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Get competitor matched lines

get_competitor_matched_lines
Read-onlyIdempotent

Read visible competitor and matched-line fields. Use only for competitor-pricing questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoCategory name to narrow the visible lines to, as shown in the workspace.
entity_nameNoEntity name exactly as the user wrote it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesOne row per product line: sku, product, category, supplier, then the line's own measures.
scopeYesWhat population the rows were read from.
truncatedYesTrue when more rows matched than were returned.
populationNoPresent on an unfiltered read: a reminder the rows are a slice, not the whole business.
evidence_idYesHandle for these rows within this call's results. Not a citation.
completenessNoPresent when nothing matched: what the empty result does and does not mean.
returned_rowsYesRows in this response.
inputs_not_appliedNoInputs the snapshot could not apply.
source_evidence_idsYesWorkspace evidence IDs backing these rows. Empty when the source carries no evidence records.
total_matching_rowsYesRows that matched before any limit.
excluded_rows_without_metricNoRows left out of a ranking because they carry no figure for the metric.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and a closed-world scope, so the safety profile is fully covered elsewhere. The description adds only the "visible" qualifier, hinting at permission-filtered results — useful but thin given how little it explains about what is returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero filler, with the scope constraint placed immediately after the purpose. Every clause carries information.

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 need not be described, and both parameters are fully covered by the schema. For a low-complexity, two-optional-parameter read tool this is nearly sufficient; only sibling differentiation within a 27-tool family 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 description coverage is 100%, so both parameters (category and entity_name) are already documented in the schema with clear semantics. The description adds nothing about parameter behavior or the relationship between the two filters, 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 states a concrete verb ("Read") and resource ("visible competitor and matched-line fields"), which is more specific than the title alone. It does not, however, name a sibling or explain how it differs from tools like find_similar_products or compare_supplier_offer_history.

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?

"Use only for competitor-pricing questions" gives a clear when-to-use condition with an implicit exclusion of other question types. It stops short of naming an alternative tool for those other cases, so routing for adjacent tasks is left to inference.

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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