perplexity-routing
Routing guide for selecting the correct Perplexity tool. Reference before spawning any Perplexity agent.
浏览 faisalanjum 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
26收录技能的仓库 Stars 合计
52仓库 Forks
26平均每个技能的仓库 Stars
2同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Routing guide for selecting the correct Perplexity tool. Reference before spawning any Perplexity agent.
SEC EDGAR filings search. Use for official regulatory documents.
Reference for all Alpha Vantage MCP tools. Use when exploring available data.
Consensus estimates and earnings data from Alpha Vantage.
Self-improvement protocol for Neo4j agents. Instructs agents to report skill updates needed.
Query earnings call transcripts, Q&A exchanges, and prepared remarks from Neo4j. Use when fetching transcript or earnings call data.
Run prompt with OpenAI or Gemini provider via agent CLI
Exhaustive multi-source research reports. Use for deep investigation.
Passthrough filter agent. Calls data sub-agents, validates responses, returns only clean data.
Test subagent resumption - call agent twice, verify context preserved
Query SEC filings (8-K, 10-K, 10-Q), extracted sections, exhibits, and financial statements from Neo4j. Use when fetching report/filing data.
Evidence citation and domain scope standards for Neo4j subagents. Prevents hallucination and ensures audit trail.
Run the same prompt with Claude, OpenAI, and Gemini in parallel, then return back exact replies you got back without modifying the results one bit.
Raw web search results (URLs, snippets). Use when you need a list of sources, not a synthesized answer.
Analyzes why stocks moved after 8-K earnings filings. Use ultrathink for all analyses. Invoke when asked to analyze stock movements, earnings reactions, or determine the primary driver of price changes.
Core Neo4j schema reference with all labels, relationships, data types, and indexes. Use when exploring database structure, checking field types, or understanding the financial knowledge graph schema.
Quick factual Q&A with citations. Use for simple lookups and single facts.
Predicts stock direction/magnitude at T=0 (report release). Uses PIT data only. Run before earnings-attribution.
Multi-step reasoning with Chain-of-Thought. Use for 'why' questions and comparisons.
Query XBRL financial metrics (EPS, Revenue, etc.) from Neo4j. Use when fetching structured financial data from 10-K/10-Q filings.
Builds and maintains cumulative guidance inventory for a company. Use when collecting historical guidance, updating guidance after earnings, preparing context for prediction/attribution workflows, or when user...
Analyzes why stocks moved after 8-K earnings filings. Use ultrathink for all analyses. Invoke when asked to analyze stock movements, earnings reactions, or determine the primary driver of price changes.
Query news articles from Neo4j with fulltext and vector search. Use when fetching news data or searching news content.
Master orchestrator for batch earnings analysis. Processes all 8-Ks for a company chronologically, running prediction→attribution loop with accuracy tracking.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。