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Check BOM

check_bom
Read-onlyIdempotent

Costs 2¢ per call. Check up to 50 BOM lines for lifecycle, stock against quantity, observed single-distributor sourcing, datasheet status and stale/missing prices. Accepts MPNs or LCSC numbers; duplicate MPN quantities are aggregated. Uses exact identities, catalogue snapshots and available distributor details. Unknown remains unknown; single_source does not prove only one supplier exists. Compact columns/rows by default; verbose returns objects. No extraction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linesYes
verboseNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / lines / maxItems
      Previous value: -20New value: +50
  2. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description adds real behavioral context on top: per-call cost, the 50-line limit, duplicate-MPN quantity aggregation, compact-vs-verbose output forms, and epistemic caveats ('Unknown remains unknown', 'single_source does not prove only one supplier exists'). That caveat is exactly the kind of semantic limit an agent needs and would not get from annotations.

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?

Dense and front-loaded with the cost signal, and nearly every clause carries information. A few clauses ('Uses exact identities, catalogue snapshots and available distributor details') are contextual filler, and the trailing 'No extraction.' is terse to the point of ambiguity.

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 describe returns, and it does via the compact/verbose distinction. Combined with cost, input limits, identifier semantics and result caveats, an agent has everything needed to call this tool correctly and interpret its output.

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 0%, so the description must carry the load, and it largely does: it defines what 'mpn' accepts (MPN or LCSC number), how quantities behave (duplicates aggregated), and what 'verbose' changes (compact columns/rows vs returned objects). It does not spell out the qty bounds (1–1e9) already in the schema, but the meaningful semantics are covered.

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 (Check) and resource (BOM lines) and enumerates exactly what is evaluated: lifecycle, stock vs quantity, single-distributor sourcing, datasheet status, stale/missing prices. No sibling is named explicitly, but the enumerated checks and the 'No extraction' note separate it from check_extraction_status, find_parts and compare_parts.

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 a clear operating context: cost (2¢ per call), a 50-line cap, accepted identifier types (MPN or LCSC number), and duplicate-MPN aggregation. It stops short of naming when to prefer a different sibling or stating exclusions, so it is strong context without routing.

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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