Explore Prompts

Design domain packs: specialized source allowlists, stricter citation rules, and domain-specific extraction (e.g., trials, filings). Include how to swap packs safely.

Create three output modes: executive brief (short), analyst memo (deep), and student explainer (teaching). Include structure, tone, and citation density rules for each.

Design hallucination controls: enforce evidence-only summarization, require citations for key claims, and label uncertainty. Include prompts and automated checks (linting).

Design evaluation metrics: search precision/recall, source diversity, citation correctness, and user satisfaction. Include how to create labeled datasets and measure improvements.

Create a testing strategy: unit tests for extractors, integration tests for API calls (mocked), and golden report tests to detect synthesis drift. Include CI gating rules.

Plan export: Markdown report, PDF generation, and CSV evidence table. Include how to preserve citations and embed “as of” timestamps consistently.

Design a user experience: question intake, clarifying questions, showing sources, evidence table, and exporting. Include interaction patterns for analysts vs casual users.

Design content versioning: snapshots, change logs, and references to “as of” dates for citations. Include retention and storage cost considerations.

Design incremental crawling: store ETags/Last-Modified, compute diffs, and update indexes incrementally. Include pitfalls and how to handle missing headers.

Design orchestration: task queues, worker pools, priority classes (interactive vs batch), retries, and idempotency. Include a simple architecture for cloud deployment.

Design caching: query result caches, page caches, and embedding caches. Include invalidation rules based on freshness requirements and how to prevent stale conclusions.

Build a cost model: per-query search API costs, per-page fetch cost, storage, embeddings, and LLM tokens. Provide formulas and a budgeting plan with guardrails.