DatasheetVend

Extract thermal resistance and operating limits

datasheetvend_extract_thermal_limits

Read-onlyIdempotent

Extract thermal characteristics: junction-to-ambient (θJA) and junction-to-case (θJC) thermal resistance, power dissipation limits, and operating/junction/storage temperature ranges — with the datasheet page where one was recorded. 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

A4/5.0

Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations: it explains the Fast Extraction pipeline (page scout, model reads, deterministic readers), the fallback to the deep engine with engine.runtime = 'monolith_rescue', that rescue runs can take minutes and how they are billed, and that only a double failure yields status FAILED. This is exactly the latency/failure-mode information an agent needs.

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 the extracted fields, then the execution semantics. It is somewhat long and dense around the rescue engine, but every sentence carries actionable information (timeout, billing, failure status) rather than filler.

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?

With an output schema present, the description needn't detail return values, and it still covers provenance (datasheet page), engine labeling, timing expectations, and terminal failure behavior. Nothing an agent needs to call this correctly is missing.

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 coverage is 100% and both parameters (documentPath, partName) are fully documented in the schema, including the https-only constraint. The description adds no parameter-level meaning, so the baseline 3 applies.

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

Purpose4/5

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

The description opens with a specific verb+resource ('Extract thermal characteristics') and enumerates exactly which quantities are returned (θJA, θJC, power dissipation limits, operating/junction/storage temperature ranges). That field list implicitly separates it from siblings like extract_absolute_max and extract_power_domains, though those siblings are never named explicitly.

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

Usage Guidelines3/5

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

The description gives operational context (client timeout of 10 minutes, rescue behavior) but never states when to choose this tool over extract_absolute_max, extract_power_domains, or extract_analog_specs. Usage is only implied by the field list.

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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