DatasheetVend

Extract analog domain specifications (ADC/DAC, Op-Amps, VREF)

datasheetvend_extract_analog_specs

Read-onlyIdempotent

Extract analog conversion and signal-conditioning specs: ADC/DAC resolution, sampling rates (MSPS/kSPS), channel counts, input-voltage ranges, static non-linearity (INL/DNL), dynamic specs (ENOB, SINAD, SNR, SFDR, THD), operational amplifiers (GBW, slew rate, rail-to-rail, CMRR/PSRR), internal voltage references (nominal voltage, tempco ppm/°C), and operating supply/temp envelopes, plus comparator propagation delay and hysteresis. Runs DatasheetVend Fast Extraction: a page scout routes targeted model reads and the module's own deterministic readers, then the same normalization and completion checks as a dashboard job finish the result, usually in seconds; engine names the engine on every result. If Fast Extraction cannot complete the module, the slower deep engine re-runs that module alone (engine.runtime is then monolith_rescue; the result says so, and it is billed as delivered). A rescue can take several minutes, so set a client timeout of 10 minutes. Only if the deep engine also cannot deliver does the module return status FAILED with the reason.

Input Schema

Name	Required	Description	Default
`partName`	No	Optional part number / MPN to disambiguate a multi-part datasheet.
`documentPath`	Yes	https:// URL to the datasheet PDF. The remote /api/mcp endpoint accepts ONLY https:// URLs (it downloads them); a local filesystem path works solely in local stdio mode (npm run mcp:serve).

Output Schema

Name	Required	Description
`engine`	No	Which engine produced this result
`review`	Yes
`status`	Yes	The module's completion status (for example approved, approved_with_warnings or empty), or FAILED when Fast Extraction could not extract the module
`contract`	Yes	Contract id, e.g. thermal_evidence_v2
`warnings`	Yes	Public engineering warnings from the extraction.
`module_id`	Yes	Canonical module id
`extracted_data`	Yes	The module's extraction after its own normalization — values with the datasheet page they came from (source_page, where one was recorded) and, where the module provides them, confidence_score and source_text_snippet.
`canonical_output`	Yes	The module's canonical (CAD-ready normalized) output block.
`engineering_summary`	Yes	Concise human-readable engineering summary, when emitted.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 30, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already establish read-only, idempotent, open-world behavior, and the description adds substantial operational context beyond them: Fast Extraction routing, deterministic readers, rescue fallback via `monolith_rescue`, billing as delivered, a 10-minute client timeout, and FAILED status if both engines fail. This is exactly the kind of behavioral disclosure an agent needs before invoking a potentially slow extraction.

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?

The description is front-loaded with the extracted specification categories, followed by operational details about Fast Extraction and rescue behavior. It is dense and somewhat long, but nearly every sentence carries useful selection or invocation information.

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?

Given an output schema, rich annotations, and a two-parameter input schema, the description is complete: it covers what is extracted, fallback behavior, timeout expectations, and failure semantics. An agent has enough context to invoke and interpret the tool correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so both `documentPath` and `partName` are already documented in the schema. The description does not add input-syntax or parameter-level meaning beyond that, so the baseline of 3 is appropriate.

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?

Starts with a specific verb and resource: 'Extract analog conversion and signal-conditioning specs.' It then enumerates the exact analog data domains (ADC/DAC, op-amps, VREF, comparators), which clearly distinguishes it from sibling extraction tools such as power, timing, and pinout extractors.

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

Usage Guidelines4/5

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

The analog-domain scope clearly indicates when this tool is appropriate versus the sibling extractors, but it does not explicitly state when not to use it or name a preferred alternative. Usage is strongly implied by the enumerated spec categories rather than phrased as direct routing guidance.

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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