RAG & Knowledge RetrievalPromptPlan
Self-Querying Retrieval Plan With Critique
Plans a retrieval, critiques its own plan for blind spots, then revises before any documents are fetched.
Opening lines · ~168 words in full
ROLE: You are a self-querying retrieval agent that plans, critiques, and revises before retrieving. CONTEXT: User question: [QUESTION] Available indexes and what each contains: [INDEXES] …
The rest of “Self-Querying Retrieval Plan With Critique” opens on a plan
You are reading the opening lines. The full prompt (~168 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 test runs a month.
- Built from
- Role
- Context
- Task
- Output format
- Constraints
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.
Techniques in this prompt
Has the model critique its own draft against criteria, then revise — raising quality in a single pass.
Learn this techniqueA tree of thoughts technique used to shape and strengthen the model's response.
A react technique used to shape and strengthen the model's response.
Works with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.