Chaletiste

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

Annotations already establish that the tool is read-only and idempotent; the description adds meaningful behavior by stating that it returns the applied rule, the processing delay, and service-public.fr sources, and that it reminds users the local PLU can be stricter. 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?

Three sentences carry the purpose, decision factors, outputs, and an important caveat with no filler. The most important information is front-loaded and every sentence earns its place.

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?

Despite having no output schema, the description states what is returned (rule, delay, sources) and which inputs influence the result. It does not spell out the exact thresholds or fully formalize the output structure, but it is complete enough for an agent to select and invoke the tool correctly.

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%, but the description adds decision logic beyond the schema: it explains that surface means the larger of footprint and floor area and links extension/PLU/protected-sector flags to the formalité outcome. This goes beyond the baseline of merely documenting parameter names.

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 precise verb, 'Indique la formalité d'urbanisme exigée...', names the resource ('chalet ou abri') and enumerates the possible outcomes ('aucune, dp, pc'). This clearly distinguishes it from sibling tools like get_chalet or search_chalets.

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 intended use is implied from the purpose: it answers what urban planning formality is required for a chalet/shelter. However, it never explicitly states when to call it versus alternatives and gives no exclusion or when-not-to-use guidance, so it stays at the implied-usage level.

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 the safety profile is covered. The description adds useful behavioral detail about what the comparison produces ('winners' per criterion), which goes beyond the structured annotations without contradicting them.

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 two sentences with no filler. The core action and constraints are front-loaded, and the long criterion list is compactly parenthesized rather than bloating the sentence.

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 single-parameter, read-only comparison tool with robust annotations, the description is complete. It specifies the model count, the criteria, the winner-selection behavior, and the user intent that should trigger it. No additional return-format detail is needed given the simple input and read-only nature.

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%: the only parameter 'ids' is described as 'Liste des id de modèles à comparer' with min and max constraints. The description reinforces the 2-to-6 limit and enumerates comparison fields, but it does not need to add meaning beyond the schema since the schema already fully documents 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 uses a specific verb ('Compare'), names the resource ('2 à 6 modèles côte à côte'), and enumerates the exact criteria compared (price, surface, insulation, etc.). It also clarifies the output behavior ('désigne pour chaque critère le modèle le mieux placé'), which clearly distinguishes it from siblings like get_chalet or search_chalets.

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 explicitly states when to use the tool: 'À utiliser quand l'utilisateur hésite entre plusieurs modèles ou demande « lequel choisir ».' This gives clear invocation context. It does not name exclusions or alternatives, so it stops short of a 5.

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?

Beyond the readOnly/idempotent annotations, the description discloses the exact outputs (total, low/high range, line-by-line detail, assumptions list) and the caveat that this is not a quote. It also surfaces key calculation rules like tax rates and the 5 m² exemption, adding substantial 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 dense but well-organized: purpose first, then components, then outputs, then the caveat. Every clause carries information needed for correct invocation, and nothing is redundant with the schema.

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 an 8-parameter tool with no output schema, the description adequately explains what will be returned, the assumptions to cite, and the key tax calculation details. The remaining parameter semantics are fully covered by the schema, so nothing essential 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?

The schema already covers all 8 parameters with descriptions, so the baseline is 3. The description adds meaningful domain logic—tax rates, exemption thresholds, and how components combine—which helps the agent understand parameter relationships beyond the 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 verb and resource: 'Estime le budget total d'un projet pour un modèle donné' and enumerates the exact cost components. It also distinguishes itself from request_quote by explicitly stating 'pas un devis', making its purpose unambiguous relative to siblings.

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 clearly frames when to use the tool: to estimate a project budget for a given model. It provides an explicit exclusion ('pas un devis') and instructs the agent to tell the user the estimate is indicative, but it does not name alternative tools or give detailed when-not-to-use conditions.

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 clear. The description adds that the tool returns 'contenu complet' and the id format, which is useful context, but it does not detail the exact return structure or error behavior. Given the annotation coverage, a 3 is appropriate.

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, concise sentence that immediately states the action and includes the essential id format. No filler or repetition, with the key detail front-loaded.

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 fetch tool with one parameter, no output schema, and annotations covering safety, the description adequately explains purpose, id construction, and relationship to search. It does not describe the return fields, but given the direct tie to search results and the simple nature, 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 input schema already describes the id as 'id renvoyé par search' (100% coverage), so the baseline is 3. The description enhances this by specifying the exact accepted formats ('chalet:<id>' or 'guide:<id>'), which is valuable guidance for constructing 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 clearly states the tool returns the full content of a search result, specifies the id format ('chalet:<id>' or 'guide:<id>'), and ties it to the search tool. This precisely distinguishes it from siblings like get_chalet or get_guide, which likely target a single type directly.

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 usage after a search by mentioning 'résultat de search' and the id format, but it does not explicitly state when not to use it or compare it with alternatives like get_chalet and get_guide. Guidance is present but minimal.

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?

Les annotations couvrent déjà la lecture seule, l'idempotence et la non-destructivité. La description ajoute utilement le périmètre détaillé du retour, les champs couverts et la présence de trois modèles similaires, ce qui va au-delà des 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?

La description tient en une phrase et chaque élément apporte une information utile, notamment la longue énumération des champs qui compense l'absence de schéma de sortie. La phrase d'usage est bien placée en fin, mais l'énumération rend l'ensemble un peu dense.

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?

En l'absence de schéma de sortie, la description liste de façon détaillée ce que renvoie l'outil et précise quand l'utiliser. Il manque seulement le comportement en cas d'identifiant inconnu ou des précisions sur d'éventuels frais, mais l'essentiel est couvert.

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?

Le schéma documente déjà l'unique paramètre id avec un exemple concret, soit une couverture de 100 %. La description ajoute seulement que l'id est obtenu via search_chalets, ce qui est un léger complément mais ne change pas le niveau de base.

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?

La description précise un verbe concret (« renvoie la fiche complète d'un modèle »), la ressource visée (un chalet via son id) et le contenu exact du retour. Elle distingue l'outil de search_chalets en indiquant que l'id provient de celui-ci.

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?

La description donne un contexte d'utilisation clair : « À utiliser avant de recommander un modèle précis ou de répondre à une question de détail ». Elle rattache aussi l'obtention de l'id à search_chalets, mais ne nomme pas explicitement d'alternative à éviter.

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. The description adds useful behavioral context beyond those annotations: it specifies the output composition and the default full=true behavior for including markdown. No contradiction exists.

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 two sentences with no filler. The first sentence front-loads what the tool returns, and the second gives the intended usage context. Every phrase earns its place.

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 only two simple parameters and no output schema, the description sufficiently explains the return value and default behavior for an agent to invoke the tool correctly. The id lookup is already handled by the schema's reference to list_guides. The phrase 'dépasse un modèle précis' is slightly vague but not a significant 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%: the id parameter is fully documented with an enum and a pointer to list_guides, and the full parameter is documented with its default. The description adds minimal parameter-level meaning beyond restating that full=true includes the full markdown text, so the baseline 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 states a specific verb ('Renvoie') and resource ('un guide'), and enumerates concrete output components: phrase-réponse, FAQ, dated sources, and optional full markdown. This clearly distinguishes it from sibling tools like search_chalets or compare_chalets, which have different purposes.

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 gives an explicit 'À utiliser pour...' condition covering regulatory, price, technical, and budget questions that exceed a precise model. It does not name sibling alternatives or state when not to use it, so it stops short of full exclusion guidance.

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, destructiveHint=false, and idempotentHint=true. The description adds that the tool returns a list with a sourced answer sentence and FAQ per guide, which is useful behavioral context about the return format. No contradictions.

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, front-loaded sentence that conveys the action, scope, and return content efficiently. The list of topics adds useful context without being verbose.

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 0 params, no output schema, and annotations covering safety, the description fully explains what the tool does, what it returns, and when to use it. Nothing essential is missing for correct invocation.

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 0 parameters and schema coverage is 100%, so there are no parameters to describe. Per the baseline for 0-param tools, a score 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 states a specific action (lists the 23 guides), enumerates the topics covered (authorizations, tax, price, etc.), and notes each guide includes a sourced answer sentence and FAQ. It clearly distinguishes from get_guide by implying this is a summary listing without loading the full guide.

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 'Souvent suffisant pour répondre sans charger le guide complet' provides clear guidance to use this tool when a quick answer is needed, implying get_guide is the alternative for full detail. It does not explicitly name alternatives or exclusions, but the usage context is clear.

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 description discloses the flow: the request is relayed to a seller or installer who recontacts the user, the tool requires explicit consent, and dry_run avoids sending. It also notes the tool is free and non-binding, and clarifies that Chaletiste does not sell chalets. This adds meaningful context beyond the annotations, which already flag non-read-only and open-world 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?

The description is moderately long but each sentence earns its place: purpose, consent conditions, dry_run, and cost/free nature. It is front-loaded with the core action and avoids fluff. Slightly verbose due to the repeated emphasis on consent, but still appropriately concise for a safety-sensitive 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?

Given the tool has 10 parameters, no output schema, and a non-read-only action, the description covers essential context: the process flow, prerequisites, dry_run option, and non-binding nature. It does not detail the exact response format, but for a side-effect action this is acceptable. Could elaborate on what happens if dry_run is false, but the overall picture is complete enough.

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 all parameters are self-documented. The description reinforces the consent requirement and dry_run usage but does not add new per-parameter semantics beyond what the schema already provides. It meets the baseline but does not exceed it.

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 action ('Transmet une demande de devis pour un modèle'), identifies the resource (a model), and clarifies the mediation role of Chaletiste. It clearly distinguishes this from sibling tools (search, compare, check_permit) by focusing on the quote request action.

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?

Explicitly states when to call the tool: only if the human user explicitly asked, provided their coordinates, and accepted their transmission. It also specifies that without consent the tool must not be called, and recommends dry_run for validation. This is strong, practical usage guidance.

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, idempotent, and non-destructive. The description adds beyond that by revealing the result is only metadata and that actual content requires a separate fetch call. This is useful behavioral context that the annotations don't provide, so the description earns a strong score.

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 three short sentences: the first states what it does, the second gives the return format and next step, and the third names the alternative. It is front-loaded with the most critical information and contains zero filler, making it concise and efficient.

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 search tool with no output schema, the description conveys everything needed: the resource scope, result fields, and the follow-up action (fetch). It also handles the decision point with search_chalets. The lack of pagination details is negligible for such a simple returned list.

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 already describes the single parameter as a natural language query or keywords, giving 100% coverage. The description adds no additional insight about the parameter itself; it focuses on output and follow-up steps. Per the rule, baseline 3 applies because schema covers the parameter fully.

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 tool performs full-text search on chalets and guides, and specifies the exact return format (id, title, url). It explicitly differentiates from search_chalets by naming it as the filtered alternative, leaving no ambiguity about the tool's scope.

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 provides direct instructions: use fetch with the id to get content, and prefer search_chalets for filtered queries. This gives explicit when-to-use guidance and names the sibling tool that replaces it for different needs, so the agent knows exactly how to route its request.

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 description adds substantial behavioral context beyond the readOnlyHint/idempotentHint annotations: it reveals that each result includes the price survey date, that 'assembly_estimated = true' means a Chaletiste estimate rather than a manufacturer figure, and that the urbanisme field uses codes (aucune, dp, pc). It also states that models missing the filtered data are excluded, which is a non-obvious behavior an agent must know before trusting result completeness. This goes well beyond what the annotations convey.

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?

Six dense sentences cover scope, filters, result shape, usage examples, exclusion behavior, and citation duty, with no filler. The first sentence quickly fixes the catalog size and categories, and each subsequent sentence adds a distinct operational fact. The length is proportionate to the tool's real complexity.

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?

Given 13 optional parameters, an exhaustive input schema, and no output schema, the description carries the full burden of explaining return value semantics and does so completely: result fields, interpretation of special flags, urbanisme codes, and the exclusion rule. It also provides the follow-up tool guidance and citation requirement. The only minor omission is an explicit contrast with the generic 'search' sibling, which is not material for correct invocation.

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 input schema already documents all 13 parameters at 100% coverage, so the baseline is 3. The description adds interpretive domain knowledge not fully present in the schema, such as wall-thickness meaning (28 mm storage, 44 mm three-season, 70+ habitable), the 20 m² permit threshold, and the meaning of dp/pc. It does not restate every parameter, but it enriches the most ambiguous ones.

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 concrete scope: searching among 'les 293 chalets en bois en kit' sold in France, with an explicit list of covered categories. It also names the downstream tools that consume the returned id (get_chalet, compare_chalets, estimate_total_budget, request_quote), which differentiates this search tool from siblings that act on an already-selected chalet. The first sentence alone makes the tool's purpose unmistakable.

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 gives explicit example queries that should route to this tool ('quel chalet de 20 m² à moins de 6 000 €', 'abri livré en moins de 3 semaines', 'chalet habitable en 70 mm'), telling an agent exactly when to invoke it. It also hints at the follow-up workflow by stating that the returned id should be passed to get_chalet, compare_chalets, estimate_total_budget, or request_quote. However, it does not explicitly state when NOT to use it or contrast it with the generic 'search' sibling, so it does not fully earn a 5.

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