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Match suppliers

match_suppliers

Sets the SUPPLIER on every expense that has none; it never touches bank transactions or reconciliation, so to link entries to bank lines use match_transactions instead. It dedupes the supplier records first, then lets SuperCat predict each expense's supplier (canonicalised to the dedupe-group leader). Only proposals that clear SuperCat's strong-prediction bar (confidence >= 0.75 AND topsim >= 0.4 AND (support >= 2 OR topsim >= 0.85)) are auto-applied; weaker guesses are surfaced for confirmation, not applied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only say it is a non-destructive write. The description goes far beyond that: it discloses the dedupe-then-predict pipeline, the exact confidence/topsim/support thresholds for auto-application, and that weaker predictions are surfaced but NOT applied — critical for an agent to know the tool will not silently guess.

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 core action and the sibling exclusion before the threshold mechanics. Dense but every clause earns its place; the nested boolean threshold expression makes it slightly heavier to parse than ideal.

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?

For a zero-parameter mutation with no output schema, the description covers what is modified, what is explicitly untouched, the algorithm's effect on supplier canonicalisation, and the auto-apply vs. propose-only split. Nothing an agent needs to decide or call correctly is missing.

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?

The tool takes zero parameters, so the schema carries no semantics to add. Baseline for a parameterless tool is 4; the description correctly avoids inventing parameter details.

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 precise verb+resource+scope: it sets the supplier on every expense that has none. It also explicitly distinguishes itself from the sibling match_transactions, so an agent can route correctly without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit when-not and names the alternative: it never touches bank transactions or reconciliation, so bank-line linking goes to match_transactions. The scope boundary is unambiguous.

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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