datasheet-lens

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manufacturer_check

Check each stored part's manufacturer against its datasheet, flag mismatches and distributor-name renames, and apply approved manufacturer updates to the team server.

Instructions

Check the manufacturer of each part of the store against its datasheet: the manufacturer of a part is the manufacturer of its datasheet, not the name of a distributor (older versions of adopt_part gave the name of the distributor). Gives the renames (the same manufacturer with the name of the datasheet), the parts whose datasheet gives a different manufacturer, and the parts whose datasheet names no manufacturer that the tool knows. Show the renames to the user, and apply them only when the user agrees. The changes go to the team server with the other changes of the store.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "manufacturer_check"
  }
}

Input Schema

Name	Required	Description	Default
`mpns`	No	With apply: only the parts with these MPNs (the renames that the user selects). Empty: all renames.
`apply`	No	False: only the check. True: do the renames of the check, after the user agrees.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.6.0Nov 10, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and mostly meets it: it discloses that the default mode is a non-mutating check, that `apply=true` performs renames, that changes propagate to the team server alongside other store changes, and that user confirmation is required. The only gap is that it does not describe failure behavior (e.g., parts with an unrecognized manufacturer) beyond listing them as a result category.

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 purpose and the definitional rule come first, and the parenthetical about older adopt_part versions earns its place by preventing a wrong assumption about the field's meaning. The middle sentence listing three result categories is somewhat dense, but no sentence is filler.

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?

An output schema exists, so return values needn't be spelled out, yet the description still usefully names the three result buckets, which helps an agent plan the confirmation step. Combined with the mutation and team-server-sync disclosure, this is nearly complete for a two-parameter check/apply tool, missing only error or partial-failure handling.

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 `mpns` and `apply` are already documented, including defaults and the empty-list-means-all case. The description's references to 'the renames that the user selects' and applying 'after the user agrees' reinforce but do not extend the schema, so the baseline of 3 applies.

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?

States a specific verb and object ('Check the manufacturer of each part of the store against its datasheet') and then defines what 'manufacturer' means here, including the caveat that older adopt_part returned the distributor name instead. That definitional detail lets an agent distinguish this tool from adjacent part-manipulation tools without opening their schemas.

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?

Gives explicit operating guidance: show the renames to the user and apply them only with user agreement, plus the implied check-then-apply workflow behind the `apply` flag. It stops short of naming a sibling to prefer for the related lookup (e.g., manufacturer_relation), so there is no spelled-out alternative, but the when-to-apply rule is unambiguous.

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