Prompts
Prior-knowledge summariser
summarise prior knowledge from past programmes on a specific topic
Output: A structured summary of past programme learnings with patterns, contradictions, adjacent work, and source citations.
Paste into a CLARA-enabled chat
CLARA will confirm the route, ask for anything she still needs in one batched question, and show you the draft before filing.
Use CLARA's `prior-knowledge-summariser` for <programme name>.What CLARA will ask you for
- Programme name — your programme's name (e.g. SKYPROTECT).
- Track — the slice of the programme this artefact belongs to (workstream, capability area, feature line, etc.), or
Programme-wideif it spans tracks. - Topic — what topic or domain you're researching. Be specific: "scheduling operator interviews around shift patterns", not "user research".
- Inputs — CLARA will search the programme's Confluence space for past programme writeups touching the topic. You can also paste fresh material if it's not in Confluence yet.
Where the output lands
Knowledge Base/{{track}}/Prior-knowledge/{{topic}} inside your programme's Confluence space.
Tips
- Be specific with the topic. Broader queries return mush.
- If the response is shallow, follow up with: "Go deeper on the recurring patterns — what specifically were the failure modes?"
- Treat citations as the deliverable. If a finding has no citation, treat it as a hypothesis, not a fact.
- Confirm CLARA's source list before she generates the summary. Wrong pages picked up here cascade into every downstream artefact — catch it upfront.
Where this fits in the chain
Feeds into
The output of this prompt is consumed by these downstream prompts.
Heuristic evaluator
conduct a Nielsen heuristic usability evaluation of an existing product from screenshots, a live URL, or a PDF/deck — producing a scored, evidence-anchored report with per-heuristic compliance, severity-rated findings, and a prioritised remediation roadmap
Interview-guide generator
generate a field-ready interview guide that surfaces the data the team needs
Problem-impact ranker
consolidate the captured problems for a programme into a single ranked Problem-impact analysis — each problem scored on reach, severity, evidence and leverage, grouped into leverage tiers, so the team knows which problem to build for first
Research synthesiser
turn interview transcripts and field observations into a single Research synthesis page covering themes, friction, problem statement, and success criteria