Vitef

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

Annotations already cover the safety profile (readOnly, idempotent, closed-world), so the description's added value is real: it discloses that distance, current fuel price and commune CFE rates are auto-filled, meaning the agent need not supply them, and it specifies a returned address that should be cited. Error behavior for an unknown slug is not covered.

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?

Three sentences, front-loaded with the verb and scope; the long parenthetical example list is informative but slightly overlong. The auto-completion and citation instructions are distinct, actionable sentences with no filler.

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 read-only, two-parameter compute tool with full schema coverage and rich annotations, the description supplies what the structured fields cannot: domain coverage, auto-filled inputs, and the fact that a detailed calculation page URL is returned (no output schema exists). Only failure/invalid-slug behavior is missing.

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 coverage is 100% and both parameters (slug, values) are documented in-schema, including the pointer to get_calculator/get_quote for field keys, so baseline 3 applies. The description's note that missing fields take defaults is reinforced by the schema but adds no key-level detail.

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 ('Exécute un calculateur ou simulateur Vitef') and enumerates concrete domains (salaire brut en net, indemnité de licenciement, frais de notaire…), so the agent knows exactly what the tool computes. It does not, however, distinguish itself from the similar-sounding estimate_quote or explain the split with get_calculator/get_quote, which is left to the schema.

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: run a calculation and cite the returned address. There is no explicit when-to-use, when-not, or routing to estimate_quote / get_calculator / list_calculators, so an agent facing a quote-like request has to guess.

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 readOnly, idempotent, non-destructive, non-open-world. The description adds useful context beyond that: the output is a tax-inclusive price range and a returned page through which the user can later obtain real quotes. Given there is no output schema, this return-oriented context is valuable, though it stops short of format/pagination detail.

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 sentences, with the core purpose front-loaded and the follow-up detail about real quotes second. No wasted clauses, though it could be slightly tighter.

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 read-only estimator with a nested values object and no output schema, the description covers what it produces (a price range) and what the return enables (real quotes via the returned page). Safety is covered by annotations. It is largely complete, missing only minor return-format specifics.

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 both the slug enum and the values object are already documented. The description only adds that fields follow get_quote, which is a mild pointer rather than new syntax or format meaning. Baseline 3 is appropriate when the schema does the heavy lifting.

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 gives a concrete verb+resource: it returns a price range (fourchette de prix TTC) for named service categories. It also distinguishes the estimate from real quotes ('la personne peut ensuite recevoir de vrais devis'), but it never explicitly contrasts itself with siblings like get_quote or compute_calculator, only noting the fields follow get_quote.

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 implied: this is a pre-quote estimate step and the fields come from get_quote. However, there is no explicit when-to-use-this vs when-to-use-an-alternative guidance, and no exclusions or prerequisites are 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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context beyond them: the input text is not retained ('Le texte n'est pas conservé') and the tool degrades to a bespoke letter when no template matches. It does not describe the shape of the returned match set.

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?

One dense paragraph that front-loads the core purpose before the domain list, the workflow instruction, and the privacy note. Every sentence carries information; the domain enumeration is the only slightly padded part.

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 covers what the agent needs: the input accepted (text or summary, French), the workflow position, the no-match fallback, and data-retention behavior. The only omission, the meaning of 'limit', is minor and bounded by the schema's default and range.

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 coverage is 50%: 'text' is documented in the schema and the description adds that a summary is acceptable and that the content must be French. The 'limit' parameter (default 3, range 1-5) is explained nowhere, neither in schema nor description, so the description only partially compensates for the coverage gap.

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: from the text of a received French letter, find the matching situation and the Vitef reply letter. It enumerates the covered domains (bailleur, employeur, banque, assureur, vendeur, amende, organisme) and the letter types (contestation, réclamation, demande de délai, résiliation), so the agent knows exactly what class of request it handles.

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?

Gives explicit downstream sequencing: 'Utilisez ensuite get_letter puis preview_letter avec les éléments du courrier', which positions this tool as the discovery step in a three-tool chain and distinguishes it from its siblings. It also states the fallback path ('Sans modèle adapté, la lettre sur mesure est proposée'), though it never states when not to use this tool (e.g. a letter that isn't a reply scenario).

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, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the payload content (field spec shape, calculation method, official sources), which tells the agent what kind of information it will receive and why it matters before computing.

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 sentences, front-loaded with the verb and the returned content, closing with the routing instruction. No filler, though the enumerated content list is dense and 'cas fréquents' is slightly vague, keeping it just short of ideal.

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?

No output schema exists, so the description carries the burden of describing returns, and it does so by enumerating the field spec, calculation method, official sources, and use cases. With one well-documented parameter and annotations covering safety, only finer details of return format are left unstated.

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 is a single parameter and schema description coverage is 100%, so the schema fully documents 'slug' including its source (list_calculators). The description adds no parameter-level detail, so the baseline of 3 for schema-driven params 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 opens with a specific verb and resource ('Décrit un calculateur Vitef') and then enumerates exactly what is returned: expected fields (key, label, type, options, default), calculation method, official sources, and common cases. It also differentiates itself from the sibling compute_calculator by positioning itself as the inspection step that precedes computation.

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 final clause 'À appeler avant compute_calculator' gives an explicit when-to-use and names the alternative tool, which is strong routing guidance. It stops short of an exclusion (e.g. what to do if you already know the field schema), so it is clear context rather than a full when/when-not rule set.

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 readOnly/idempotent/non-destructive, so the bar is lower. The description nonetheless adds real behavioral context beyond them: the returned page is where the letter is completed and sent by registered mail, which is downstream behavior an agent needs to know. It does not contradict the read-only annotation.

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?

Front-loaded with the verb and resource; the parenthetical enumerations of letter types and categories are useful rather than filler. The second sentence on the returned page is well placed, though the single dense block with three separate lists is slightly heavy.

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 carries the return-value burden and mostly does: it says what metadata is provided and that a usable page is returned for completing/sending the letter. The remaining gap is the absent differentiation from preview_letter and find_reply_letter in a crowded sibling set.

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 coverage is 100%, so the baseline is 3. The description enriches 'provider' with concrete known recipients (Free, SFR, EDF…), which adds a little meaning beyond the schema's 'Destinataire connu (slug)', but it gives no format, matching, or fallback guidance for the parameter.

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 gives a specific verb ('Décrit') plus a well-bounded resource ('un des 58 modèles de lettres conformes de Vitef'), enumerates the concrete letter types and the eight categories. It tells an agent exactly what it returns (applicable law, fields to fill, known recipients). It never explicitly distinguishes itself from siblings like preview_letter or find_reply_letter, which keeps it short of a 5.

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 mention that 'la lettre se termine et s’envoie en recommandé sur la page renvoyée' hints at the lookup-then-complete workflow, and the slug schema note points to search_services as the feeder. There is no explicit 'use this when…, use preview_letter when…' routing, and no stated prerequisites or exclusions.

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 cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds that the tool returns 'étapes et champs attendus' — a hint at output content that the annotations do not provide — plus the sequencing constraint. It does not describe the shape of the returned field list, which matters since there is no output schema.

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 purpose and the sequencing instruction are front-loaded and efficient, but the parenthetical list of sixteen devis types largely duplicates the enum values in the schema and inflates the sentence substantially. Roughly half the text is redundant with structured data.

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 one-parameter, read-only lookup with no nested objects, no output schema, and full enum coverage, the description supplies the two things an agent actually needs: what it returns ('étapes et champs attendus') and when to call it relative to estimate_quote. Little is missing, though a note on output shape would close the remaining 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?

Schema description coverage is 100% and the single slug parameter is a fully documented enum, so the schema carries the semantics. The description's service-domain list maps loosely onto the enum values but adds no format, casing, or fallback guidance beyond what the enum already enumerates. Baseline 3 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?

States a specific verb and resource: it 'Décrit une estimation de devis Vitef ... étapes et champs attendus', which is a concrete schema-introspection action rather than a restatement of the name. It is distinguishable from the sibling estimate_quote because it positions itself as the preparatory step. The exhaustive parenthetical list of devis domains adds bulk but not additional clarity about what the tool does.

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?

'À appeler avant estimate_quote' gives explicit sequencing and names the sibling alternative with the condition that selects it, so an agent knows exactly where this fits in the workflow. It stops short of stating when not to use it or what estimate_quote returns, but the routing intent is unambiguous.

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, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds meaningful context beyond annotations by stating the list contains 60 free calculators and exposes their slug identifiers.

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 definition is one front-loaded sentence with no wasted clauses. The count, 'gratuits', category examples, and slug mention all add useful information for selecting and interpreting the tool.

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 read-only list tool with one fully documented optional parameter and no output schema, the description provides enough context to call it correctly. A brief note on using get_calculator for individual records would make it 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?

The single optional 'group' parameter is fully documented in the schema, including the available group names, so schema coverage is 100%. The description does not mention filtering by group, but with full schema coverage the baseline score of 3 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 names a specific verb ('Liste') and resource ('calculateurs et simulateurs'), and adds useful scope: 60 free tools, example categories, and the returned slug identifier. It is clearly distinguishable from get_calculator, which by name suggests retrieving one calculator rather than listing all.

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 listing purpose implies when to use it, but there is no explicit guidance such as when to choose this over get_calculator, compute_calculator, or search_services. Usage is inferable from the description 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?

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered structurally. The description adds genuinely useful context beyond that: sender coordinates are excluded from the preview, and the PDF plus registered-mail sending occur on the returned page rather than as a side effect of this call. It stops short of describing pagination or return shape.

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 sentences, zero padding, with the core action stated first and the scoping/where-the-rest-happens caveat second. Every clause carries information an agent needs.

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?

There is no output schema, and the description partly compensates by explaining what the returned page is for (PDF and registered mail). Combined with full schema coverage of all three parameters, the definition is nearly sufficient; only the exact preview/return format is left unstated.

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 slug, values and provider are already documented in the schema (including the pointer to get_calculator/get_quote for field keys). The description only adds that sender coordinates are not among the supplied fields, which is marginal added meaning. 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 and resource: it drafts the text preview of a Vitef letter from field values. It also bounds the scope (no sender contact details) and clarifies that PDF generation and registered mailing happen elsewhere, which separates it from full-letter or send operations. It does not name a sibling directly, so differentiation is inferential rather than explicit.

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 implies this is the preview step before PDF/sending, but it never states when to choose it over siblings such as get_letter, get_calculator or estimate_quote. The cross-references to get_calculator/get_quote appear only in the schema, not in the description. Usage is implied 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?

Annotations already establish a safe, idempotent, closed-catalog read, so the bar is lower; the description still adds real value by naming the France-specific catalog scope, listing the covered content types, and specifying the return shape (titres, types, adresses des pages). It omits any note on how limit affects result volume, but that is minor.

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 core action is front-loaded in the first clause and the return format is stated in a short second sentence. The four quoted example queries are dense but each earns its place by teaching the expected input style.

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 usefully states what comes back (titles, types, page addresses) and covers the single required parameter's intent. Only the limit parameter's effect on results is left unexplained, which is a small gap for a two-parameter search tool.

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 coverage is 50%: query is documented ('La demande, en français') while limit is not. The description reinforces that the query is free-text natural language and French, which is genuinely useful, but adds nothing about the limit parameter or the maximum of 20 — the baseline 3 given partial 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?

States a specific verb (Cherche) and resource (catalogue Vitef) and enumerates the content types it covers — lettres, calculateurs, simulateurs, devis, outils — with four illustrative queries. An agent can identify it as the natural-language discovery entry point, though it never explicitly contrasts itself with the get_/list_ siblings that retrieve individual items.

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 through example queries like « résilier ma box Free » rather than stated. It never says when to prefer this over get_calculator, get_letter, or get_quote, nor that this is the first step before calling a specific retriever, leaving the agent to infer the routing.

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