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

No annotations are provided, so the description carries the full burden. It states the operation is 'récupère' (retrieves), implying read-only, but does not explicitly mention side effects, authentication, or error behavior. The basic nature is clear, but depth is limited.

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, but the second sentence is dense with provider-specific mapping details. All information is relevant and purposeful, though slightly lengthy for a simple getter.

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?

An output schema exists, so return values need not be described, but the description adds important context about provider types and page_id derivation. It does not cover error cases or permissions, but those are not essential given the schema and the tool's simplicity.

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 0% and the description only repeats 'par son id' without explaining where the user_id comes from or adding constraints. The parameter is self-explanatory by title, but the description does not enrich its semantics.

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?

Description clearly states the verb 'récupère' (retrieves) and the resource 'informations d'un utilisateur' by id, and distinguishes the tool by mentioning connected providers and sub-accounts. It also ties the tool to a specific use case (before schedule_post), making its purpose unambiguous relative to sibling 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?

Explicitly says to use this tool before schedule_post to identify the correct page_id, and provides concrete mapping rules for different provider types. This gives clear guidance on when to use the tool versus alternatives.

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 indicates a read-only listing operation via the verb 'list', which is transparent. However, it does not explicitly state side effects, permissions, or error conditions. Since no annotations are provided, the description carries the full burden, but the simplicity of the operation makes this acceptable.

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 short sentences, directly stating what it does and when to use it. No unnecessary words or 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?

Given that an output schema exists, the description does not need to detail return values. It covers purpose and usage context sufficiently. Minor omission: it does not explicitly state that it is a non-destructive operation, but this is implied by the verb '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 tool has zero parameters, so there is nothing for the description to explain. The input schema is empty, and the description does not need to add parameter 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 clearly states the tool's function: 'Lists all social media accounts connected to Plus Tard.' It also provides context by implying it is a prerequisite for scheduling, which distinguishes it from scheduling actions.

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 specific use case: 'Use this tool to know which accounts are available before scheduling a post.' This indicates when to use it, though it does not explicitly mention alternative tools or conditions for not using it.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly discloses that the tool creates a user, returns an OAuth URL, requires the end user to open the URL in a browser, and that the URL is valid for 24 hours. It also notes the default language. This is robust transparency for a tool with no annotation support.

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 concise, with the core action front-loaded, followed by usage guidance and then essential behavioral details (browser requirement and validity). Every sentence adds value, and the structure is logical. It is slightly verbose in the OAuth explanation but still 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?

Given an output schema exists (so return format is presumably covered) and no annotations, the description provides a comprehensive picture: what it does, when to use it, parameter defaults, and the critical OAuth flow requirement. It is complete enough for an agent to invoke correctly without needing additional context.

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 0%, so the description must compensate. It states that email and language are optional and that the default language is 'fr'. While it doesn't elaborate on the purpose of the email parameter, the description covers both parameters sufficiently to guide invocation, which is adequate for only 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?

States a specific verb ('Crée un nouvel utilisateur') and resource ('nouvel utilisateur Plus Tard'), and clearly distinguishes the action from siblings like get_user and list_accounts. The return of an OAuth URL is also explicit, leaving no ambiguity about the tool's primary function.

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 an explicit when-to-use instruction: 'Utilise ce tool quand l'utilisateur veut onboarder un nouveau client ou se créer un compte.' This is clear guidance, though it does not explicitly state when not to use it or mention alternatives. The condition is specific enough for an agent to route correctly.

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

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

No annotations are present, so the description carries the full burden. It warns about common ID misuse and provider-specific constraints, but does not explicitly describe side effects (e.g., that this creates a scheduled post) or error/result behavior. It could be more transparent about what happens on success/failure.

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 well-structured with clear bullet points and an IMPORTANT section. It is somewhat lengthy but each sentence adds necessary guidance. The organization makes it easy to scan while covering multiple edge cases.

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 input schema and existence of an output schema, the description covers essential pre-requisites, provider nuances, and required formats. It does not need to explain return values since an output schema exists. It is sufficiently complete for an AI agent to invoke 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?

The description adds meaningful context for page_id (external vs internal), provider (providerId for sub-account-less providers), planned_at (future UTC ISO8601), and image_posts (required for Instagram). However, it does not explain text, tiktok_params, or twitter_params, leaving 4 of 7 parameters partially or entirely undocumented.

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 schedules a post on a single social network via Plus Tard and lists all supported providers. It distinguishes itself from sibling tools by specifying when to use it (for scheduling content) rather than validation, account listing, or registration.

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?

Provides explicit when-to-use guidance ('quand l'utilisateur veut programmer, publier ou scheduler') and detailed operational instructions: one call per network, prerequisite calls to list_accounts/get_user, correct page_id vs internal ID, provider-specific handling, Instagram image requirement, and UTC date format. This is exemplary.

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

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

No annotations are provided, so the description carries the full burden. It clearly states the primary behavior (validation) and the return content (creation/expiration dates). It does not explicitly mention whether the operation is read-only or if it can fail, but the nature of validation and the absence of side effects are strongly implied. A small gap exists regarding error behavior, but overall the description is transparent.

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 concise sentences in French. It conveys the core purpose, usage scenario, and return information with no redundancy or unnecessary detail. Every sentence contributes directly to understanding the tool.

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

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

The description tells the agent what the tool does, when to use it, and what it returns. It does not specify the exact output format or error handling, but these are not essential for the agent to decide to invoke it. Given the simplicity of the tool, the description is sufficiently complete for practical use.

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 zero parameters, so there is nothing to describe. The schema coverage is effectively 100% since no parameters exist. The description correctly does not attempt to explain nonexistent parameters, so it fully satisfies this dimension.

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 verifies an API key and returns its creation and expiration dates. It explicitly mentions when to use it (diagnosing authentication issues or confirming key activity), making its purpose unambiguous and distinct from sibling tools like list_accounts or get_user.

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 explicit usage guidance: 'Utilise ce tool si l'utilisateur veut diagnostiquer un problème d'authentification ou confirmer que sa clef est active.' This tells the agent exactly when to invoke this tool, leaving no ambiguity about its applicability.

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