菜单
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.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| 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.
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.