assurance

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that the search targets a public index, which usefully implies no authentication, but it does not disclose result shape, pagination, or how the limite parameter affects behavior.

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

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

A single, front-loaded sentence with no redundant wording. It communicates the resource, the action, and the topic scope efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple public search tool with read-only annotations, the core scope is mostly clear. However, with no output schema and no parameter documentation, the agent is left guessing about return format, limite semantics, and edge cases like empty results.

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

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

Schema description coverage is 0% and the description does not explain either parameter. 'requete' and 'limite' are inferable from their names and the search context, but no format, defaults, examples, or constraints are provided, so the description fails to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Recherche') on a specific resource ('l'index public des pages de ScoreProtect.fr') and narrows scope with content categories. This clearly differentiates it from sibling tools like simuler_cout_assurance_emprunteur or statut_produits.

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

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

There is no guidance about when to use this tool versus the siblings, no when-not-to-use conditions, and no mention of alternatives. The 'index public' phrase gives some context but does not help an agent choose between tools.

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

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

Annotations already mark the tool as read-only and non-destructive, so the safety profile is covered. The description adds that the tool produces total costs and an estimated savings figure, but does not disclose calculation assumptions, input constraints, or output format. With the annotation bar lowered, this is adequate but not rich.

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

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

The entire description is one front-loaded sentence that says exactly what the tool does and what it returns, with no filler. It is concise while covering the core purpose and output categories.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple four-number calculator, the description plus self-explanatory parameter names (capital, duration in years, rates as percentages) may be minimally sufficient, and it does state the two output categories. However, with no output schema, no parameter descriptions, and no mention of constraints or calculation basis, it leaves the agent to guess at currency, formula, and return shape.

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

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

Schema description coverage is 0%, and the description only hints that taux_groupe_pct/taux_delegue_pct correspond to bank vs delegated scenarios; it does not explain units, acceptable ranges, or the roles of capital and duree_annees beyond their names. Parameter names carry some meaning, but the description adds almost no semantic value over the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific action ('Compare') and identifies the exact resources: group borrower insurance vs delegated under the Lemoine law, along with outputs (total costs, estimated savings). This distinguishes it from the sibling 'simuler_cout_assurance_emprunteur', which appears to simulate a single cost scenario.

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

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

The purpose implies the tool is for comparing bank vs delegated rates, but there is no explicit statement of when to prefer it over 'simuler_cout_assurance_emprunteur' or when not to use it. No prerequisites or exclusions are given, so an agent must infer usage from the description.

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

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

Annotations already declare the tool read-only and non-destructive. The description adds useful context by specifying the content is public identity data (SIREN, ORIAS, categories) and frames it as a trust/verification resource, going beyond the annotation baseline.

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

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

The description is a single, focused sentence that front-loads the core purpose and immediately adds a practical use case. Every word earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only informational tool, the description is nearly sufficient. It names the key returned data categories and the anti-fraud purpose. It does not describe the exact return format, but with no output schema and such a simple tool, this is a minor gap.

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

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

The schema has zero parameters, so no parameter documentation is required. The description does not need to explain parameters and the baseline of 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource: the public identity of the publisher, including specific data points (TENDIL COURTAGE, SIREN, ORIAS, categories). It lacks an explicit verb like 'returns' or 'provides', but the intent is unambiguous and it is distinct from the sibling tools.

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

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

The description states an explicit use case: verifying that the site is not fraudulent. It does not mention exclusions or alternative tools, but the guidance is clear enough for an agent to know when this tool is relevant.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the claim 'Faits vérifiés' (verified facts), which is useful context about content reliability. However, it doesn't disclose return format, whether the output is a static summary, or any limits. It adds some value beyond annotations but not rich behavioral context.

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

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

The description is a single efficient sentence with topics clearly front-loaded and zero filler. It earns its place by enumerating the law's coverage. Minor deduction for lacking a clear verb, which makes it read more like a tagline than a functional statement, but there is no waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only fact tool, the description lists the covered topics adequately. However, the functional nature is ambiguous—it never states what the agent receives or should relay to the user (a summary, a fact sheet, a citation). Since there is no output schema to compensate, this gap matters and keeps it from being complete.

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

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

There are zero parameters, so the schema needs no description support; per the baseline, 4 is appropriate when no parameters exist. The description correctly does not attempt to document nonexistent parameters. Nothing is missing here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the specific resource (Loi Lemoine 2026) and lists its key topics (delegation, annual termination, equivalent guarantees, health questionnaire), which distinguishes it from siblings. However, it lacks an explicit action verb—there's no 'returns', 'explains', or 'provides'—so the description reads like a content summary rather than a functional spec. An agent can infer it's an information-retrieval tool but only indirectly.

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

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

No guidance is given on when to use this tool versus siblings like chercher_contenu (search content) or comparer_delegation_assurance (compare delegation). An agent cannot tell whether to pick this over chercher_contenu when a user asks about the law. The description provides no exclusions, conditions, or alternative names.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it computes total, average monthly, and first-year cost, which is useful output context, but it does not disclose behavioral traits such as rounding, assumptions about rate application, or limitations. It is consistent with annotations, so no contradiction, but it adds limited behavioral depth beyond annotations.

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

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

The description is a single, efficient sentence that packs the action, the resource, the outputs, and the inputs with zero waste. It is front-loaded with the verb and immediately communicates the core function, making it easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is a straightforward calculation with three parameters and no output schema. The description adequately explains the inputs and the expected outputs (total, average monthly, first-year cost), which is sufficient for an agent to invoke it correctly. It lacks details on calculation methodology or edge cases, but these are not critical for basic usage. Overall, it is complete for the tool's simplicity.

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

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

Schema description coverage is 0%, so the description must compensate. It explicitly names each parameter: capital, taux_annuel_pct (annual rate as a percentage of capital), and duree_annees (duration). It clarifies that the rate is a percentage and the duration is in years, which adds meaning beyond the bare schema types. However, it does not specify the currency for capital, leaving some ambiguity, hence not a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Calcule' (calculates) and the resource 'le coût d'une assurance emprunteur' (borrower insurance cost). It also specifies the exact outputs (total, average monthly, first year) and the inputs (capital, annual rate as % of capital, duration). This fully distinguishes it from siblings like 'comparer_delegation_assurance' (which compares delegation insurance) and other unrelated tools, leaving no ambiguity about its purpose.

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

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

The description explains what the tool does but does not explicitly state when to use it versus alternatives. It implies use when a cost calculation is needed, but there is no mention of exclusions, prerequisites, or alternative routing to sibling tools. The context is clear enough for an agent to infer usage, but explicit guidance is lacking.

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

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

Annotations already mark this as read-only and non-destructive. The description adds value by clarifying the exact kind of state ('canonical and verifiable') and what dimension is exposed ('distribution ouverte ou non'). No contradiction with annotations.

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

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

The description is a single, compact sentence with no wasted words. It front-loads the core purpose and lists scope explicitly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only status tool, the description covers the resource, the product scope, and the result dimension. It is complete enough for an agent to select and call it correctly, though slightly abstract terms like 'canonique' could be expanded.

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

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

The tool has zero parameters and schema coverage is 100%, so there is no parameter burden for the description to carry. The baseline of 4 applies because nothing is missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource: a canonical, verifiable status of ScoreProtect products, and enumerates the product categories. It also defines the key output dimension ('open distribution or not'). It lacks an explicit verb but is specific enough to distinguish it from the listed sibling tools.

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

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

The phrase 'canonical et vérifiable' implies this is the authoritative source for product status, and the product list gives a clear scope. However, there is no explicit guidance on when to use this tool versus alternatives like comparer_delegation_assurance or chercher_contenu.

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