Results for “graph-ranking”

Route business growth prompts to the right skills. Use when prompts mention fundraising, investors, market research, campaigns, SEO, lead intelligence, social graph ranking, connection optimization, sales outreach, or when the user wants an easy group invocation for growth skills.

Finds, scores, and reaches high-value contacts through social graph analysis and warm path discovery, generating personalized outreach drafts for email, LinkedIn, and X.

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Knowledge-graph-augmented retrieval. Entity and triple extraction, graph construction (Neo4j, LlamaIndex PropertyGraphIndex), hierarchical community summarization (Microsoft GraphRAG), personalized PageRank (HippoRAG), multi-hop traversal retrieval, and hybrid graph + vector pipelines. USE WHEN: user mentions "GraphRAG", "HippoRAG", "knowledge graph RAG", "entity extraction", "multi-hop reasoning", "Neo4j RAG", "LlamaIndex property graph", "LangChain graph retriever", "triple extraction", "community summarization" DO NOT USE FOR: vanilla vector RAG - use `rag-patterns`; multimodal inputs - use `multimodal-rag`; production indexing ops - use `rag-production`; hallucination checks - use `rag-guardrails`

Converts CSV, Excel, or JSON data into a polished, interactive visual report page with KPI cards, charts, data tables, and insights.

Analyzes .NET project code coverage and CRAP (Change Risk Anti-Patterns) scores to identify risk hotspots, methods blocking coverage gains, and prioritize where to add tests.

Compares Trailmark code graphs at two source code snapshots to surface security-relevant structural changes that text diffs miss, such as new attack paths, blast radius growth, and privilege boundary modifications.

Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula.

Rank a topic's user-flow branches by proof priority (value × risk × frequency) right after user-flow-map, ordering the branches, gating variation breadth, and promoting or pruning flows so state-model and ux-variations grow the tree in proof order — writes only existing flow-tree ordering fields, no schema change.

Assigns behavioral trust grades (A–F) to MCP servers by running probes for prompt injection, permission overreach, data leaks, and adversarial-input handling, and publishes reproducible onchain attestations.

Turn a pile of accounts into a stack-ranked priority list with a reason on every row. A layered score (gates first, then an evidence-weighted base rank over the signals you actually have, then bounded boosts for product usage and buyer intent) that stays fair across channels and never scores a blank field as a zero. Built for B2B GTM teams, customizable to your signals and your ICP. Trigger on "score these accounts", "rank by fit", "composite ICP score", "stack-rank my list", "who should I work first", "prioritize these leads", or any multi-signal account qualification.

Build structured knowledge graphs from unstructured text by extracting entities, mapping relationships, generating graph triples, and visualizing the result. Use when the user requests knowledge graph creation or provides relevant inputs for this workflow.

Reads existing per-leader research files to map co-authorships, endorsements, and organizational ties across movement leaders, producing a cross-leader network graph with clusters, bridges, and isolates.

Filters and ranks trending Hugging Face models, datasets, and spaces by novelty and significance, providing a 'why notable' explanation for each pick.

Codebase Memory — Knowledge Graph Tools

Live Upwork market research producing a ranked niche-opportunity dashboard. Use when the user wants to scan the Upwork market, find or validate a freelance niche, asks 'is there demand for X', wants competitor profile analysis, or needs rate observations for a niche. Triggers: 'research my niche', 'scan the Upwork market', 'is there demand', 'what should I specialize in', 'check the market', 'what do freelancers charge for X'.

Interactive knowledge graph analysis. Routes natural language questions to graph scripts, interprets results in domain vocabulary, and suggests concrete actions. Triggers on "/graph", "/graph health", "/graph triangles", "find synthesis opportunities", "graph analysis".

Creates a New York Times-style data chart frame with animated reveal, supporting line, bar, and range-band charts from CSV/JSON or a textual conclusion.

Monthly P&L, cashflow forecast, runway calculation, and top movers. Investor-ready Gamma deck plus Slack summary, archived to Notion. Runs monthly on a 1st-of-month cron schedule.

Provides a dashboard template for community/dating metrics with a navigation rail, ticker bar, headline KPIs, 30-day mutual-matches bar chart, and match-rate trend block.

Score, evaluate, and iteratively improve any content or strategy using an auto-assembled panel of domain experts. Handles copy, sequences, landing pages, strategy docs, titles, charts, recruiting evaluations, or anything else that needs a quality gate. Recursively iterates until all scores hit 90+ (max 3 rounds). Use when asked to: "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "which version is better", "expert score", "evaluate this copy/strategy/page", or when another skill needs a quality gate on its output. Also triggers on: "score this landing page", "expert panel these email variants", "rate this headline", "panel these charts".

AI 原生的潜在客户情报和外联流水线。用 agent 驱动的信号评分、共同关系人排名、暖场路径发现、来源语音建模和多渠道外联（邮件、LinkedIn、X），替代 Apollo、Clay 和 ZoomInfo。在用户想找到、评估并联系高价值联系人时使用。

Scores competitors across nine weighted dimensions with explicit 1–5 rubrics and a tension plot, producing comparable profile cards for competitive analysis.

This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.

Rank a backlog of feature ideas by impact, effort, risk, and strategic alignment to identify the top 5 to pursue.

DriveLM: Driving with Graph Visual Question Answering

Design grading plans. TRIGGERS - Use when user needs help with grading-plan related tasks.

Score and rank options contracts for any ticker using a multi-factor model covering liquidity, IV attractiveness, Greeks balance, and risk/reward. Returns scored option chains with the best contracts highlighted.

`task-agent`/`review-agent`: use when CPU, memory, I/O, database, network, rendering, or cost needs measured bottleneck evidence; skip without a profiling need.

Analyze weekly price charts for stocks, indices, crypto, or forex to identify trends, support/resistance, and probabilistic scenarios based purely on chart data.

Build quiz and assessment funnels that generate qualified leads through interactive scorecards, covering concept hooks, question design, dynamic results, and automated follow-up sequences.

Calculates IV Rank and IV Percentile for any ticker to determine whether implied volatility is high or low relative to its 252-day history, and provides trading signals based on IV zones.

Researching competitors and shaping positioning: feature matrices, SWOT, benchmarking, positioning maps, battle cards, win/loss, LLM brand visibility. Research only — use for strategy, not code.

Analyzes earnings-season implied volatility: historical IV crush, implied move forecast, IV Rank strategy tag, and a priced Iron Condor quote ready to trade.