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Find Parts by Spec

find_parts
Read-onlyIdempotent

Find electronic components by function and numeric specs such as voltage, current, package, or stock. Apply constraints and rank pass, fail, or unknown evidence without validating design fit.

Instructions

Free. Find candidates by function and numeric specs with units, package or stock. Example: query='buck converter', constraints=[{parameter:'vin_max',op:'>=',value:'24 V'}, {parameter:'iout',op:'>=',value:'2 A'}]. Also accepts vds, rds_on, canonical parameter names and text constraints (interface contains I2C). Uses catalogue/JLCPCB parameters and DigiKey parametric filters when configured. Ranks pass/fail/unknown evidence; unknown is unverified. Values retain sources and test conditions. Compact columns/rows by default; verbose returns objects. Does not validate design fit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesFunction, e.g. buck converter, N-channel MOSFET, 6-axis IMU
packageNo
verboseNo
in_stockNoRequire positive stock observed within 24h; refresh at most six candidates.
constraintsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.4.0

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/openWorld safety, and the description adds real behavioral context on top: evidence ranking semantics (pass/fail/unknown, unknown = unverified), source and test-condition retention, compact-vs-verbose return shape, 'Free' cost signal, and the DigiKey/JLCPCB configuration dependency. This is meaningful disclosure beyond the structured fields.

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 cheapest useful fact ('Free') followed by the core action, and every sentence carries distinct information about constraints, ranking, or output format. It is dense and the inline example fattens the prose, but nothing is truly wasted.

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

Completeness4/5

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

For a 6-parameter filtering tool with no output schema, the description covers result ranking, evidence reliability, and return shape (compact vs verbose), which is what the agent most needs. Remaining gaps are minor: limit/pagination behavior and package filtering semantics are left to the schema defaults.

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?

With only 33% schema coverage, the description compensates well: it shows the constraints object shape via example, clarifies value format ('24 V', '10 mΩ'), mentions text operators like 'contains', and explains verbose toggles output objects vs compact rows. It omits semantics for limit (1-20, default 5) and leaves package unelaborated, so not quite a 5.

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?

States a specific verb+resource ('Find candidates by function and numeric specs') plus scope modifiers (units, package, stock) that differentiate it from a plain keyword lookup. It implicitly separates itself from check_design_fit via 'Does not validate design fit,' but never names search_parts or find_alternative, so sibling differentiation is incomplete.

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?

Provides a concrete usage example with query + constraints, explains what parameter naming schemes are accepted (vds, rds_on, canonical names, text constraints), and states a clear when-not boundary ('Does not validate design fit'). It stops short of routing the agent to alternatives like search_parts or find_alternative, so it is not a full 5.

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