diligence-research

name	diligence-research
description	Use when conducting research on AI infrastructure, semiconductors, memory/storage, datacenters, or hyperscalers using the Diligence Stack MCP server. Triggers on: 'search Diligence Stack', 'query Diligence Stack', 'fetch Diligence Stack evidence', 'find Diligence Stack reports', 'look up semiconductor / AI research'.
metadata	{"triggers":"search Diligence Stack, query Diligence Stack, fetch evidence, research semiconductors"}

Diligence Research

This skill directs the systematic retrieval, ingestion, and citation of institutional investment-research evidence from the Diligence Stack (Creative Strategies / Ben Bajarin) via its dedicated MCP server tools.

Procedure

1. Catalog and Constraint Discovery Before filtering by parameters, discover the current state of the authorized corpus to ensure searches use valid and current constraints. Call mcp__diligence-stack__list_catalog (with and without facet parameters) to retrieve the active date boundaries, valid knowledge bases, categories, and tickers. Never guess filter values.

2. High-Precision Evidence Searching Use mcp__diligence-stack__search as your primary entry point for finding specific claims, numbers, and excerpts. Keep queries descriptive, objective, and keyword-focused. Apply specific metadata filters. (See references/metadata-filters.md for details on structuring search constraints).

3. Fetching Un-truncated Evidence and Links Search results often return truncated summaries. Always use mcp__diligence-stack__fetch to retrieve the full, un-truncated derived text or media details behind specific evidence_ids. Crucial: Always include "original_link" in the include array (along with "text") to fetch the authenticated direct URL to the source report.

4. Deep Document Reading If a search result points to a highly relevant report or a specific section requires thorough reading, retrieve full document page ranges using mcp__diligence-stack__get_document. Specify the pages object with a strict from and to page range.

5. Financial Model Inspection When quantitative questions involve company models or market forecasts, use mcp__diligence-stack__list_financial_models to browse published financial workbooks. Use mcp__diligence-stack__read_financial_model with the exact modelSlug, datasetId and filters to pull clean, normalized data grids.

6. Attribution and Citation Every claim or quantitative figure extracted from the Diligence Stack must be cited properly. (See references/citation-rules.md for mandatory attribution, hyperlink formats, and how to handle estimates).

Resources

• references/metadata-filters.md — The strict definitions for search constraints (categories, tickers, publishers, evidence kinds) used in step 2.
• references/citation-rules.md — Mandatory formats for attributing claims, estimates, and providing authenticated links used in step 6.