HelpMyAgent

Compare French companies

company_fr_compare

Compares 2 to 5 French companies across public administrative, financial and legal-risk fields without producing a global winner. Use when: Compares 2 to 5 French companies across public administrative, financial and legal-risk fields without producing a global winner. Avoid when: Do not use this endpoint as a legal, regulated credit or guaranteed fraud-free decision unless explicitly stated otherwise. Limitations: Coverage depends on the public sources listed for this endpoint. Price: 0.030 USD per call via x402.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`identifiers`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`rankings`	Yes
`companies`	Yes
`limitations`	Yes
`comparability`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

AddedSep 6, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations are present but provide only generic hints (readOnlyHint false, destructiveHint false). The description adds valuable behavioral context: a limitation that coverage depends on public sources, a price per call, and a caution against using it for legal/credit/fraud-free decisions. No contradiction with annotations was found.

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

Conciseness3/5

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

The description is short and organized into labeled sections, but the 'Use when' field duplicates the opening sentence verbatim, wasting a section that could have offered alternative routing guidance. The remaining content is compact and front-loaded.

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 single-parameter tool with an output schema, the description covers the key aspects: what is compared, the non-winner behavior, limitations, and pricing. It does not explicitly name SIREN/SIRET as the identifier format, but the regex pattern covers that. The tool is simple enough that an agent can invoke it correctly with this description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%; the schema only provides a regex pattern for identifiers. The description does not explain that identifiers should be SIREN/SIRET numbers or how they map to French companies. It repeats the 2-to-5 bounds already present in minItems/maxItems, failing to compensate for the missing parameter documentation.

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?

The description states a specific verb ('Compares'), a bounded subject ('2 to 5 French companies'), and a clear scope ('public administrative, financial and legal-risk fields'). It also adds a key discriminator, 'without producing a global winner', which distinguishes this tool from benchmarking siblings.

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

Usage Guidelines3/5

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

The 'Use when' section is a verbatim repeat of the main description, adding no new guidance. The 'Avoid when' section gives a meaningful exclusion for legal/credit/fraud decisions, but does not explain when to choose this tool over related siblings like company_fr_benchmark or company_fr_peers. Usage context is implied rather than explicit.

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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TDQS

B3.3/5.0

Disambiguation3/5

Most endpoints target distinct resources, but several clusters are easy to confuse: company_fr_intelligence vs company_fr_kyb, company_fr_peers vs company_fr_competitors vs company_fr_public_contract_competitors, and company_fr_risk vs company_fr_default_score vs company_fr_payment_context. The descriptive names help, but the repetitive 'Use when' sections often restate the description rather than contrasting with nearby tools.

Naming Consistency4/5

The dominant convention is domain_fr_feature with consistent snake_case, e.g., company_fr_profile, company_fr_financials, company_fr_public_contracts, procurement_fr_search, which makes the family predictable. The three meta tools (describe_api, list_categories, search_apis) switch to a bare verb_noun style, and a few company_fr names use verbs while most use nouns, creating a minor inconsistency.

Tool Count2/5

With 30 tools, the surface exceeds the 25+ threshold and feels heavy for an agent to navigate, especially because aggregators like company_fr_intelligence and company_fr_kyb overlap with many single-purpose endpoints. The broad French-company data domain justifies a large number of endpoints, but several could be consolidated or split out to make the server more focused.

Completeness4/5

The set covers discovery, verification, profile, directors, financials, legal risk, compliance, public contracts, procurement, funding, benchmarking, signals, and aggregation, so core French-company workflows have no major dead ends. Minor gaps remain around beneficial-ownership/shareholder data and subscription-style monitoring, but those are explicitly outside the stated scope of most endpoints.

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