Meilleur Code Parrainage

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

Annotations already declare read-only, idempotent, non-destructive and closed-world, so the description correctly focuses on what they cannot convey: the output is plain text, brands are returned in the requested order, and a missing brand is flagged without aborting the other results. It also confirms no account or key is needed.

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?

It is a single dense paragraph with zero filler, front-loading the action and scope before the return format and the sibling routing. The nested clause listing the fiche fields is long but each element is informative.

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 fully carries the burden of return-value documentation by enumerating the fields of each fiche and the partial-failure behavior. Nothing an agent needs to call it correctly or interpret the result 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%, so the array bounds, item type and case-insensitivity are already documented in the schema. The description adds only that output ordering follows input ordering, which is useful but thin beyond 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 opens with a specific verb and resource ('Compare côte à côte 2 à 5 marques de l’annuaire') and immediately anchors scope with a concrete example. It also states the exact return shape (the same fiche as detail_offre), which separates it cleanly from every sibling.

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?

Explicit routing is given for both adjacent needs: use detail_offre for a single brand, and rechercher_offres or offres_par_categorie to find brands worth comparing. The agent never has to infer which tool fits.

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 read-only and idempotence annotations, it discloses that no account or key is required and that an absent brand produces an error directing the agent to rechercher_offres. It also explains the returned content, including verification date, consulted official page, limited-offer end date, and warnings, which is especially valuable without an 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 single-brand scope are front-loaded, followed by selection rules, failure behavior, and access requirements in a logical order. Although dense, the field inventory is useful because there is no output schema, and the remaining sentences all provide actionable 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 simple one-parameter read operation, the definition covers scope, expected result content, when to use it, sibling alternatives, missing-brand behavior, and authentication requirements. The absence of an output schema is well compensated by the enumeration of returned fields, and no pagination or other complex invocation behavior appears necessary.

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 fully documents marque, including common spelling, case-insensitivity, and examples, so the baseline is 3. The description adds operational meaning by requiring one precise brand and routing uncertain names through search, though it adds no further syntax or formatting details.

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, resource, and scope: returning the complete referral-offer record for one brand in the Meilleur Code Parrainage directory. The detailed field inventory and explicit routing to comparer_offres and rechercher_offres clearly distinguish it from its 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?

It explicitly says to use the tool when the user names a precise brand and wants to know how to obtain the bonus. It also gives clear alternatives for multiple brands and uncertain names, plus recovery guidance when the brand is absent.

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 and destructiveHint=false, so the safety profile is covered. The description adds non-obvious context beyond that: the result is sorted by offer count descending and that no authentication or key is required ("Lecture seule, sans compte ni clé"). It does not discuss pagination or result size, but for an enumeration tool this is close to complete.

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 compact sentences, front-loaded with what is returned, then usage, then the read-only/auth note. Each sentence carries distinct information; the only minor redundancy is restating "ne renvoie aucune offre" alongside the usage guidance.

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

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

With no output schema, the description carries the burden of describing return values, and it does: category names, verified-offer counts per category, a total, and the ordering. Combined with the zero-parameter confirmation and read-only note, an agent has everything needed to call 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?

Zero parameters, so the baseline is 4; the description correctly confirms "Aucun paramètre", matching the empty input schema and preventing an agent from inventing arguments. No further parameter meaning is possible.

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

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

States a specific verb and resource ("Liste toutes les catégories de l’annuaire") plus what each entry contains (nombre d'offres vérifiées, total) and the sort order (de la plus fournie à la moins fournie). It explicitly names the sibling offres_par_categorie as the downstream consumer, so an agent can distinguish it from the other five tools.

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

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

Gives two concrete use cases (obtenir les noms exacts pour offres_par_categorie, présenter l'étendue de l'annuaire) and an explicit exclusion ("ne renvoie aucune offre"), which steers agents away from using it when they actually need offers. Alternatives and when-not-to-use are both covered.

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

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

The annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description still adds real context beyond them: 'sans compte ni clé' tells the agent no authentication is needed, and the enumerated payload lists what each offer record contains in the absence of an 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?

It is front-loaded with the payload contents first and the routing rules second, and every clause carries information. The field enumeration is long but each item maps to a distinct returned value, so it earns its space; only the phrase 'toutes catégories confondues' slightly duplicates the scope already implied.

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 no parameters, no output schema and no nesting, so the burden falls on describing what comes back and when to call it — the description does both, including verification and expiry dates that an agent would otherwise have to discover by calling.

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

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

With zero parameters the baseline is 4, and the description explicitly confirms 'Aucun paramètre', so the agent won't waste a turn probing for filters. Nothing more can be added for a parameterless tool.

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

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

The description names a specific verb and resource ('Renvoie la sélection du mois des meilleures offres de parrainage') plus its editorial provenance ('choisies et classées par la rédaction ... toutes catégories confondues'), which immediately separates it from the category- and brand-scoped 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?

It states the exact triggering condition ('les meilleurs codes de parrainage du moment sans marque ni secteur') and routes the agent to the right alternative in each excluded case: offres_par_categorie for a sector, detail_offre for a brand.

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 safety annotations, it discloses the text output and its per-offer fields, default and maximum result counts, absence of pagination, explicit errors for unknown or empty categories, and the lack of account or API-key requirements. « Lecture seule » repeats the annotations but is consistent with them, while the remaining operational detail is substantial.

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 front-loaded and progresses logically from purpose to tool routing, output, errors, and access requirements, with no filler. It is somewhat dense and repeats schema or annotation facts such as the limits and read-only status, so it is not perfectly economical.

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 two-parameter read tool, it covers selection criteria, sibling alternatives, result shape and fields, result limits, pagination, error behavior, and authentication. Because there is no output schema, the explicit text-output description and field list are especially valuable, and no material invocation detail appears 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 fully documents categorie and limite, including case handling, examples, bounds, and the default, so parts of the description repeat structured information. It still adds useful semantics through the single-category scope, explicit invalid-or-empty-category failure, and confirmation that the result cap cannot be extended through pagination.

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 opening sentence gives a precise verb, resource, and scope: listing verified referral offers from a single category in a named directory. The routing sentence further distinguishes it from rechercher_offres, detail_offre, meilleures_offres, and lister_categories.

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 explicitly says to use the tool for product-type searches without a named brand and supplies concrete examples such as « une banque en ligne ». It also gives alternatives for brand searches, the cross-category monthly selection, and discovery of exact category names, making both positive and negative selection conditions 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?

Beyond the annotations, which already declare read-only, idempotent, non-destructive behavior, the description adds that no account or key is required. It also discloses the result limit behavior: 10 results by default, up to 20, with no pagination. It describes the fallback message when nothing matches, which helps the agent recover correctly.

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 front-loaded with the purpose and then routes the agent to sibling tools in a compact, semicolon-separated structure. The return format and fallback behavior are included without unnecessary filler. Every sentence contributes to correct tool selection or invocation.

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, so the description appropriately explains the return format: brand, profile URL, referral code, benefits for both parties, categories, and verification date. It also covers the no-results case and access constraints. This is complete for a two-parameter read-only 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 description coverage is 100%, so the schema already documents both parameters. The description reinforces the query semantics with examples such as brand name, partial name, or keyword, and repeats the limit behavior. It does not add substantially new parameter meaning beyond what the schema provides, 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 and resource: searching verified referral offers in the Meilleur Code Parrainage directory from a brand name or keyword. It explicitly distinguishes this search tool from siblings such as detail_offre, offres_par_categorie, and meilleures_offres. An agent can understand its role without opening 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?

The description gives explicit when-to-use guidance: use this first when the brand is uncertain or misspelled, or when the need is expressed as keywords. It also names the alternatives and the conditions that select them: detail_offre for a known brand, offres_par_categorie for browsing a sector, and meilleures_offres for the monthly selection.

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