CreditLabs

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real domain behavior beyond that: the schedule is indicative only, assumes a fixed rate, excludes insurance and fees, and the final payment is adjusted for rounding. It does not describe how rounding is applied or how the periods are laid out.

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 dense sentence with no filler: the output, the rate assumption, the exclusions and the last-payment adjustment are all front-loaded. Nothing could be removed without losing a constraint.

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?

With no output schema, the description must carry the return-value burden, and it does so only at a high level (monthly schedule, adjusted final payment). It omits the per-period breakdown (principal vs interest split), currency of the output, and the fact that a 30-year/20% cap applies. Adequate for a simple read-only calculator, but not fully self-contained.

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 100%, so each parameter (principal in euros to the cent, annual nominal rate not TAEG, integer duration) is already documented in the schema. The description adds only the fixed-rate assumption and confirms that insurance and fees are outside the calculation; it contributes no per-parameter meaning, so the baseline 3 applies.

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 a specific verb and output ("Produit un échéancier indicatif mensuel") plus the calculation mode ("à taux fixe") and explicit scope exclusions ("hors assurance et frais"). It is clearly distinct from a single-payment calculator, but it never names or contrasts with the sibling calculate_monthly_payment, leaving the differentiation implicit.

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?

Usage is only implied: the word "échéancier" suggests this is for full schedule generation rather than one payment, and "indicatif" signals a non-binding estimate. There is no explicit statement of when to prefer this over calculate_monthly_payment, and no prerequisites or exclusions beyond the fee/insurance caveat.

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?

The annotations already declare this as a read-only, idempotent, closed-world operation, so the safety profile is covered. The description adds the useful scope caveats that the result is indicative and excludes insurance and fees, but says nothing about precision, rounding, or whether the rate is applied monthly vs annually.

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 well-formed sentence with no filler, and the key qualifiers (indicative, excluding insurance and fees) are front-loaded. It is compact without being cryptic.

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 three-parameter, deterministic calculation with full schema coverage and no output schema, the definition states what is computed and what is out of scope. Only the return shape (single payment vs payment plus total interest) is left slightly ambiguous, though 'la mensualité et les intérêts' implies both.

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?

With 100% schema description coverage, the schema already documents principal in euros to the cent, the integer year range, and the nominal annual rate as a percentage that is not a TAEG. The description adds only the fixed-rate assumption, so it neither compensates for nor extends the schema meaningfully.

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 a concrete computation (monthly payment plus interest) on a specific resource type (fixed-rate amortizing loan) and bounds the scope (excludes insurance and fees). It does not, however, distinguish itself from the sibling calculate_amortization, which an agent could easily confuse with it.

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 on when to prefer this tool over calculate_amortization or the simulators listed as siblings. The only usage signal is implicit: it computes a payment rather than a full schedule, which the agent must infer.

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?

No annotations are supplied, so the description carries the disclosure burden. The 'get'/'Resume' phrasing signals a read-only summary and the exclusion of dossier submission reveals a boundary, but the description never says what the overview actually returns, whether it is cached/static, or how it relates to the other tools' data. Adequate but thin for an unannotated tool.

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?

Two short sentences, the summary statement front-loaded and the exclusion placed after it so an agent reads the purpose first. No filler, though the first sentence is a compressed content list rather than a full declarative statement of what the call returns.

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, no-output-schema tool the description is nearly sufficient: it names the scope and one prohibition. What is missing is a clear statement of the return content or shape, which matters more here because no output schema exists to describe the response.

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 takes zero parameters (empty object schema, additionalProperties false), so there is no parameter meaning to explain. Baseline 4 applies; the description correctly wastes no words on inputs.

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 pairs the verb 'Resume' (summarize) with the resource 'CreditLabs' and enumerates what the overview covers: credit business-introducer activity, editorial pages, and indicative simulators. That content list also implicitly separates it from siblings like list_editorial_sources and list_simulators, which expose individual sections rather than a whole-site summary, though the distinction is only implied.

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?

It gives one explicit negative rule: 'N'utilise pas cet outil pour deposer un dossier' (do not use this tool to submit an application/file). However, it never states the positive condition for choosing this tool over the sibling list_* or calculate_* tools, nor does it name an alternative for dossier submission, leaving the when-to-use guidance only half covered.

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?

No annotations are supplied, so the description carries the full behavioral burden. It discloses the backing endpoint (/api/ai/sources) and the nature of the payload (editorial URLs), implying a safe read, but says nothing about authentication, rate limits, pagination, or whether results are cached or localized.

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 filler; the resource and source endpoint appear immediately. It is efficient, though the brevity leaves no room for the differentiating detail an agent would want.

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-required-parameter read tool with no output schema and full schema coverage, the definition covers what the tool returns (citable editorial URLs) and where from. Only secondary details such as auth requirements or result ordering are absent, which is a minor gap at this complexity level.

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 100% and the single 'kind' parameter already enumerates hub, guide, observatory, simulator, barometer, avis, comparatif. The description merely echoes a subset of those values, adding no syntax, default-behavior, or multi-value semantics beyond the schema; baseline 3 applies.

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?

States a specific verb+resource: listing citable editorial URLs (guides, observatory, simulators) from the /api/ai/sources catalogue. That is concrete enough to distinguish it from get_site_overview, but it never explicitly contrasts with list_simulators, which overlaps on the 'simulateurs' content it names.

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 parenthetical categories imply when the tool is relevant (fetching editorial/citable links), but there is no explicit when-to-use or when-not-to-use guidance and no routing to siblings such as list_simulators or calculate_* tools. Usage is inferable rather than stated.

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?

With no annotations, the description carries the full burden: it adds a meaningful legal/interpretive caveat ("Une simulation n'est pas une offre de pret") that tells the agent these are indicative, non-binding entries. However, it says nothing about read-only behavior, whether the list is filtered or paginated, or what a simulator entry contains.

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?

Two short sentences with the resource description front-loaded and the caveat second. Nothing is redundant, though the second sentence serves more as a disclaimer than as operational guidance.

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 list tool this is close to adequate, but there is no output schema and the description never indicates what fields or how many simulators come back. An agent can decide to call it, but cannot anticipate the result 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate beyond confirming the call needs no input. Baseline 4 applies for a parameterless tool.

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?

States a specific verb and resource ("Liste les simulateurs indicatifs CreditLabs"), so an agent knows this is an enumeration of simulator entries, not a computation. It implicitly contrasts with the calculation siblings (calculate_amortization, calculate_monthly_payment) by framing the results as "indicatifs", though it never names those alternatives.

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 explicit when-to-use or when-not-to-use guidance and no mention of the sibling tools. The only usage signal is the caveat that a simulation is not a loan offer, which constrains interpretation of results rather than routing between tools.

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