datasheet-qa

Ingests hardware datasheets into a searchable knowledgebase and answers questions with citations.

1|Updated May 13, 2026
One-click install
npx skills add https://github.com/coolrobertj/Agency-Cowork --skill datasheet-qa-coolrobertj
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: datasheet-qa
Source: https://github.com/coolrobertj/Agency-Cowork/tree/main/skills/datasheet-qa/skills/datasheet-qa
Command: npx skills add https://github.com/coolrobertj/Agency-Cowork --skill datasheet-qa-coolrobertj

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Electrical engineers spend hours digging through 200-page PDF datasheets to find a single timing parameter, pinout, or power specification. This Skill converts datasheets into searchable markdown, indexes them, and answers natural language questions with citations to the exact source section. ## Core Features & Use Cases - Datasheet Ingestion: Converts PDF, Word, and Excel datasheets to clean markdown, classifies them into organized knowledgebase folders (SoC, System, Components, Firmware), and adds metadata headers with part number, manufacturer, and revision. - Indexed Q&A: Searches indexed datasheets via keyword and semantic search to answer questions about timing parameters, register maps, pinouts, thermal limits, and power specs, always citing the source file and section. - Cross-Part Comparison: Compares specifications across multiple indexed datasheets, such as DDR5 vs DDR4 power consumption. - Use Case: Ask "What are the I2C register addresses for the VRM?" and receive the register map with descriptions, cited to the exact datasheet section, rendered as an HTML table. ## Quick Start Ingest this DDR5 datasheet PDF into the knowledgebase and then tell me its maximum clock frequency.

Frequently Asked Questions about datasheet-qa

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search hardware datasheets with natural language?

Ingest the datasheet first so it is converted to markdown and indexed in the QMD knowledgebase. Then ask questions in plain language, such as maximum junction temperature or register addresses, and the skill retrieves matching sections with source citations.

How to convert a PDF datasheet to searchable markdown?

Provide the PDF file path, SharePoint link, or email attachment. The skill invokes the markitdown skill to convert it to markdown, adds a metadata header with part number and revision, stores it in the Specifications knowledgebase folder, and re-indexes QMD.

Can I compare specs across multiple datasheets?

Yes, once multiple datasheets are indexed, the skill can cross-reference them. For example, it can extract power tables from both DDR5 and DDR4 datasheets and present a side-by-side comparison with citations to each source.

What file formats does datasheet ingestion support?

The skill accepts PDF, Word, and Excel datasheets, converting them through the markitdown skill. Sources can be local file paths, SharePoint links, or email attachments.

What happens when a datasheet answer is not in the indexed files?

The skill explicitly states that the data is not available rather than guessing. It never fabricates specifications and always confirms which part and revision it is citing to avoid confusing specs across documents.

How are large datasheets over 500 pages handled?

Large datasheets may be split into logical sections before indexing to improve search recall. This ensures queries about specific parameters return the relevant section rather than losing precision in a single massive document.