Prompt Cards

Draft a policy for paywalled/restricted content: detect paywalls, avoid bypass, rely on accessible sources, and suggest user-provided excerpts when needed. Include user messaging guidelines.

Create a plan for handling PDFs: downloading, parsing text, capturing page numbers, and generating citations. Include limitations and a quality checklist for extraction accuracy.

Design a content extraction module: boilerplate removal, main-content detection, metadata extraction (title/author/date), and language detection. Include fallback strategies for messy pages.

Plan a resilient fetching layer: retries, exponential backoff, timeouts, caching, and content-type handling. Include how to avoid hammering sites and manage 429/503 responses.

Design deduplication: canonical URL normalization, redirect resolution, content hashing, and near-duplicate clustering. Include evaluation metrics for dedupe accuracy.

Design a freshness strategy for research: recency-aware search, change detection, and update alerts. Include how to present “as of” dates and avoid outdated claims.

Create a source scoring rubric: domain trust, author expertise, citations, recency, and conflicts of interest. Output a weighted scoring model and how to tune it per domain.

Design a query planning module that expands a user question into search operators, sub-queries, and entity lists. Include multilingual support and query diversification strategies.

Draft a compliance-first plan: robots.txt handling, site terms, user-agent identification, rate limiting, and respectful crawling. Include an ethics checklist and escalation rules.

Create a selection matrix for available APIs: search/SERP providers, content extraction, crawling, and anti-bot friendly approaches. Compare cost, rate limits, coverage, and TOS constraints.

Design an end-to-end architecture for a research bot that uses web search APIs, page fetching, and summarization. Include modules, data flow, storage, caching, and citation strategy.

Create a 90-day plan to build a high-capability agent system using MCP and A2A: milestones, architecture decisions, eval harness, safety gates, and a pilot deployment. Include staffing assumptions and deliverables.