postari

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

No annotations are provided, so the description carries full burden. It does not disclose behavioral traits like read-only nature, side effects, authentication requirements, or error conditions. The description implies a read operation but does not explicitly state it, leaving ambiguity.

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 of 16 words, front-loaded with the main purpose. It conveys the essential information without any extraneous text, achieving maximum 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?

The tool has two optional parameters and no output schema. The description lists the metrics returned but does not specify the output format (e.g., counts, percentages, structure). For a stats tool, this lack of output details leaves the agent uncertain about the return value, making it only moderately complete.

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

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

Schema description coverage is 100% for the two optional parameters (to, from). The description mentions 'date range' which aligns with the schema but does not add additional meaning beyond the parameter descriptions. Baseline score of 3 applies.

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

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

The description clearly states the tool retrieves global account metrics (sent, delivered, unique opens, unique clicks, unsubscribes, bounces) within a date range. It uses a specific verb (retrieves) and resource (global account metrics), and distinguishes from siblings which focus on subscribers, campaigns, or lists.

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

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

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention when not to use it or any prerequisites. It simply states what it does without contextual usage advice.

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. Description does not disclose what happens if the contact does not exist, if the list is invalid, or whether the operation is idempotent. Behavioral implications are unclear.

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, concise and to the point. No extra fluff, but could include more detail without sacrificing brevity.

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 3 parameters, no output schema, and no annotations, the description fails to cover essential context like error handling, return value, or edge cases. Incomplete for an agent to reliably 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?

Description adds meaning by explaining that either email or contact_id is used to identify the contact, which is not clear from the schema alone. However, it does not clarify that at least one must be provided, nor does it explain format 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 action: adding a contact to a list, specifying identification methods (email or contact_id). This distinguishes it from sibling tools like 'create_subscriber' which may not involve a 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 on when to use this tool versus alternatives like 'create_subscriber' or 'tag_subscribers'. Missing context about prerequisites or 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, the description carries the full burden but only states the basic action. It does not disclose any behavioral traits such as permissions needed, uniqueness constraints, 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?

The description is concise (one sentence) but is underspecified, lacking structure or additional details that would aid an agent.

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 two parameters and no output schema, the description is incomplete. It omits important context like uniqueness of names, required scopes, or what happens on success.

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 50% (only 'name' is described). The description adds no value beyond the schema; it does not explain the 'description' parameter or any 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?

The description clearly states the tool creates a new contact list. It uses a specific verb-resource combination and is distinct from sibling tools like list_lists and 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. For instance, it does not mention that add_subscriber_to_list should be used for adding subscribers or that list_lists is for viewing existing lists.

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 discloses the upsert behavior (no duplication), which is key. However, it lacks details on how fields merge when updating, whether email is the unique identifier, and any side effects or prerequisites. The transparency is adequate but not comprehensive.

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 directly conveys the core functionality. No redundant words or structures. It earns its place without any 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 7 parameters, 1 required, no output schema, and no annotations, the description covers the essential behavior but lacks details on error handling, idempotency, or differentiation from sibling update_subscriber. It is minimally complete but leaves gaps for complex scenarios.

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 57% (4 of 7 properties have descriptions). The description adds no extra information about parameters beyond what the schema already provides. It does not clarify phone format, last_name/first_name usage, or metadata expectations. Baseline 3 is appropriate given moderate 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 clearly states the tool performs an upsert (create or update) on a contact/subscriber, using specific verb 'crea o actualiza' and resource 'contacto/suscriptor'. It distinguishes itself from sibling tools like update_subscriber (which likely updates only existing) and add_subscriber_to_list (which is list-specific).

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 creating or updating a subscriber, but does not provide explicit guidance on when to choose this over update_subscriber or other alternatives. No exclusion criteria or context are given, leaving the agent to infer from the tool name and description.

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 burden. It discloses the time range (últimos 28 días), checked metrics, and output format (veredict + acciones). However, it does not explicitly state whether the tool is read-only or has side effects, but given its diagnostic nature, this is a minor 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 two sentences, no wasted words. Information is front-loaded and every sentence adds 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 no parameters and no output schema, the description covers inputs, analysis details, and output format completely. It tells the agent exactly what to expect.

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

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

The tool has zero parameters, and schema coverage is 100%. Per guidelines, baseline is 4. The description adds no param info because none is needed.

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 deliverability of the account, covering specific metrics (rebotes, quejas, aperturas, salud del dominio) and returns a verdict with prioritized actions. It uses a specific verb ('diagnose') and resource ('deliverability'), differentiating it from sibling tools like account_stats or list_campaigns.

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

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

Explicit usage guidance is provided: 'Úsalo antes de un envío grande o si los correos no llegan.' This clearly tells when to use this tool versus alternatives, which are about campaigns or subscribers.

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 burden. It discloses that the tool lists actions and what information is returned, but does not mention any behavioral traits such as pagination, ordering, side effects, or auth requirements. For a simple read operation, this is minimally sufficient.

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 consists of two sentences that are moderately concise. It front-loads the purpose with the metaphor 'Transparencia qué hizo la IA' and quickly provides specifics. It is efficient but could be slightly more compact.

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 low complexity (one parameter, no output schema, no annotations), the description is complete. It explains what the tool does, what information is returned, and for what purpose (auditing). No major gaps in context are present.

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 for the single parameter 'limit' is 100%, explaining it is a number between 1-100 with default 50. The description does not add any additional semantic details about the parameter, so it meets the baseline but adds no extra value.

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

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

The description clearly states the verb 'lista' (lists) and the resource 'acciones de la cuenta originadas por un agente/IA', including specific sources and the types of information provided (qué, sobre qué, cuándo). It effectively distinguishes this tool from its siblings, which are focused on campaigns, subscribers, and other non-agent activities.

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 use for auditing agent actions but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. Sibling tools like 'account_stats' or 'diagnose_deliverability' are not compared, leaving the agent without clear selection criteria.

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 does not disclose whether the tool is read-only, has any permissions requirements, rate limits, or behavior on invalid IDs. It mentions 'real metrics' but omits critical behavioral context.

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

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

The description is a single, concise sentence that efficiently conveys the tool's purpose. However, it lacks structure (e.g., separate sections for input/output) and is solely in Spanish, which may limit accessibility.

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 simplicity (1 parameter, no output schema), the description lists the main metrics but omits details like aggregation, date ranges, or data format. It is somewhat complete but could be more precise, especially since there is no output 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 does not add parameter-level semantics; it only describes the output. No extra meaning beyond the schema is provided.

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 explicitly states 'Real metrics of a campaign' and lists specific metrics (sent, opens, clicks, bounces, unsubscribes, revenue), clearly identifying the tool's purpose and distinguishing it from siblings like list_campaigns and account_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?

No guidance is provided on when to use this tool versus alternatives. It does not mention that for listing campaigns, use list_campaigns, or for account-level stats, use account_stats. The description lacks context on appropriate usage scenarios.

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 operation by stating 'devuelve' (returns), but does not explicitly confirm non-destructive behavior or mention error handling, authentication needs, or rate limits. With no annotations, more detail would be beneficial.

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 Spanish sentence that efficiently states the action and output. Every element serves a purpose with no redundancy.

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

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

For a simple one-parameter tool with no output schema, the description adequately covers typical use cases. It lists return fields (data, status, tags, basic history) but lacks detail on response format or error conditions.

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 'email' has a schema description of 'Correo a buscar.' which is essentially the same as the tool description's usage. With 100% schema coverage, the description adds no new meaning, meeting baseline expectations.

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 searches for a contact by email and returns data, status, tags, and basic history. It distinguishes from siblings like create_subscriber (creates) and update_subscriber (updates) 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 explicit guidance on when to use this tool vs alternatives is provided. The purpose implies usage for subscriber lookup, but there is no contrast with sibling tools like get_campaign_stats or diagnose_deliverability.

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 explains the two-step workflow (draft then send), default no-send behavior, AI generation, and auth requirements. Missing details on idempotency or error handling, but overall it discloses key behavioral traits.

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 about 100 words, front-loaded with the main purpose. It has a logical flow: purpose, workflow, default behavior, requirements. Every sentence adds value, though it could be slightly more 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 13 parameters, nested objects, and no output schema, the description covers the essential workflow, two-step calling, scope needs, and parameter alternatives. It references sibling tool list_lists for list_id. Lacks explanation of response format and error scenarios, but is fairly complete for typical 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?

Schema coverage is 100%, baseline 3. The description adds context: clarifies the relationship between brief, blocks, html_body (alternatives), explains confirm_send and scheduled_at usage, and reinforces the generative nature. This adds meaningful semantic 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's purpose: 'Lanza una campaña de correo COMPLETA desde un brief en lenguaje natural.' It uses specific verbs and resources, and distinguishes itself from sibling tools like list_campaigns or send_transactional_email by focusing on generative campaign creation 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 provides explicit guidance: default no send, requires a second call with confirm_send for actual sending or scheduled_at for scheduling. It mentions required scopes (write/send) and tenant configuration. However, it does not explicitly exclude alternatives like send_transactional_email.

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, and the description does not disclose behavioral traits such as read-only nature, pagination, or authentication requirements.

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 with no wasted words, clearly front-loaded with the core action.

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 lacks information about return structure, pagination, or sorting, making it incomplete for full understanding.

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%, and the description adds the specific status filter values (draft, scheduled, sending, sent), which are not in 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 lists campaigns/emails with optional status filtering, but does not explicitly differentiate from sibling tools like list_lists or get_campaign_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?

No guidance is given on when to use this tool versus alternatives, or any prerequisites.

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 carries full burden. It describes output (name and count) but does not mention pagination, ordering, or any side effects. Read-only assumed but not 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?

One sentence that is concise and front-loaded with the action. Could be slightly more structured but 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?

Minimal description for a simple tool. No output schema, so returns unclear. Adequate but could add context about list types or uniqueness.

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, so baseline is 4. The description adds meaning by specifying the output includes name and count, which is not in 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 verb 'Lista' and the resource 'listas de contactos' with scope 'del tenant' and what is returned 'nombre y conteo'. It distinguishes from siblings like create_list 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 explicit guidance on when to use versus alternatives. It is implied for listing all lists, but no mention of filtering or when not to use.

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?

Discloses synchronous nature and scope requirement. No annotations provided, so description carries full burden. Lacks details on error handling, delivery guarantees, idempotency, or return value.

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?

Brief single sentence conveying type, examples, sync, and scope. No fluff, but could be slightly more 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?

For a 6-parameter tool with nested objects and no output schema, description covers purpose, usage, and basic behavior. Lacks error handling and response details but overall adequate.

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 parameters are well documented. Description adds only that it uses template and variables, and mentions sync/scope but not unique parameter semantics beyond 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?

States it sends a 1-to-1 transactional email (quotes, receipts, etc.) to one address using a template and variables. Clearly distinguishes from sibling tools like launch_campaign which send bulk or triggered 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?

Defines use case as transactional emails and states it is synchronous and requires scope 'send'. Does not explicitly list when not to use it or compare to alternatives like trigger_flow or campaign 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, the description must fully convey behavioral traits. It indicates a mutable operation (add/remove) but omits details like idempotency, error handling if the tag or contact is missing, 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?

The description is a single efficient sentence, but its brevity sacrifices critical detail. It is front-loaded but insufficiently informative.

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

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

Given no output schema, 4 parameters, and sibling tools, the description lacks completeness. It does not explain the return value, error scenarios, or constraints, leaving the agent underinformed.

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 50%; only 'tag' and 'operation' have descriptions in the schema. The description vaguely mentions 'emails or contact_ids' but adds no additional meaning beyond the schema, failing to compensate for the missing parameter descriptions.

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 (add or remove a tag) and the resource (multiple contacts). It also specifies the identification methods (emails or contact_ids), making the tool's purpose 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?

No guidance is provided on when to use this tool versus alternatives (e.g., vs. 'add_subscriber_to_list' for list membership). There is no mention of prerequisites or excluded scenarios.

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, and the description does not disclose behavioral traits such as whether the tool is idempotent, if it overrides existing flow membership, or any authorization requirements. The phrase 'para que reciba esa secuencia' implies the contact will receive a sequence, but no side effects or limitations are mentioned.

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, concise and front-loaded. It efficiently communicates the core action without 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?

Given the complexity (4 parameters, nested object, no output schema, no annotations), the description is insufficient. It does not explain what happens upon success, error conditions, or behavior when both email and contact_id are provided. The lack of output schema information also reduces completeness.

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 value by indicating that either 'email' or 'contact_id' can be used, which is not clear from the schema alone. However, it does not explain the 'trigger_data' object parameter, and schema coverage is low (25%). The description partially compensates for the gap but is not comprehensive.

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: add a contact (by email or contact_id) to an automatic flow. It specifies the resource (flow) and the verb (trigger). However, it does not explicitly mention that flow_id is required, which is a minor gap.

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 'add_subscriber_to_list' or 'send_transactional_email'. The description does not specify prerequisites or conditions for using email vs contact_id.

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 full burden. It only says 'updates data', without mentioning idempotency, permission requirements, what happens if the subscriber doesn't exist, or whether updates are partial or full. 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?

The single-sentence description is very concise and to the point. However, its brevity comes at the cost of missing necessary details. It is front-loaded but could be slightly expanded without losing 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 tool has 6 parameters, no output schema, and no annotations, the description is incomplete. It fails to specify return value, error behavior, or how updates affect existing data. A mutation tool requires more context 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 description coverage is 0%, so the description should compensate. It lists 'nombre, país, teléfono, etiquetas', but the schema has first_name and last_name separately, so 'nombre' is ambiguous. It omits the crucial role of 'email' as the required identifier. Parameter meanings are only partially clarified.

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 updates an existing contact's data, listing example fields (name, country, phone, tags). This distinguishes it from sibling tools like create_subscriber and get_subscriber. However, it doesn't explicitly specify that 'email' is the identifier, which is implied by the schema.

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

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

The description does not provide explicit when-to-use or when-not-to-use guidance. The purpose implies it is for updating existing subscribers, not for creating (create_subscriber) or tagging only (tag_subscribers), but no direct comparison is given.

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