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

With no annotations, the description discloses the output format (CSV string), row structure (specific fields listed), and access requirement (PRO plan). It does not explicitly state side effects, but 'export' implies read-only. This exceeds minimal disclosure.

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 concise sentences: purpose, output format, and row structure/plan requirement. It 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?

For a simple one-parameter export tool with no output schema and no annotations, the description is adequately complete. It covers purpose, output, data structure, and access constraint.

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 provides full coverage of the 'period' parameter with enum values and a default description. The tool description does not add parameter-specific details, so 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 clearly states the tool exports emission data as a CSV file, with a specific verb ('Export') and resource ('emission data for all events'). It distinguishes itself from sibling tools, which focus on searching, issuing, funnels, recipients, and validation—none of which export CSV.

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 when a CSV export of emission data is needed, and no sibling tool offers CSV export, so context is clear. It also adds a prerequisite (PRO plan) but does not explicitly name alternatives 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?

With no annotations provided, the description carries the full transparency burden. It does disclose the PRO plan requirement and indicates the output scope (funnel metrics), but it does not explicitly state that this is a read-only operation or describe any potential side effects, error conditions, or pagination behavior. The verb 'Get' implies read-only, but more explicit behavioral disclosure would improve this.

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 with no fluff. The first sentence front-loads the core action and metrics, and the second provides usage context and the plan requirement. Every word 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 a single simple parameter, no output schema, and no annotations, the description covers the essential aspects: what metrics are retrieved, how to use it, and the permission requirement. It lacks detail on the exact return format (e.g., data structure, time range), but for a simple analytics tool this is generally sufficient, making it slightly above baseline.

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

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

Schema coverage is 100%, so the single parameter event_id is already fully described in the schema. The description adds context about the event's funnel but no additional meaning about the parameter itself (format, source, constraints). Baseline 3 applies because the schema does the heavy lifting; no significant additive value from the description.

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 ('Get') and resource ('engagement funnel for a specific event'), then enumerates the exact metrics returned (issued, accepted, viewed, shared, clicked). This distinguishes it from sibling tools like search_events and issue_certificates, which serve different functions.

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

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

The description gives clear usage context: 'Use to understand event performance' and notes the PRO plan requirement. While it does not explicitly list when not to use it or name alternative tools, the sibling list makes differentiation easy. This is 'clear context, no exclusions,' fitting a 4.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the delivery method ('via email (and WhatsApp if enabled)'), the plan requirement ('Requires PRO plan or higher'), and the return format ('Returns emission_id and status per recipient'). This adds useful context beyond the basic action, though it doesn't cover idempotency or error handling.

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 (three sentences) and front-loaded with the primary purpose. The subsequent sentences add essential behavioral details without unnecessary fluff. Every sentence earns its place, 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?

The description is fairly complete for a tool with three required parameters and no output schema. It explains the core action, return values, plan requirement, and delivery mechanism. However, it does not mention the recipients limit (max 500 in schema) or potential asynchronous behavior, which could be relevant for batch operations. The schema covers parameter details, but the description could provide more context on call behavior.

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% parameter description coverage, so the baseline is 3. The description does not add significant new meaning to the parameters; it only rephrases 'event' and 'recipients' without elaborating on badge_id or the structure of recipients. The schema already provides detailed 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 tool's action with a specific verb ('Issue') and resource ('digital certificates') and adds context ('to a list of recipients for a specific event'). This distinguishes it from sibling tools like search_events or list_recipients, which serve different purposes.

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: issuing certificates to recipients for an event. It also includes a prerequisite ('Requires PRO plan or higher'), which is a form of guideline. However, it does not explicitly mention alternatives or exclusions, 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?

No annotations are provided, so the description carries the burden. It discloses key behaviors not evident from the schema: pagination limit (max 50 per page), email masking for privacy, and the PRO plan requirement. It could add more (e.g., error handling), but it covers the most important operational 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 compact yet comprehensive: a single sentence states the core purpose, followed by three short, high-value clauses covering pagination, privacy, and plan requirement. No filler words or 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?

The tool has a simple schema with 3 params and no output schema. The description explains what the tool does, key operational behavior (pagination, masking, plan), and the status filter context. It doesn't describe return format explicitly, but the purpose statement implies the response includes recipient info and status, which is sufficient for a simple list 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% with meaningful descriptions for all parameters (event_id, page, status). The description adds context about pagination and filtering but doesn't elaborate on parameter syntax beyond what the schema already provides. 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 explicitly states the action ('List') and the resource ('recipients for a specific event'), and includes the specific certificate statuses (pending, accepted, refused). This clearly distinguishes it from sibling tools like search_events or issue_certificates.

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 context: listing recipients for a specific event, with pagination and plan requirements. It doesn't explicitly name alternatives or state when not to use it, but the purpose is specific enough to avoid confusion with the listed 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 the full burden of behavioral disclosure. It describes the search scope ('created by your organization') and the return fields (event_id, name, date, total emissions count), but does not explicitly state that it is read-only or describe any side effects. The word 'search' implies safety, but more explicit disclosure would be better.

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 three concise sentences, each adding distinct value: the operation, the use case, and the returned fields. There is no redundant or extraneous wording, making it highly effective.

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 2 parameters, both documented in the schema, and no output schema. The description covers the purpose, direct use case, and return fields, which is sufficient for a search tool. Minor details like matching behavior or pagination defaults are not mentioned, but the essentials 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?

The input schema fully describes both parameters (query and limit) with clear descriptions, achieving 100% schema coverage. The tool description adds no additional parameter semantics beyond what the schema provides, so the 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 uses the verb 'Search' with the resource 'events created by your organization in thatsme', clearly defining the tool's function. It distinguishes from siblings such as issue_certificates and get_engagement_funnel by focusing on event discovery for certificate issuance and engagement checking, which are handled by other tools.

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

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

The description explicitly states when to use the tool: 'Use to find a specific event before issuing certificates or checking engagement.' It does not mention alternative tools or exclusion criteria, but the context is clear enough for an agent to decide without further guidance.

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 key behavioral traits: caller must be an admin of the owning company, cross-issuer attempts are rejected, the original conquest date is preserved, and it creates a certificate (Post). This goes beyond basic mutation disclosure, though it does not detail the full lifecycle of the unverified achievement.

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

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

Three sentences, no filler. Each sentence adds new information: the action and input, the security constraint, and the specific use case. The description is front-loaded and easy to scan.

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 5 parameters (3 required), no output schema, and no annotations. The description covers the core purpose, admin requirement, and a specific workflow, which is sufficient for an AI agent to understand when to invoke it. However, it omits details about return values or side effects on the achievement, leaving a minor gap.

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

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

Schema coverage is 100%, so the baseline is 3. The description does not add significant meaning beyond the schema descriptions. It mentions the relationship between event_id and badge_id, but that is also present in the schema. Overall, the schema already documents the parameters well, so the description contributes minimal additional 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 states a specific action: 'Issue an official retroactive certificate (Post) from a user-submitted unverified Achievement.' It clearly distinguishes from sibling 'issue_certificates' by focusing on retroactive certificates from unverified achievements and the lead-conversion flow, making the tool's purpose unmistakable.

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 exact use case: 'Used for the Hugo Furtado lead-conversion flow.' It also provides important context about caller admin permissions and cross-issuer rejection, but does not explicitly mention when NOT to use this tool or suggest alternatives, which would fully meet the 5-level criteria.

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