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Prefetch Datasheets

prefetch_datasheets
Read-only

Free. Starts background extraction for up to 20 parts at once, e.g. a BOM, so they are ready before you read them. Returns immediately with each part's status. A new datasheet takes about 2.5 minutes at the median and 6.5 minutes at the 90th percentile; a cold GPU start can take about 12 minutes. These are estimates, not deadlines. Poll check_extraction_status (free). A part without a known datasheet comes back 'queued' while we look for its PDF, and reads 'resolving' until the search ends; only then is 'no_source' final: check the part number, or attach the PDF with request_datasheet_upload (org-private). The Free plan has a daily cap on new datasheets ('trial_limit'). MPNs or LCSC numbers only; resolve value-only BOM rows with search_parts first. Example: prefetch_datasheets(['TPS54302', 'ADS1115', 'LP5907']) datasheet_status: 'ready' → read it; 'extracting' / 'queued' / 'pending' / 'resolving' → poll check_extraction_status; 'not_extracted' → prefetch_datasheets; 'no_source' / 'unsupported' → request_datasheet_upload. Full list in the server instructions.

Input Schema

NameRequiredDescriptionDefault
part_numbersYes1-20 parts. Specific manufacturer part number (MPN) or LCSC number (e.g. 'TPS54302DDCR', 'C2837938'). Not a value ('100nF'), description or reference designator ('R1').

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / part_numbers / description
      Previous value: -"List of MPNs to prefetch (max 20). Must be specific manufacturer part numbers, not values or descriptions."New value: +"1-20 parts. Specific manufacturer part number (MPN) or LCSC number (e.g. 'TPS54302DDCR', 'C2837938'). Not a value ('100nF'), description or reference designator ('R1')."
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare the safety profile (readOnly/non-destructive), but the description adds substantial behavior beyond them: it is free, returns immediately with per-part status, median/p90/cold-start latency estimates framed as non-deadlines, a Free-plan daily cap surfaced as 'trial_limit', and the non-obvious lifecycle of 'queued' → 'resolving' → final 'no_source'. This is exactly the context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with cost and effect, then timing, then status routing. Dense and nearly every sentence earns its place, though the status-to-action mapping reads as a compressed run-on and could be split for scanability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must explain returns, and it does: every status value is enumerated with the follow-up action for each, and the polling tool is named. An agent has everything needed to call it and act on the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already documents the MPN/LCSC-vs-value distinction, so baseline is 3. The description adds real meaning on top: the BOM-scale use case, the value-only-row exception routed to search_parts, and a concrete example call with sample identifiers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific verb and resource ('Starts background extraction for ... parts') plus scope (up to 20 at once) and the motivating scenario (a BOM). It is immediately distinguishable from siblings like read_datasheet and check_extraction_status, which the description names.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use ('so they are ready before you read them'), when-not/input constraints ('MPNs or LCSC numbers only'), and a full alternative-routing map: poll check_extraction_status, resolve value-only rows with search_parts, attach PDFs via request_datasheet_upload for 'no_source'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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