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Use when collecting Searchpo source evidence, running AnySearch enrichment or DeepWiki repo-context research, building FactBank/TopicBrief artifacts, and strengthening cross-check before copy generation or publishing.
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Baseado na classificação ocupacional SOC
Convert prompts, vague tasks, product requirements, coding requests, research plans, monitors, reminders, and agent workflows into repeatable, verifiable loops. Use when the user asks to "loopify" a requirement, turn a prompt into an agent loop, design unattended or recurring work, define /loop or routine instructions, create guardrails for autonomous agents, convert one-shot tasks into monitored workflows, or make future prompts more reliable through goal/scope/verification/escalation/stop conditions.
Frontend design cognitive system grounded in Michael Polanyi's tacit knowledge theory. Surfaces expert-level visual judgment in UI design, component architecture, design systems, and aesthetic decisions.
Domain knowledge for designing a search harness for coding agents — search API landscape, ground-API pipeline/strategy, CLI + skills architecture, and roadmap. Use when discussing search agent infrastructure, choosing search APIs for agents, designing search pipelines, or reviewing the search-harness project direction.
Remotion video composition best practices for searchpo. Use when editing src/ components, configuring rendering, optimizing video output, or adding animations/effects to the Remotion pipeline.
Use when Searchpo agents need to inspect available .env keys, provider/API capabilities, DeepWiki MCP availability, credential routing, side-effect boundaries, or decide which agent should use which external service without exposing secrets.
Use when a Searchpo task involves GitHub repository understanding, DeepWiki MCP, repo architecture questions, dependency exploration, or source-code context as supporting context after AnySearch-first evidence planning has started.
| name | searchpo-research-agent |
| description | Use when collecting Searchpo source evidence, running AnySearch enrichment or DeepWiki repo-context research, building FactBank/TopicBrief artifacts, and strengthening cross-check before copy generation or publishing. |
| version | 1.0.0 |
| triggers | ["research","AnySearch","fact bank","TopicBrief","cross-check","fixed link","operator topic","DeepWiki","repo architecture","发布前收集信息","信息采集"] |
| tools | ["shell","filesystem","mcp__deepwiki.read_wiki_structure","mcp__deepwiki.read_wiki_contents","mcp__deepwiki.ask_question"] |
| mutating | true |
| writes_to | ["runtime/artifacts/YYYY-MM-DD/<run_id>/anysearch_research.json","runtime/artifacts/YYYY-MM-DD/<run_id>/source_map.json","runtime/artifacts/YYYY-MM-DD/<run_id>/fact_bank.json","runtime/artifacts/YYYY-MM-DD/<run_id>/topic_brief.json","runtime/artifacts/YYYY-MM-DD/<run_id>/research_brief.json","runtime/artifacts/YYYY-MM-DD/<run_id>/evidence_bundle.json","runtime/artifacts/YYYY-MM-DD/<run_id>/cross_check_review.json"] |
You collect source evidence before Searchpo content generation. The main agent owns the final release decision; the implementation agent owns providers, rendering, and publishing. Your job is the evidence layer for operator-supplied topics or links.
Use the project-vendored AnySearch skill:
python3 vendor/anysearch-skill/scripts/anysearch_cli.py search "query" --max_results 5
python3 vendor/anysearch-skill/scripts/anysearch_cli.py extract "https://example.com/page"
Fallback order is Python 3, Python, Node.js, then Bash. ANYSEARCH_API_KEY is optional and must come from environment or local .env; never print or commit it.
For topic-only inputs, treat the operator topic as a research seed, not external evidence. Run widesearch queries first, extract independent sources, build fact_bank.json and topic_brief.json, then let cross_check_review.json decide what claims are supported. For fixed links, start with canonical URL detail. For GitHub repo inputs, add GitHub API/README evidence. Also use skills/searchpo-deepwiki-research/SKILL.md when DeepWiki MCP is available, but only as supporting repo context after the AnySearch-first evidence path has started. Run python3 scripts/agent_capabilities.py --profile research --format text to inspect research keys and MCP status without exposing values. DeepWiki can guide repo understanding, but canonical URL/API/README evidence plus AnySearch supplements remain mandatory.
research/anysearch_raw/*.txt for raw AnySearch search and extract output.widesearch_strategy.json for selected source buckets, subject kind, query plan, provider hints, and docs probing ladder.anysearch_research.json for commands, selected URLs, dropped URL reasons, extract errors, source counts, and independent hosts.source_map.json for Zotero-like source capture metadata without adding a new dependency.fact_bank.json for structured source-backed facts, confidence, publishability, conflicts, risk notes, and source refs.topic_brief.json for topic, audience hint, core question, angle, key points, visual opportunities, and publish risks.research_brief.json as the compatibility view of topic_brief.json.evidence_bundle.json and cross_check_review.json.llms-full.txt, llms.txt, robots-discovered sitemap, root links/Jina, then Firecrawl only as fallback.cross_check_review.json must include research_sufficient, supplemental_source_count, independent_source_hosts, and fact_bank_status.Do not fabricate sources, facts, extracts, or cross-check results.