postari

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

No annotations exist, so description carries full burden. It lists the metrics returned but does not disclose whether it is read-only, any potential side effects, rate limits, or how data is aggregated. Adequate but not thorough.

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?

Single sentence listing all key metrics and the date range context. No wasted words; front-loaded with important 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 no output schema, the description adequately lists the metrics. It doesn't specify aggregation granularity (e.g., totals vs. per-day) but is sufficient for a simple stats 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?

Schema coverage is 100%, so baseline is 3. The description mentions 'en un rango de fechas' matching the from/to parameters but adds no additional syntax or format details 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 clearly states it provides global account metrics (sent, delivered, opens, clicks, unsubscribes, bounces) over a date range. This distinguishes it from sibling tools like get_campaign_stats (per campaign) and diagnose_deliverability (diagnostic).

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 for retrieving global metrics over a date range. It does not explicitly list when not to use it or alternatives, but sibling names provide context (e.g., get_campaign_stats for campaign-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?

With no annotations, the description carries the full burden. It discloses the critical behavioral nuance that activation does not trigger sending, which prevents a common misunderstanding. It does not elaborate on permissions or return values, but for a status toggle this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, front-loaded with the main action and a critical warning. No filler 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?

For a simple tool with one required parameter and one optional boolean, the description covers the core behavior and the key caveat. The absence of output schema is not a major deficit here, but it could mention edge cases like invalid flow_id.

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 meaning to the 'paused' parameter by showing its effect, but the schema already provides that description. It does not add any explanation for 'flow_id', which remains undocumented. With 50% schema coverage, the description only partially compensates for the gap.

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

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

The description clearly states the tool's purpose: putting the automation into service (active) or pausing it. It explicitly distinguishes itself from the sibling tool arm_flow by warning that activating does not send, which is essential for correct selection.

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 by naming arm_flow as the alternative for sending, effectively saying 'use this to change status, but for sending use arm_flow.' This is a clear when-not and alternative.

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, the description must fully disclose behavior. It only states the basic action, omitting details like whether contacts are created if missing, duplicate handling, permissions, or side effects.

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 concise sentence in Spanish fully captures the tool's purpose without any wasted words.

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 3 parameters, no output schema, and no annotations, the description is too minimal. It lacks information on return values, error conditions, prerequisites, and use cases.

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 meaning by indicating that the contact can be specified via email or contact_id, and that list_id is the target list. However, it does not explain behavior when both email and contact_id are provided, or if neither, and does not cover the remaining parameters 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 clearly states the action: adding a contact to a list, and specifies two identification methods (email or contact_id). It distinguishes from siblings like create_subscriber (creating a new subscriber) and tag_subscribers (adding tags).

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?

No guidance on when to use this tool versus alternatives like create_subscriber or tag_subscribers. No prerequisites or context 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?

With no annotations provided, the description carries the behavioral burden. It discloses major side effects: sends real emails, requires a specific confirmation string, is not retroactive, and depends on prior testing and account permissions. This goes beyond the schema by adding safety-relevant context, though it does not mention error behavior or return values.

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 main action, then lists prerequisites and a key limitation (non-retroactive) in two dense sentences. Every sentence earns its place, and there is no fluff, 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 the tool has 3 parameters, no output schema, and no annotations, the description covers the essential aspects: purpose, side effects, prerequisites, and behavioral constraints. It does not describe return values or failure modes, but for an action that arms a flow, 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 67% (flow_id lacks a description). The description mentions the 'confirm' requirement but merely restates what the schema already says ('debe ser exactamente "ARMAR ENVIOS"'). It does not explain flow_id or acknowledge_no_list_filter, though flow_id is self-explanatory from context.

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: 'ARMA la automatización' (arms the automation) and specifies the consequence: 'a partir de aquí envía correos REALES sola' (from here it sends real emails on its own). This distinguishes it from siblings like test_flow or activate_flow by emphasizing real sends and non-retroactivity.

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 prerequisites: literal confirmation with 'ARMAR ENVIOS', prior flow testing, and account permission for agent sends. This implies the tool should be used after test_flow and only when ready for real sends, giving clear usage context even though no alternative tools are explicitly named.

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 transparency burden. It discloses a key behavioral trait: the flow is created as a draft and disassembled, sending nothing until tested and activated. This goes beyond the schema and gives crucial context about the tool's side effects.

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, front-loaded with the primary action. Every sentence adds relevant information without unnecessary fluff, 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 the tool has 4 parameters, nested objects, and no output schema or annotations, the description is lean. It covers the core creation action and the draft state, but lacks details on return values, prerequisites, or post-creation workflow. The graph format clarification helps, but overall completeness is moderate.

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 75%, with parameters like name, trigger_type, and trigger_config already described. The description adds value by clarifying that the 'graph' parameter uses the same format as get_flow's return value, which is helpful, but it does not expand on the other 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 clearly states the tool's function with the verb 'Crea' (creates) and resource 'automatización' (automation). It distinguishes itself from sibling tools like test_flow, activate_flow, and arm_flow by noting the automation is created in draft/disassembled state, implying a distinct creation step.

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 the tool is the first step in creating an automation, but does not explicitly state when to use it versus alternatives. The note about being born as a draft suggests subsequent use of test_flow and activate_flow, but this guidance is implicit 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?

Al no haber anotaciones, la descripción asume la carga de revelar comportamiento. Indica el retorno (URL pública y código embebible) y un comportamiento por defecto (campo de correo cuando no se pasan campos). Aunque no detalla más efectos secundarios, aporta información útil más allá del esquema.

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 descripción es de dos frases breves, directas y sin relleno. La información clave aparece al inicio y cada palabra aporta valor.

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?

La herramienta tiene 6 parámetros, sin anotaciones ni esquema de salida. La descripción cubre el propósito y el valor de retorno, pero deja sin contexto parámetros como double_optin y thank_you_message. Aun así, es suficiente para entender la operación básica de creación de formularios.

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?

El esquema tiene un 50% de cobertura de descripciones y la descripción solo añade detalle sobre 'fields' (que por defecto incluye un campo de correo). No explica 'name', 'double_optin' ni 'thank_you_message', por lo que compensa parcialmente la falta de documentación de parámetros.

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 descripción usa el verbo 'Crea' y especifica el recurso 'formulario de captación', además de indicar que devuelve URL pública y código para embeber. Esto la distingue claramente de herramientas hermanas como create_list, create_flow o create_segment.

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?

No menciona cuándo usar esta herramienta frente a alternativas ni excluye casos (p. ej., update_form). La única indicación de uso es implícita: si no se pasan campos, se incluye uno de correo. No hay guía explícita de cuándo o cuándo no usarla.

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, the description carries the burden of behavioral disclosure. It does state that the tool creates a resource and returns a public URL, which is helpful. However, it omits details about potential side effects, permissions, or error cases. The information provided is adequate but not rich enough to earn a higher 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 compact and well-structured. The first sentence establishes the primary purpose and return value, and the second provides essential parameter context. Every sentence adds value with no redundancy or 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?

Given the tool's complexity (9 parameters with many optional) and no output schema, the description adequately covers the most important aspects: the return value (URL), the 'kind' variants, and the form integration. It does not need to repeat schema details. Some minor omissions, like default kind, are available in the schema, so the description is complete enough for an agent to use 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 67%, and the description adds meaningful context for key parameters: it explains the 'kind' values (blocks, code, ai, iframe, external_url) and clarifies the purpose of form_id ('Conéctale un formulario... para que capte suscriptores'). This goes beyond the schema and compensates for parameters with no description in the schema, like iframe_url and external_url.

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: 'Crea una página de aterrizaje y devuelve su URL pública.' It specifies the resource (landing page) and the action (create) with an additional outcome (returns URL). It also enumerates the different 'kind' variants, distinguishing this tool from siblings like create_launch or update_landing.

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 for when to use the tool (to create a landing page) and includes additional guidance on how to attach a form with form_id. While it doesn't explicitly mention alternatives like update_landing or list_landings, the tool's purpose is obvious and no misleading exclusions are present.

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?

Without annotations, the description carries the behavioral disclosure burden. It provides valuable behavior details: a launch groups campaign emails with dates, and if `stages` is omitted and type is curso/infoproducto, it seeds 8 standard stages (lead magnet → webinar → apertura de carrito → cierre). This goes beyond a simple 'creates a launch' statement, though it doesn't mention permissions, reversibility, or return shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no redundant content. The first sentence is front-loaded with the verb and object, and the second sentence adds a conditional behavioral rule. Every clause 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?

The tool has 7 parameters, no output schema, and no annotations. The description explains the core purpose, the structure of a launch, and a key default behavior. It doesn't cover error conditions, return values, or all edge cases, but for a creation tool with high schema coverage, it is reasonably 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?

All 7 parameters have schema descriptions, so baseline is 3. The description adds context beyond the schema by explaining the default seeding behavior tied to `stages` and `seed_default_stages`, and lists the specific 8-stage sequence, which the schema does not enumerate. This elevates the value to 4.

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 'Crea un LANZAMIENTO' (Creates a launch), specifying the exact resource and verb. It clarifies the launch type with examples (curso, infoproducto, evento) and distinguishes from sibling tools like get_launch and list_launches by indicating this is the creation 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?

The description implies the tool is for creating a launch object and explains the default stage seeding, but it does not explicitly state when to use this over other creation tools like create_flow or create_campaign. No alternatives or when-not-to-use conditions are given.

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 must carry the burden of behavioral disclosure. It only states 'creates', implying mutation, but does not mention permissions, reversibility, or other behavioral traits beyond the basic action.

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, efficient sentence. It is front-loaded with the core action, but could include more detail without sacrificing conciseness.

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 lack of annotations, output schema, and sibling differentiation, the description is too minimal. It fails to provide necessary context such as how the list relates to subscribers, duplicate handling, or typical use cases.

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 only 50% (the 'description' parameter lacks a description). The tool description does not add any meaning beyond what the schema provides; it merely repeats the concept of creating a list.

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 creates a new list of contacts, using a specific verb and resource. However, it does not differentiate from sibling tools like 'add_subscriber_to_list' or 'list_lists', which could cause ambiguity.

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?

No usage guidance is provided. The description does not indicate when to use this tool versus alternatives, when not to use it, or any prerequisites or side effects.

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, the description carries the burden for behavioral disclosure. It reveals a key trait: the segment is a 'regla de quién entra que se recalcula sola' (self-recalculating rule), which is valuable. However, it doesn't mention potential side effects like overwriting existing segments, required permissions, or error scenarios, leaving gaps in transparency.

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 long, front-loaded with the core purpose ('Crea un segmento'), and adds just enough context to be useful. Every word earns its place, with no redundant 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 tool has a nested `definition` object and no output schema or annotations. The description provides the core concept but not enough detail on constructing the definition JSON, what the return value is, or required prerequisites. It is adequate for basic understanding but leaves clear gaps for an AI agent to invoke it confidently.

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 low (33%: only the 'definition' parameter has a description). The tool description helps by explaining the concept of a segment ('quién entra' rule), which clarifies what 'definition' should contain. However, it does not add semantics for 'name' or 'description' parameters, and the definition's JSON structure is only referenced via 'same JSON as the UI'.

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 tool's function: 'Crea un segmento' (creates a segment) and differentiates it from sibling tools by explaining it's a self-recalculating 'who enters' rule used to segment launches without duplicating lists. This distinguishes it from create_list and create_launch, which are 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 provides clear usage context: 'Es lo que se usa para segmentar un lanzamiento sin duplicar listas' (it's what is used to segment a launch without duplicating lists). This implies when to use it, but it doesn't explicitly state when NOT to use it or name alternative tools. The guidance is clear but lacks explicit exclusions.

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

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

The only behavioral trait disclosed is the upsert ('no duplicar'). With no annotations, more details like idempotency, field merging behavior, or error handling are needed. The description falls short.

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 with no fluff, but it is too short for the tool's complexity. Conciseness is good, but structure suffers from omission of details.

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 7 parameters, upsert behavior, no output schema, and no annotations, the description is incomplete. It lacks return value info, conflict resolution specifics, and requirements beyond email.

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 provides no parameter-level information. Only 57% of parameters have schema descriptions, and the description does not compensate for the missing ones (phone, first_name, last_name). It adds no value 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 clearly states the tool performs an upsert (create or update) on a subscriber. The verb 'Crea o actualiza' and 'suscriptor' are specific. However, it does not explicitly contrast with sibling 'update_subscriber', which could cause minor ambiguity.

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?

No guidance is provided on when to use this tool versus alternatives like 'update_subscriber' or 'add_subscriber_to_list'. The implied usage (to create or update) is not sufficient for a clear decision.

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?

Despite having no annotations, the description discloses a key behavioral trait: idempotency. It explicitly states that if the tag already exists, it returns the existing one without duplicating. This adds context beyond the schema, though it does not cover permissions or response format.

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 front-loads the core purpose and appends the idempotency behavior in parentheses. Every word earns its place, with no filler.

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

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

While the tool is simple, the description lacks usage guidance and parameter semantics. It also does not mention return values or potential errors, and with no annotations or output schema, it carries more burden. The idempotency note is helpful but incomplete.

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 description coverage is 0%, and the description does not explain the 'name' or 'color' parameters. It only mentions creating a tag and idempotency, leaving parameter semantics entirely to the schema's bare structure.

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 'Crea una etiqueta' (creates a tag), using a specific verb and resource. It clearly distinguishes from sibling tools like create_flow or create_list by explicitly naming 'tag' as the resource.

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?

No guidance is provided on when to use this tool versus alternatives. The description only mentions idempotency but does not discuss use cases, prerequisites, or exclusions. Sibling tools like tag_subscribers or create_subscriber exist, but no differentiation is given.

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 burden of disclosure. It reveals that templates can be duplicated from catalog and that catalog templates are shared and immutable. However, it doesn't address permissions, return behavior, or what happens if the template name already exists, leaving transparency gaps.

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, front-loaded with the main action, and includes a useful clarification about catalog templates. Every sentence carries meaning, so 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?

Given the tool has 7 parameters, no output schema, and no annotations, the description should provide more detail about the template's content fields and return value. It only covers the duplication aspect, leaving many aspects of the tool undocumented.

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 only adds context for from_template_id, which is already described in the schema. It doesn't explain the purpose of blocks, subject, preheader, or other fields, and the schema has low coverage (14%). Thus, the description adds minimal value for most 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 clearly states the tool creates an account-specific template ('Crea una plantilla propia de la cuenta') and optionally duplicates from a catalog using from_template_id. This specific verb+resource distinction sets it apart from catalog templates and differentiates it from sibling tools like create_flow.

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 when to use this tool: when you need a custom template, and that catalog templates are shared and cannot be edited, so users should duplicate them here. This provides clear context, but it doesn't explicitly name alternative tools or state 'use this instead of X'.

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?

Without annotations, the description carries full burden. It discloses the time range, metrics analyzed, and return structure (verdict + actions). It implies read-only behavior, though not explicitly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with key terms (deliverability, 28 days, metrics, verdict, usage). Every word contributes value.

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?

Even without an output schema, the description explains the return value (verdict + actions). No parameters and clear scope make it complete for a diagnostic 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?

No parameters exist, so baseline 4 applies. The description does not need to add parameter meaning.

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 diagnoses account deliverability over the last 28 days, listing specific metrics (bounces, spam complaints, opens, DNS health). It is well-differentiated from sibling tools which focus on campaigns, lists, or subscribers.

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 usage context: 'Use it before a large send or if emails are not arriving.' Does not list alternatives but usage is clear and actionable.

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 describes the tool as listing actions (read-only behavior) and covers the what/on-what/when aspects. However, it does not mention authentication, scope, or rate limits; for a simple read tool, this is adequate.

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 key purpose ('Transparencia...') and covers all essential information with zero wasted words.

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 only one optional parameter and no output schema, the description adequately explains the purpose, scope, and output fields ('qué se hizo, sobre qué y cuándo'), providing sufficient context for an agent to use 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% for the single parameter 'limit'. The description adds no additional meaning beyond the schema's '1-100, default 50.' Baseline of 3 is appropriate as 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 clearly states the tool lists account actions originated by an agent/AI, specifying sources (Atelier chat, agent API, A2A) and the purpose ('qué se hizo, sobre qué y cuándo'). The verb 'lista' and resource 'acciones de la cuenta originadas por un agente/IA' are specific and unambiguous.

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 the use case ('Para auditar lo que un agente ejecutó'), providing clear context. While no explicit alternatives or exclusions are given, the sibling tools are all different (campaigns, subscribers, etc.), so differentiation is inherent.

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, the description carries the full burden. It discloses that it applies the saved filter and returns three numbers (base, exclusions, final total), making the behavior transparent. It doesn't explicitly state read-only, but 'ANTES de enviar' implies no side effects.

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 leads with a user-oriented question, then provides a clear answer. Every word adds value, with no filler or repetition of the tool name.

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 tool with one parameter and no output schema, the description is complete: it explains the purpose, timing, and the nature of the return value (counts). It doesn't describe exact JSON keys, but for a simple tool this is acceptable.

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

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

There is only one parameter, campaign_id, with 0% schema description coverage. The description doesn't explicitly mention the parameter but implies it via context (the campaign whose audience is calculated). The phrase 'aplicando el filtro guardado' adds meaning about how the parameter is used, though it doesn't compensate fully for missing schema documentation.

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 a specific verb ('Devuelve') and resource ('destinatarios REALES') with a clear context ('ANTES de enviar'). It distinguishes itself from sibling tools like get_campaign_stats by focusing on pre-send audience size calculation.

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 'ANTES de enviar' (before sending), giving clear temporal usage context. No alternatives are named, but the context is sufficient to differentiate from post-send stats tools.

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 bears full responsibility for behavioral disclosure. It lists the returned metrics but fails to mention that this is a read-only operation, any authentication requirements, rate limits, or error behavior. For a read tool, this is a notable gap.

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 efficiently communicates the tool's purpose. It is front-loaded with the verb and lists the metrics, containing no redundancy or fluff.

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 partially compensates by listing the metrics returned (sent, opens, clicks, etc.). However, it lacks details on the response structure, pagination, or additional metadata. Overall, it is fairly complete for a simple 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 has 100% documentation coverage with a single parameter 'campaign_id' described as 'ID de la campaña.' The description does not add any extra meaning or constraints beyond the schema, so 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 clearly states it retrieves real metrics for a campaign, listing specific metrics like sent, opens, clicks, etc. The verb 'get' and resource 'campaign stats' are unambiguous, and it effectively distinguishes from sibling tools like list_campaigns (which lists campaigns) and account_stats (likely account-level stats).

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 no guidance on when to use this tool versus alternatives. While the purpose is clear, there is no explicit mention of context, prerequisites, or exclusion of other tools. For example, it does not differentiate from account_stats or list_campaigns in terms of use cases.

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, the description carries the full burden. It mentions that metrics are 'REALES' (real) and that totals are included, which gives some insight into data accuracy and output content. Yet it lacks any disclosure about read-only behavior, response structure, error conditions, or operational caveats, leaving significant gaps.

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 at two sentences, with the key data content front-loaded in the first sentence. The use of ALL CAPS for 'MÉTRICAS REALES' is somewhat emphatic but not wasteful. Every sentence contributes to understanding the tool's value.

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 one parameter and no output schema, the description provides a high-level overview but misses important context: it does not explain the structure of stages or metrics, nor clarify how this tool compares to list_launches. The parameter is undocumented, and the return format is vaguely described, making it incomplete for an agent to use confidently.

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 a single launch_id parameter with no description coverage. The description does not mention this parameter at all, nor does it explain its format, constraints, or how it relates to the returned data. With 0% schema coverage, the description fails to compensate.

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 a launch with its stages and real metrics (sent, opens, clicks) plus a total. While it lacks an explicit verb like 'retrieve', the noun phrase is informative and distinguishes itself from sibling tools such as list_launches by focusing on per-stage metrics.

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

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

The final sentence 'Es la forma de saber cómo va un lanzamiento' provides a clear use case for monitoring launch progress. However, it does not explicitly compare with alternatives like list_launches or get_campaign_stats, nor does it state when not to use this tool.

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 implies a read-only operation by stating it 'devuelve' (returns) data, but it does not explicitly declare idempotency, side effects, or authentication requirements. Since no annotations are provided, the description carries the full burden, and it lacks depth (e.g., rate limits, data freshness).

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, clear sentence that conveys purpose and output without unnecessary words. It is well front-loaded 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 simple retrieval tool with one parameter and no output schema, the description adequately states what is returned (data, status, tags, basic history). However, it could specify the structure of 'datos' or 'historial básico' to fully guide an agent.

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 covers 100% of parameters with a description for 'email'. The description repeats the concept of searching by email but adds no new semantics (e.g., format expectations or validation). Baseline 3 is appropriate.

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

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

The description specifies the action 'Busca' (searches) and the resource 'contacto' (subscriber) by email, with a clear list of returned data (datos, estado, etiquetas, historial básico). It distinguishes itself from siblings like create_subscriber, update_subscriber, and tag_subscribers by focusing on retrieval.

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?

No guidance is provided on when to use this tool instead of alternatives. The description does not mention preconditions, when to avoid it, or compare with similar tools like diagnose_deliverability or get_campaign_stats.

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 covers key behaviors: default draft-only mode, conditional sending, scope requirements, and that it returns a draft with preview. It does not detail error handling or edge cases, but provides sufficient transparency for typical use.

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 that front-load the main purpose and key behaviors, with no wasted words. It efficiently communicates the core mechanics and usage pattern.

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 13 parameters and no output schema, the description provides a solid overall context: what it does, how to use it in two steps, scope requirements, and the return type (draft with preview). It doesn't address parameter conflicts, but covers the essential completeness for effective 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 input schema already has 100% description coverage, so the baseline is 3. The tool description adds context by highlighting the 'brief' and 'confirm_send' parameters as key toggles, and explains the overall workflow (draft then send). This adds value 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 clearly states it launches a complete email campaign from a natural language brief, generating subject, design, and assembling on a list. It distinguishes from sibling tools like send_transactional_email and list_campaigns by focusing on campaign generation from a brief.

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 says by default it only creates a draft, and to actually send, one must call again with confirm_send:true or scheduled_at. It also mentions required scopes (write for draft, send for sending) and provides clear guidance on when to use each mode.

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, the description carries the full burden. It discloses the linking/unlinking behavior, the prerequisite that the email must already be written, and the ability to modify title, date, and status. However, it does not mention side effects, overwrite behavior, or permission requirements, leaving some ambiguity for a mutating 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?

Two concise Spanish sentences, front-loaded with the primary action, then providing essential context and additional capabilities. Every sentence adds value with no fluff.

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 6 parameters, no output schema, and no annotations, the description covers both primary purposes (linking/unlinking and updating stage fields) and explains the KPI dependency. It omits return value or error behavior, but these are less critical for a straightforward tool. The required vs optional parameters are clear from the schema.

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

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

Schema coverage is 50%, and the description compensates by explaining that title, scheduled_at, and status are stage fields to update, and that campaign_id null disconnects. It doesn't explicitly describe launch_id and stage_id, but their role as identifiers is clear from tool name and required status. This adds meaning beyond the sparse 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 clearly states it connects an already-written email to a launch stage (or disconnects with campaign_id null) and can also update stage title, date, or status. This specific verb-resource pair distinguishes it from sibling tools like launch_campaign or update_flow_emails.

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 clear situational context: without this link, the stage measures nothing, so use it to enable KPIs. It also notes the additional use case of updating stage fields. While it doesn't explicitly name alternatives or exclusions, it gives enough guidance for when to invoke the tool.

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 full burden for behavioral disclosure. It only states basic functionality and filtering. No mention of authentication, rate limits, idempotency, or what happens on empty results. For a read operation, this minimal disclosure is insufficient.

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 very concise with two sentences. First sentence states purpose, second adds filtering capability. Every word earns its place with no fluff.

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 list tool with 2 optional parameters and no output schema, the description covers basic functionality and filtering. However, it lacks information about the return format (fields, ordering, pagination) which would be helpful for an agent to interpret results.

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% with descriptions for both parameters. The description adds value by listing explicit filter values ('draft, scheduled, sending, sent') that are not in the schema as enums, enhancing parameter understanding 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 clearly states the tool lists campaigns/emails of the tenant ('Lista las campañas/correos del tenant'), which is a specific verb+resource. It distinguishes itself from sibling tools like get_campaign_stats and launch_campaign by clearly being a listing operation. Mention of filtering by status adds further specificity.

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 when to use (to list campaigns), but provides no explicit guidance on alternatives or when not to use. It does not mention other tools for campaign stats or launching, so usage context is implied but not 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?

With no annotations, the description carries the full burden but only describes the output contents. It does not explicitly state read-only behavior, pagination, permissions, or error conditions. The historical aside about emails living 'buried in the flow' is colorful but not behaviorally informative.

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 first sentence is concise and informative, front-loading the core purpose and output details. The second sentence is an unnecessary poetic aside that adds no functional value, though it does not make the description overly long.

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 list tool with no output schema, the description provides some return fields (node_id, subject, URL) but omits possible additional fields, pagination, ordering, and error handling. It is minimally adequate but not fully 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 only parameter, flow_id, has no schema description, and the tool description never mentions it by name. It implicitly equates flow with 'automatización' but does not explain the expected value, format, or how it affects the results, leaving the agent to infer from the parameter name alone.

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 the resource (emails within an automation/flow) and lists key returned attributes (node_id, subject, own URL). It differentiates from sibling list tools by focusing on flow emails rather than campaigns, launches, or lists, though it lacks an explicit verb like 'list'.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention when to choose list_flow_emails over list_campaigns, list_launches, or update_flow_email, nor does it state any exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only listing operation but does not explicitly state side effects, authorization requirements, or data scope (e.g., whether archived or draft landings are included). The mention of metrics gives some output context but lacks behavioral depth.

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 redundant words. It efficiently communicates the core function.

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?

While the tool is simple, the description omits crucial information about the 'limit' parameter and does not describe return structure beyond the listed metrics. Given no output schema, the lack of parameter semantics makes the description incomplete for reliable 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 defines a single 'limit' parameter with no description, and the tool description does not explain its purpose, default value, or effect. With 0% schema description coverage, the description completely fails to clarify how to use 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 the specific verb 'Lista' (lists) and identifies the resource 'páginas de aterrizaje' (landing pages), while also specifying included metrics (visits, conversions, conversion rate). This clearly distinguishes it from sibling list_* tools like list_campaigns or list_launches.

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 no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or relationships with sibling tools like create_landing or update_landing.

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, the description must disclose behavior. It indicates a read-only listing operation and adds details about the returned counts (stages and email connections). However, it does not mention pagination, rate limits, or any potential side effects, leaving some transparency gaps.

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, focused sentence that front-loads the primary action and then adds key details. Every word contributes value without unnecessary verbosity.

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 adequately explains the tool's purpose and what it returns for a simple read-only list, but it omits any guidance on the parameters (limit, status) and the return format. Given the lack of an output schema, this leaves the agent with partial information 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?

Schema coverage is 50% (only status has a description); the tool description does not explain the limit or status parameters. Since the description adds no meaning beyond the schema, it fails to compensate for the low coverage, especially for the undocumented limit 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 lists launches for the account and includes specific details (number of stages and email connections). This distinguishes it from siblings like get_launch (single launch) and list_campaigns (different resource).

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 for listing account launches but does not explicitly state when to use this over alternatives like get_launch or list_campaigns. No exclusion or alternative guidance is 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?

With no annotations provided, the description must disclose behavioral traits. It implies a read-only operation but does not explicitly state it is non-destructive or safe. It adds some context (tenant scope) but lacks details on authorization or performance.

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, efficient sentence that conveys the essential information without any unnecessary words or repetition.

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 no parameters and no output schema, the description adequately covers the return content (name and count) and scope (tenant). It is mostly complete, though it could mention the response format (e.g., array) for clarity.

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

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

There are zero parameters, so schema coverage is 100%. The description adds value by specifying the output includes 'name and count', which goes beyond the empty input schema. Baseline for 0 params is 4.

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 lists all contact lists with their name and count. The verb 'Lista' (Lists) and resource 'listas de contactos' are specific. No sibling tool performs the same function, so it is well-differentiated.

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 no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. This is a significant gap for an agent choosing between sibling tools.

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 discloses synchronous behavior and scope requirement, but lacks details on rate limits, error responses, idempotency, or what happens on failure. The scope requirement adds value but is insufficient for full transparency.

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 sentences long, front-loaded with the core action, and every sentence adds value. There is no redundant repetition of schema fields, and the information is well-organized.

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 6 parameters, no output schema, and siblings that overlap in functionality, the description should explain what the tool returns (e.g., success indicator) and prerequisites (e.g., must specify template_id or html_body). The current description omits these details, leaving the agent to infer from schema.

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 no new information beyond 'using a plantilla and variables', which is already covered by schema. It does not clarify the trade-off between template_id and html_body or the exact format of variables.

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 sends a 1-to-1 transactional email, provides concrete examples (quote, receipt, welcome, reminder), and specifies it uses a template and variables. This differentiates it from siblings like launch_campaign or list_campaigns, which handle bulk or informational emails.

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 identifies the tool for transactional emails (1-to-1) and mentions it is synchronous and requires scope 'send'. It implicitly distinguishes from bulk campaign tools among siblings, but does not explicitly state when not to use it or provide explicit 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?

With no annotations provided, the description carries the full burden. It adds valuable behavioral context: returns the real recipient count and fails with HTTP 400 if any reference is missing instead of saving partially (atomicity). It does not disclose whether existing audience rules are overwritten, which is a minor gap, but the disclosed behaviors are significant and non-obvious.

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 sentences long, each earning its place: purpose, return value/confirmation, and error behavior. It is front-loaded with the core function and avoids any filler or repetition.

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 tool with 6 parameters, no output schema, and no annotations, the description provides a solid high-level overview including purpose, output behavior, and error handling. However, it omits mention of include_tags (positive targeting) and tag_on_delivery side effects, which are covered only in schema param descriptions. Overall, it is reasonably complete 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 description coverage is 83%, and param descriptions in the schema are already informative (e.g., 'nombre o UUID', 'manda a A menos los de B'). The tool description adds no additional parameter meaning beyond restating the exclusion concepts, so it does not elevate above the baseline for well-documented schemas.

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 defines who receives an email and who does not, with specific exclusion criteria (tags, lists, previously received campaigns). It distinguishes from sibling get_campaign_audience by using the verb 'define' (set) and mentioning the return of the real recipient count, which is a unique behavioral feature.

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 before sending a campaign ('confirmar antes de enviar'), providing clear context for when to use it. However, it does not explicitly exclude alternatives or mention sibling tools like get_campaign_audience, so it lacks an explicit when-not-to-use statement.

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, the description carries the full burden of behavioral disclosure. It acknowledges mutability (add/remove) but omits details like idempotency, error behavior, or whether partial failures occur. The lack of annotation makes this a significant gap.

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-formed sentence with no extraneous information. Every word earns its place, providing efficient communication of the core purpose.

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 complexity (4 parameters, no output schema, no annotations), the description is insufficient. It fails to describe return values, error conditions, or whether the tag must pre-exist. A more complete description would cover these aspects for safe 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 coverage is 50%; the description adds value by clarifying that emails or contact_ids identify contacts, and that multiple contacts are supported. However, it does not explain the relationship between these two parameters (mutual exclusivity) or the default operation value, which the schema already covers.

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 adds or removes a tag to multiple contacts using emails or contact IDs. It uses specific verbs ('añade o quita') and identifies the resource ('etiqueta', 'contactos'), distinguishing it from sibling tools like update_subscriber or add_subscriber_to_list.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or context for using tag_subscribers over other subscriber management tools.

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 disclosure. It clearly states that the tool sends a real email ('enviándola de verdad') to one account member, defaulting to the owner, which is the key side effect. It could mention additional behavioral details (e.g., whether the flow state changes), but the disclosed info is sufficient for a test action.

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 only two sentences, front-loaded with the action and resource. Every clause adds value: the mandatory timing, the default recipient, and the restriction. No wasted words.

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 lacking annotations and an output schema, the description covers the core action, the required context (before arming), the recipient constraint, and the default behavior. These details are sufficient for an agent to select and invoke the tool correctly without additional documentation.

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 only documents to_email; flow_id lacks a description. The description adds critical semantics for to_email: it must be from an account member and defaults to the owner. flow_id is left implicit, but the tool name and context make its purpose clear. The added value is meaningful despite the partial coverage.

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

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

The description uses the specific verb 'Prueba' (test) with a clear resource ('una automatización') and states the key scope: sending to one account member. This differentiates it from sibling tools like arm_flow, activate_flow, and trigger_flow, which operate on flows in different ways.

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 states 'Es OBLIGATORIO antes de armar' (mandatory before arming), giving a clear when-to-use directive. It also provides an exclusion: 'No se puede usar para mandar correo a terceros', which tells the agent when not to use 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?

No annotations exist, so the description must disclose behavior. It lacks details on idempotency, side effects, permissions, or what happens if the contact is already in the flow. This is insufficient for a mutation 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?

A single sentence that conveys the core purpose without fluff. It could be slightly more informative but remains concise.

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 4 parameters, no output schema, and no annotations, the description fails to cover important aspects like trigger_data usage, flow requirements, and behavioral implications. It is incomplete.

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 only 25% schema coverage, the description should compensate. It explains email and contact_id but says nothing about trigger_data, which is an arbitrary object. The param semantics are poor.

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 puts a contact into an automatic flow using email or contact_id. It distinguishes from sibling tools like launch_campaign or list_campaigns, though it doesn't explicitly differentiate.

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

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

Usage is implied: use when you want to enroll a contact in a flow sequence. No explicit when-not or alternatives are provided, leaving some ambiguity.

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, the description carries full burden and does well by disclosing that the tool cannot arm but can disarm via armed:false. It also scopes exactly which parts of the automation are editable. It doesn't cover permissions or return values, but the provided constraints are meaningful and prevent misuse.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences deliver the core purpose and a critical exclusion/alternative. The information is front-loaded, and every clause earns its place with no fluff.

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 is sufficient for a 6-parameter tool with nested objects and no output schema: it covers main editable fields, disarming semantics, and sibling differentiation. It lacks explicit mention of partial-update behavior (whether omitted fields are unchanged) or return format, but these are not essential for basic 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 coverage is low (33%), so the description compensates by mapping human-readable concepts to parameters: 'nombre' (name), 'disparador' (trigger_config), 'pasos (graph)' (graph), and 'estado' (status). It also clarifies the armed semantic. Only flow_id is not spelled out, but it is required and self-evident.

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 ('Edita') and names the exact resource (una automatización) and fields (nombre, disparador, pasos, estado). It also explicitly differentiates from arm_flow by stating this tool is not for arming and can only disarm, eliminating ambiguity.

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 clear when-to-use versus when-not-to-use guidance: use for editing and disarming, not for arming. It names the alternative tool (arm_flow) and mentions its confirmation requirement, which helps the agent choose correctly among siblings.

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 full behavioral disclosure burden. It does add valuable context that changes are scoped to one email and do not affect the rest of the flow, which is a meaningful safety guarantee. However, it omits details like reversibility, required permissions, error conditions, or side effects beyond the scoped fields, which are important for a mutation 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 two sentences long, front-loaded with the main action and scope. The second sentence provides a safety rationale without unnecessary detail. Every word contributes value, and the structure is clean 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?

While the description excels at purpose and scope, it leaves gaps typical for a mutation tool with no annotations or output schema: no return value description, parameter format details for blocks, or error handling expectations. For a 6-parameter tool, the description is above the minimum viable but still incomplete for an agent needing full invocation confidence.

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 schema description coverage at only 17%, the description compensates by explicitly naming all editable fields: subject, preheader, blocks, and label. This adds meaning beyond the bare property types. It does not explain the structure of blocks or the roles of flow_id and node_id, but these are inferable from the tool's purpose, so the compensation is solid but not complete.

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 with a specific verb 'Edita' (edits) and identifies the resource as a specific email within an automation, listing the editable fields (subject, preheader, blocks, label). It also distinguishes itself from editing the entire flow by stating 'sin tocar el resto del flujo' (without touching the rest of the flow), which differentiates it from sibling update_flow.

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 usage context: use this to modify a single email without affecting the rest of the flow. It suggests an alternative ('reescribir el graph entero' – rewriting the entire graph) and positions this as safer, implicitly indicating when to prefer this tool over a broader update. However, it does not explicitly name the alternative tool or provide 'when not to use' conditions, so it falls 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It lists editable fields but does not disclose side effects such as whether existing fields are overwritten, whether permissions are required, or what happens to the form after update. This is a significant gap for a mutation 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 concise sentence that covers most relevant aspects. It is front-loaded with the primary action ('Edita un formulario') and efficiently lists the editable attributes. However, the comma-separated list is slightly unwieldy but still 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?

Given the tool has 8 parameters, no annotations, and no output schema, the description is incomplete. It omits the redirect_url parameter, lacks any note about postconditions or return values, and does not clarify how the update interacts with existing form data. This is insufficient for a complex mutation 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?

Despite having 0% schema coverage, the description adds meaningful semantics for 6 of the 8 parameters (e.g., 'lista donde caen las altas' clarifies list_id, 'doble opt-in' clarifies double_optin). However, it omits redirect_url and does not explain parameter types or constraints, leaving some gaps.

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 with a specific verb ('Edita' = edits) and resource ('formulario' = form). It enumerates the editable aspects (title, fields, list, double opt-in, thank-you message, activation), which distinguishes it from sibling tools like create_form or update_flow by focusing on form-specific updates.

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 no explicit guidance on when to use this tool versus alternatives. It implies usage for editing an existing form, but there are no exclusions, prerequisites, or mentions of when create_form or other update tools would be more appropriate.

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, the description carries full burden. It discloses that changing the slug breaks shared URLs and that the response warns about it, which is valuable. However, it does not explain partial vs. full updates, permissions, or other side effects.

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 long, front-loaded with purpose and editable fields, and adds a crucial warning in a concise manner. No unnecessary words.

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 tool with 8 parameters and no output schema or annotations, the description is incomplete. It does not explain the return value, whether the update is partial or full, or how the remaining parameters behave, leaving significant gaps.

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 meaning for some parameters (blocks as content, slug, form_id as connected form, is_active as activation) but leaves ai_prompt, html_code, name, and landing_id unexplained. Since schema coverage is 0%, this partial coverage is insufficient.

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 edits a landing page and lists the editable aspects (content, slug, connected form, activation). This distinguishes it from siblings like create_landing and list_landings.

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 purpose implies use for editing existing landings but does not explicitly mention when to use this tool versus create_landing or list_landings. No exclusions or alternatives are stated, so guidance is only implied.

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 provided, so description must disclose behavior. It only states 'updates data' without explaining merge vs overwrite, error handling on non-existent email, idempotency, or return value. Minimal transparency.

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?

Extremely concise (one sentence), front-loads key info (verb, resource, fields). No fluff, but could benefit from structured formatting or bullet points for clarity.

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 mutation tool with 6 parameters, no output schema, and no annotations, the description is severely lacking. It does not explain return value, error conditions, or behavioral nuances like partial updates.

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 description must compensate. It lists field categories (name, country, phone, tags) but omits specifics like first_name vs last_name, and does not mention email or provide details on format or constraints.

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 'actualiza' (updates) and resource 'contacto existente' (existing contact), listing specific fields. It distinguishes from sibling create_subscriber (creates new) and get_subscriber (reads).

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?

No explicit guidance on when to use vs alternatives, prerequisites, or exclusions. Implied usage for updating existing subscribers but does not contrast with other tools like tag_subscribers or trigger_flow.

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