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faisalanjum AI Skills

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Browse published AI skills maintained by faisalanjum. Compare skill descriptions and follow each source repository for setup instructions.

Author statistics

Indexed skills

26

Repository stars across indexed skills

52

Repository forks

26

Average repository stars per indexed skill

2

Repository stars may repeat across skills from the same repository.

26 skills

Browse skills

GitHub

perplexity-routing

faisalanjum

Routing guide for selecting the correct Perplexity tool. Reference before spawning any Perplexity agent.

GitHub

skill-update

faisalanjum

Self-improvement protocol for Neo4j agents. Instructs agents to report skill updates needed.

GitHub

neo4j-transcript

faisalanjum

Query earnings call transcripts, Q&A exchanges, and prepared remarks from Neo4j. Use when fetching transcript or earnings call data.

GitHub

filtered-data

faisalanjum

Passthrough filter agent. Calls data sub-agents, validates responses, returns only clean data.

GitHub

neo4j-report

faisalanjum

Query SEC filings (8-K, 10-K, 10-Q), extracted sections, exhibits, and financial statements from Neo4j. Use when fetching report/filing data.

GitHub

evidence-standards

faisalanjum

Evidence citation and domain scope standards for Neo4j subagents. Prevents hallucination and ensures audit trail.

GitHub

multi-compare

faisalanjum

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.

GitHub

perplexity-search

faisalanjum

Raw web search results (URLs, snippets). Use when you need a list of sources, not a synthesized answer.

GitHub

earnings-attribution

faisalanjum

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.

GitHub

neo4j-schema

faisalanjum

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.

GitHub

earnings-prediction

faisalanjum

Predicts stock direction/magnitude at T=0 (report release). Uses PIT data only. Run before earnings-attribution.

GitHub

neo4j-xbrl

faisalanjum

Query XBRL financial metrics (EPS, Revenue, etc.) from Neo4j. Use when fetching structured financial data from 10-K/10-Q filings.

GitHub

guidance-inventory

faisalanjum

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...

GitHub

earnings-attribution

faisalanjum

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.

GitHub

neo4j-news

faisalanjum

Query news articles from Neo4j with fulltext and vector search. Use when fetching news data or searching news content.

GitHub

earnings-orchestrator

faisalanjum

Master orchestrator for batch earnings analysis. Processes all 8-Ks for a company chronologically, running prediction→attribution loop with accuracy tracking.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.