at the top of this page pins the label git:20260729.bd66119, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_zzp33f2kodh3n4ik
GET https://markdownregistry.com/api/v1/resolve?ref=ericrisco/rsc-harness/prompt-engineering
GET https://markdownregistry.com/api/v1/blob/5cd81b97f2bad34f87f2e9931b6fb1f81456332042ff503104fb3311bdce3e6b
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
ericrisco/rsc-harness · skills/ab-testing/SKILL.md · Use when designing or analyzing a controlled experiment — falsifiable hypothesis, sample size from an MDE, reading…
ericrisco/rsc-harness · skills/accessibility/SKILL.md · Use when making a web UI conform to WCAG 2.2 Level AA — axe-core or Lighthouse a11y violations, keyboard operability…
ericrisco/rsc-harness · skills/ads/SKILL.md · Use when running or fixing paid acquisition on Google or Meta — campaign structure (Performance Max, Demand Gen…
ericrisco/rsc-harness · skills/agent-eval/SKILL.md · Use when measuring whether an LLM or agent system actually got better and gating merges on it: golden sets, fixing an…
ericrisco/rsc-harness · skills/agent-safety/SKILL.md · Use when bounding an LLM agent that already runs — scoping its task domain, gating tools to least privilege, defending…
ericrisco/rsc-harness · skills/ai-media/SKILL.md · Use when a creative goal must become a finished media file: pick and order generative-media models per modality — AI…
ericrisco/rsc-harness · skills/analytics/SKILL.md · Use when instrumenting product or web analytics — GA4/PostHog SDK wiring, event taxonomy, funnels, double-counted…
ericrisco/rsc-harness · skills/analyze/SKILL.md · Use when constitution, spec, plan and tasks all exist and you want them cross-read against each other before any code…
ericrisco/rsc-harness · skills/api-connector-builder/SKILL.md · Use when writing a client for someone else's REST or GraphQL API: auth flow choice and token refresh, pagination to…
ericrisco/rsc-harness · skills/api-design/SKILL.md · Use when settling the contract of an API you expose, before implementation: resources/URLs, REST vs GraphQL…
giuseppe-trisciuoglio/developer-kit · plugins/developer-kit-ai/skills/prompt-engineering/SKILL.md · Provides workflows to write, debug, and optimize prompts for LLMs, including few-shot example selection…
codealive-ai/ai-driven-development · skills/prompt-engineering/SKILL.md · Universal prompt engineering techniques for any LLM. Use when crafting, optimizing, or reviewing prompts for AI models…
doodledood/manifest-dev · claude-plugins/manifest-dev-tools/skills/prompt-engineering/SKILL.md · Create, update, review, or discuss an LLM prompt — a system prompt, a skill, or an agent. Use when writing or improving…
nahid-sparktales/agent-dispatcher · skills/ai/prompt-engineering/SKILL.md · Write or revise a prompt so it holds up — output contract, instruction placement, examples that earn their place, an…
vodailocz/kilo-kit-mcp · skills/engineering/prompt-engineering/SKILL.md · Use when designing, optimizing, testing, or deploying robust prompt systems for AI agents. This skill provides…
