Projet Ariane — Orientation

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful context about what the tool returns (ranking details, link to school sheet) and its data source, which helps an agent understand the output without needing to call it. It does not contradict annotations and adds value beyond the structured fields, so a 4 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, well-structured sentence that front-loads the purpose ('Palmarès des lycées... et des collèges') and then efficiently lists scope and content. There is no redundancy or fluff; every clause adds information. It is appropriately concise for the tool's 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?

The tool has five parameters, one required, with 100% schema coverage and no output schema. The description covers the purpose, scope, content of the result, and data source, which is sufficient for an agent to invoke it correctly. It could explicitly state that the output is a list of establishments, but that is implied by 'palmarès' and the listed fields. Given the read-only nature and schema richness, this is nearly 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?

Schema description coverage is 100%, so all five parameters are already documented in the input schema. The description mentions the scope (national, department, city) which maps to parameters but does not add syntax or semantics beyond the schema's existing descriptions (e.g., precedence, defaults). Thus a baseline of 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 clearly states the tool provides rankings ('Palmarès') of high schools and middle schools, with specific content (rank, success rate, added value, link to school sheet) and scope (national, department, city). It names the data source (DEPP/Projet Ariane) and distinguishes itself from sibling search tools by focusing on rankings rather than lookup.

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 implies when to use it (when a ranking of schools is needed) and provides context about the scope options (national, department, city). However, it does not explicitly mention alternatives or when not to use it, nor does it reference sibling tools like rechercher_ecole. This is a clear context without exclusions, earning a 4.

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. The description adds useful behavioral context beyond that: past events are never returned, data comes from Projet Ariane and OpenAgenda, and results include dates, lieu, and registration link. This sets accurate expectations for an agent.

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 compact: one substantial sentence plus one sharp exclusion sentence. It is front-loaded with the main action and each clause adds distinct information without 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 read-only list tool with six optional, well-described parameters and no output schema, the description covers scope, supported filters, output elements, data sources, and a key behavioral guarantee. An agent has enough context to invoke it 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 description coverage is 100%, so the baseline is 3. The description adds value by grouping filters into meaningful dimensions ('par ville ou département, type et horizon') and indicating result content. It does not repeat every parameter detail, but the schema already documents limite and recherche well.

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: 'Liste les événements d'orientation à venir.' It names the event subtypes (JPO, salons, forums, ateliers, conférences), the available filters, and the output fields. This clearly distinguishes it from sibling tools, which target classements, fiches, and searches, not events.

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 clear context for when to use the tool: to list upcoming orientation events by city/department, type, and horizon. It also adds an exclusion ('Ne rend jamais un événement passé'). It does not explicitly name alternatives, but none of the siblings cover events, so the intended use is obvious.

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 behavioral context by specifying the exact content of the returned record (description, montant, profils éligibles, liens officiels) and the data source (Projet Ariane), which goes beyond the 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, front-loaded sentence that states the action and the key content without any filler. It is 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?

With only one parameter, no output schema, and simple annotations, the description is complete for an agent to invoke correctly. It tells what the tool returns and from where, and lists the fields included, which is sufficient for a retrieval 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?

The input schema provides 100% coverage for the single parameter slug, including an example. The description adds no additional parameter meaning beyond what the schema already states, so the baseline of 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 clearly states the tool returns the complete record of a financial aid, listing the specific content (description, amount, eligible profiles, official links). This distinguishes it from sibling fiche tools for schools, formations, and métiers, which are separate resources.

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?

While the description doesn't explicitly state when to use this over alternatives, its purpose is unambiguous: it is the tool for retrieving a full financial aid record by slug. The sibling list includes rechercher_aides, which implies this is for direct lookup of a known aid, but the description itself doesn't mention that contrast.

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 safety. The description adds context about the data content, including conditional bac results for lycées and the Projet Ariane data source. However, it does not mention potential limitations, error conditions, or rate limits, which are minor given the read-only nature.

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 sentence that front-loads the main action and efficiently lists the types of data returned. There is no filler or redundancy, making it highly concise and well-structured.

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 there is no output schema, the description compensates by enumerating the types of data returned (campus, addresses, formations, selectivity, bac results). It also hints at conditional content for lycées. While it could specify the structure more, it is sufficiently complete for an agent to understand what to expect.

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% for the single parameter 'slug', which is well-documented in the schema as the URL identifier returned by rechercher_ecole. The description does not add any additional meaning beyond what the schema already provides, so it stays at the baseline.

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 fiche of an establishment and enumerates its content: campus, addresses, formations with Parcoursup selectivity, and bac results for a lycée. This is specific and distinguishes it from sibling tools like fiche_formation and fiche_metier.

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 does not explicitly state when to use this tool versus alternatives. The input schema's parameter description mentions the slug is returned by rechercher_ecole, implying a workflow, but this is not in the tool description itself. Usage is implied rather than explicit.

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

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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context by naming the specific datasets returned and the time scope ('derniers millésimes', 'données Projet Ariane'), which goes well beyond the 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, well-structured sentence: the verb and resource come first, followed by a colon and a compact enumeration of the returned content. Every part adds information and there is 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?

The description enumerates the main return content well, but there is no output schema to fall back on and the schema marks 0 required parameters. The description does not clarify that id or slug should normally be supplied to retrieve a specific fiche, nor what happens if neither is provided. This leaves a real invocation ambiguity.

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 both id and slug are already documented with their meaning and source (rechercher_formation). The main description does not add new parameter-level meaning beyond clarifying that the tool returns a formation fiche, 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 opens with 'Retourne la fiche d'une formation' and lists the exact contents returned (établissement, diplôme, statistiques Parcoursup, insertion, métiers visés). This makes the tool's purpose concrete and differentiates it from sibling tools like fiche_ecole or fiche_metier, which target different entities.

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 detail-view counterpart to rechercher_formation, and the parameter descriptions mention that id/slug are provided by rechercher_formation. However, there is no explicit statement of when to choose this tool over a sibling or of the condition 'use after a search'.

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 this as read-only and non-destructive. The description adds meaningful behavioral context by specifying exactly what the tool returns and its data source, which is especially useful given there is no output schema. It does not address missing-slug or error behavior, but that is a minor gap for a safe lookup 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?

The description is a single front-loaded sentence with no filler. The verb and object appear first, and the parenthetical lists the returned content economically. Every element 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?

For a simple one-parameter, read-only lookup with complete schema coveragechers, the description is largely adequate: it states the return sections, the source, and the required identifier. The only notable gap is that it does not explicitly instruct the agent to use rechercher_metier when the slug is unknown, which would strengthen guidance.

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 single required slug parameter is already well documented with an example ('infirmier, developpeur-web'). The description adds no additional parameter-level meaning, so 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 states a precise verb and resource: 'Retourne la fiche complète d'un métier' and enumerates the contained sections (description, rémunération, marché de l'emploi, formations associées). It clearly distinguishes this from sibling tools by resource type (métier vs école, formation, aide) and by 'fiche complète' versus search-oriented tools like rechercher_metier.

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 use case is implied rather than explicit: the slug parameter and the notion of returning a complete fiche suggest the agent should call this when it already knows the métier identifier. However, the description does not name alternatives or state when not to use it, leaving sibling differentiation largely to inference.

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 read-only and non-destructive nature of the tool. The description adds a useful data-source context ('données Projet Ariane') and indicates the result is a list, but it does not disclose output format, pagination, or any special query behavior. 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?

A single, compact sentence that front-loads the action and object, then adds the scoping condition and data source. No filler or redundant phrasing.

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 well-described parameters, the description plus schema is largely sufficient. The main gap is that it does not explicitly state that at least one of metier or domaine should be used, and it does not describe the shape of the returned list, though 'Liste' implies a list of diplomas and formations.

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 documents both parameters fully, so the baseline is 3. The description adds semantic value by framing metier and domaine as alternative search dimensions ('un métier donné ou à un domaine'), which clarifies the intended relationship between the two optional parameters.

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 ('Liste'), names the resource ('diplômes et formations'), and clearly scopes the result to a given métier or domaine. This distinguishes it from sibling tools like rechercher_formation and fiche_formation, which target formation lookup or detail rather than mapping a job/domain to training paths.

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 a clear usage context: use it to discover diplomas and formations for a target job or professional field. However, it provides no explicit guidance about when not to use it, no mention of alternatives like rechercher_formation or fiche_formation, and no clarification about whether at least one parameter must be provided.

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 that the tool returns a list with amounts and links to fact sheets, which is useful output context. However, it does not describe pagination, sorting, or behavior when no results match. Given the annotations cover the main safety aspects, 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, well-structured sentence that front-loads the core purpose and then states the output. No filler or redundant information. It is appropriately concise and immediately actionable.

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 description covers the tool's purpose, the input requirement (free-text situation), and the output format (list with amounts and links). There is no output schema, so the description must convey what the agent will receive, which it does. It does not mention the optional 'categorie' parameter, but that is documented in the schema. For a search tool with only two parameters, this is sufficiently 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 input schema has 100% description coverage, documenting both 'categorie' (with accepted values) and 'situation' (with max length). The description adds minimal parameter meaning beyond the schema, only reiterating that 'situation' is free text. With full schema coverage, the baseline of 3 is correct.

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 'Trouve' and the resource 'aides financières', with concrete examples (bourses, aides au logement, mobilité). It distinguishes itself from sibling tools by targeting financial aids specifically, while other 'rechercher_*' tools cover articles, schools, formations, etc. The purpose is unambiguous and immediately recognizable.

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 specifies the usage context: 'correspondant à une situation décrite en texte libre', which tells the agent it expects a free-text description of a person's situation. It does not explicitly name alternative tools or exclusion conditions, but the siblings are clearly for different resource types, so the intended use case is clear. This counts as clear context with no exclusions, matching a 4.

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 le profil sécurité (readOnlyHint=true, destructiveHint=false, openWorldHint=false), donc la barre est plus basse. La description ajoute du contexte comportemental utile : l'ordre des résultats ('classés par pertinence') et la composition du retour ('avec lien vers l'article'). Aucune contradiction avec les 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?

Une phrase unique d'environ 24 mots où chaque segment apporte une information : type de contenu, éditeur, domaine thématique, modes de recherche, tri, lien de sortie. Aucun remplissage, et l'information clé ('Trouve des articles et guides') est en tête.

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?

Pas de schéma de sortie : la description assume l'essentiel du retour ('avec lien vers l'article') mais ne précise pas la structure complète des résultats ni le comportement en cas de zéro résultat. Comme l'outil est simple, les paramètres à 100 % couverts et les annotations sécurité présentes, la description reste quasi suffisante.

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?

La couverture du schéma est de 100 % : les trois paramètres (recherche, tag, limite) ont déjà leur propre description dans le schéma. La mention 'par mots-clés ou par tag' ne fait que reformuler ces descriptions sans ajouter de sémantique nouvelle (format attendu, défauts, exemples supplémentaires). Baseline 3 justifié.

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?

Le verbe 'Trouve' est spécifique, suivi d'une ressource précise ('articles et guides publiés par Projet Ariane') avec méthode ('par mots-clés ou par tag'), tri et type de sortie. La ressource 'articles et guides' distingue clairement l'outil des frères structurés (rechercher_ecole, rechercher_metier, rechercher_aides) qui visent des fiches/records, pas du contenu éditorial.

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?

Le contexte d'usage est implicite : la liste thématique (Parcoursup, alternance, métiers, aides, vie étudiante) et le type 'articles et guides' suggèrent quand l'utiliser, notamment par contraste avec les outils frères. Mais la description ne nomme aucune alternative et n'exclut rien ; un agent doit inférer qu'il faut rechercher_metier pour les fiches métiers plutôt que cet outil.

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 mark the tool as read-only and non-destructive. The description adds that the data originates from 'Projet Ariane', which gives context about the data source. It also specifies that results include links to detailed sheets, but it does not disclose potential variations in result counts or whether results are exhaustive. Given the annotations, the description adds useful context, so a 4 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, dense sentence that packs in the key information: what is searched (schools by various criteria), the example results (campuses, number of formations), and the data source (Projet Ariane). There is no redundancy or fluff; every phrase contributes to clarity. This is well-structured and front-loaded with the main verb.

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's moderate complexity (3 parameters, all documented in schema) and no output schema, the description is quite complete: it explains the search scope, what results include, and cites the data source. It does not explain the structure of return values, but without an output schema, that may not be strictly necessary. The only minor gap is not mentioning result ordering or pagination, but that is not critical for a 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?

The schema covers all parameters with descriptions (100% coverage), so the description doesn't need to add much. The description does mention 'campus' and 'formations' which align with the parameters but doesn't add deeper semantics like example formats or value constraints beyond the schema. Since schema coverage is high, the baseline is 3, and the description adds marginal value.

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's purpose: finding schools and institutions by various criteria (name, acronym, city, type), and it specifies the types included (universities, engineering schools, etc.). It also mentions the results include campuses, number of programs, and links to detailed sheets, which adds specificity. This distinguishes it from siblings like 'rechercher_formation' and 'rechercher_metier'.

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 provides clear context on how to use the tool: search by name, acronym, city, or type, and the output includes campuses, number of formations, and links. However, it does not explicitly state when not to use this tool or mention alternative tools like 'ou_se_former' or 'fiche_ecole', which might serve similar purposes. The exclusion of alternatives is a minor gap.

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 the tool as read-only and non-destructive. The description adds useful behavioral context beyond those annotations: results are relevance-ranked, include Parcoursup access rates, provide links to detail sheets, and come from the Projet Ariane dataset. There is no contradiction with the 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, well-structured sentence that front-loads the main action and resource, then efficiently adds search dimensions, output ranking, and data provenance. Every element contributes useful, non-redundant information.

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 search tool with a 100% documented schema and no output schema, the description adequately explains the main results: ranked formations, Parcoursup access rates, and links to detail sheets. It does not explicitly delineate the boundary with sibling tools like rechercher_ecole, but the overall context is sufficient for correct tool selection and 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?

Schema description coverage is 100%, so the baseline is 3 even with no extra parameter detail in the description. The description mentions filtering by 'intitulé, ville, niveau ou type', which maps to the schema properties, but it adds no syntax, value formats, or constraints beyond what the schema already provides.

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 is action-specific: 'Trouve des formations' names the verb and resource, enumerates relevant formation types, and distinguishes itself from sibling tools like rechercher_ecole and rechercher_metier. It provides the key search dimensions and output characteristics, so an agent can clearly identify what this 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?

The description gives clear context for when to use this tool: searching for formations by keyword, city, level, or type. It does not explicitly state when not to use it or name alternative tools, leaving some boundary inference to the agent, but the sibling list and the description's specificity make the intended use fairly obvious.

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 signal readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior beyond that: it names the data source (Projet Ariane) and the return shape (list with links to fiches), though it does not discuss limits or empty-result 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 a single, front-loaded sentence with no filler. It packs in the action, criteria, source, and output shape efficiently, and the parenthetical data-source note 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?

For a simple read-only search tool with fully documented parameters and safety annotations, the description is nearly complete: purpose, source, and output are all covered. It could be more explicit about whether both criteria can be combined and what fields appear in the returned list, but nothing essential to invocation 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 description coverage is 100%, so the baseline of 3 applies even though the description adds little parameter detail. The description restates the two criteria but does not clarify how required 'interets' and optional 'domaine' combine; 'ou' could imply domain-only searching even though 'interets' is required.

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 ('Trouve'), a target resource ('métiers'), and the matching criteria ('centres d'intérêt ou un domaine'), then specifies the output as a list with links to fiches. This clearly differentiates it from sibling fiche_metier, which presumably returns a single job sheet.

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 clear search context: use it to discover careers from interests or a domain, and expect a list back. It does not explicitly name alternatives or state when not to use it, but the context is sufficient for an agent to route a broad career-search query here.

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 and destructiveHint, so this is known to be a safe read operation. The description adds useful context by naming the data sources (France Travail, La Bonne Alternance, Projet Ariane) and specifying that only active offers are returned, but it does not disclose behaviors like rate limits or external-service dependency.

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 sentence front-loads the verb and resource, then packs sources, search criteria, and returned fields without filler. Every clause earns its place and the description remains easy to parse.

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 that there is no output schema, the description usefully enumerates the result attributes: contract type, salary, date, and offer link. It does not describe response formatting, pagination, or error behavior, but for a simple read-only search tool with fully documented parameters, this is sufficient.

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 already has meaningful documentation. The description only restates that searching works by métier or mot-clé and by ville, adding no syntax, format, or default details beyond the schema, which matches the baseline.

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 verb and resource: it finds active job and apprenticeship offers from named sources by trade or keyword and city. It also distinguishes this from sibling search tools such as rechercher_metier or rechercher_formation, so an agent can tell them apart without inspecting schemas.

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 concrete usage context: search by métier or mot-clé plus ville, with contract, salary, date, and link fields. It does not explicitly list when not to use it or name an alternative sibling, but the criteria are clear enough to select this tool for job/alternance offer searches.

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