profile

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

With no annotations, the description must carry the transparency burden. It discloses a key limitation ('no raw email is published') and implies a contact boundary, but it does not describe the return format or any other behavioral traits such as data freshness or access restrictions.

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, front-loaded with the core content ('Current availability'). While it is a fragment rather than a full sentence, it avoids unnecessary words and is appropriately sized for a simple getter.

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

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

This is a simple tool with no parameters and no output schema, so the description must explain the return value. It lists the information provided (availability, work scope, contact boundary) and one limitation, but it does not specify the structure or format of the returned data, leaving some ambiguity.

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 the input schema is an empty object. Since parameter semantics are not applicable, the baseline of 4 is appropriate; the description does not need to add parameter details.

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

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

The description clearly identifies the resource ('current availability, work scope, and the contact boundary') and the tool name 'get_availability' implies a retrieval operation. However, it lacks an explicit verb and does not distinguish itself from sibling tools like get_profile_summary.

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 mention when to use this tool instead of alternatives such as get_profile_summary or search_faq, nor does it specify any context or 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 are present, so the description carries the full burden of behavioral disclosure. It describes the payload but does not state side effects, permissions, error behavior, or response format beyond the vague 'machine-readable pointers'; the 'get' prefix only weakly implies read-only behavior.

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 terse sentence with no filler, and the core resource is front-loaded. It loses a point for the slightly awkward noun-phrase structure ('Profile summary:') and lack of a clear verb.

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 parameterless read tool, the description conveys the essential return contents (entity identity, availability, pointers) and is sufficient for an agent to invoke it safely. The lack of an output schema lowers the bar, though usage context remains thin.

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

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

The tool has zero parameters, so parameter semantics are not applicable. The baseline of 4 applies because no input guidance is needed and the description does not need to compensate for schema 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 identifies the resource as a profile summary and enumerates its contents (entity fields, availability, machine-readable pointers), making the tool's purpose clear. It does not explicitly distinguish it from siblings like get_availability, but the scope is still understandable.

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 when-to-use guidance or alternative routing is provided. Since the description mentions availability, an agent may be uncertain whether to call this or get_availability; there is no exclusionary note or context for selection.

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 implies a read-only lookup by saying 'full indexed detail,' but it does not explicitly state that it is safe/non-destructive, nor does it mention error handling, authentication, or rate limits. It provides basic context about output content but lacks 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, well-structured sentence that front-loads the core purpose. It includes specific output details without unnecessary fluff, earning a perfect score.

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 and no annotations, the description should provide a clear picture of what to expect. It lists some return values (canonical URL, links, proof count) but does not cover pagination, error behavior, or other potential fields. For a simple lookup tool, it is minimally complete but leaves 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?

Schema coverage is 0%, so the description must compensate. It does clarify that 'slug' refers to the project's slug, which is helpful, but it does not explain slug format, uniqueness, or how to obtain it. For a single parameter, this is adequate but not thorough.

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: retrieving full indexed detail for one project by slug. It specifies the resource (project), the method (by slug), and the content (canonical URL, links, proof count), distinguishing it from siblings like list_projects or get_proof.

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 detailed information for a single project identified by slug. It does not explicitly compare with alternatives, but the context is clear enough that an agent would know to use this for single-project lookup rather than listing or other specific queries.

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 unknown slugs return an error and indicates two modes (default and slug-scoped). This is useful behavioral context, though it doesn't cover return format or side effects (if any).

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, front-loaded with the core purpose, followed by a short error-handling note. 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?

For a simple 1-parameter tool with no output schema or annotations, the description covers the purpose, parameter behavior, and error case. The term 'claim gates' might be unclear to unfamiliar agents, but within the sibling context it is 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 0%, so the description must add meaning. It explains that 'slug' specifies a per-project proof link and that unknown slugs cause an error. This clarifies the optional parameter well beyond the bare 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 function: retrieving verification proof for claim gates, or per-project proof links when a slug is given. This distinguishes it from sibling tools like get_project and get_profile_summary.

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 for proof retrieval, optionally scoped by slug. However, no explicit when-to-use or alternatives are provided, and there is no mention of when choose this over other getter 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. It discloses important behaviors: filters combine with AND, are case-insensitive, and unknown values yield an empty list. It also clarifies tag format and matching. This is strong transparency for a read-only list operation, though it does not mention pagination or sort order.

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

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

The description is concise, with two sentences that first state the core purpose and filter behavior, then provide tag-specific details. Every sentence adds value, and it is well-structured for quick reading.

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 only two optional parameters and no output schema, the description covers key aspects: scope ('portfolio projects'), filter semantics, edge case behavior, and tag format. It is complete enough for agents to use effectively, though it omits details about the returned fields or pagination, which are not critical.

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 provides no descriptions (0% coverage). The description adds meaning for filters overall and specifically elaborates on the 'tag' parameter with format examples and case-insensitivity. However, the 'lens' parameter is not explained beyond its enum values, leaving a partial compensation. The filter behavior applies to both parameters, giving some semantics.

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

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

The description clearly states the tool's function with a specific verb+resource: 'List portfolio projects.' This distinguishes it from sibling tools like get_availability and get_project, which imply different operations (e.g., fetching a single project or checking availability).

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 the tool (to list portfolio projects) and describes optional filters and their behavior, but it does not explicitly mention alternatives or when not to use it. For example, it does not say 'use get_project for a single project,' so guidance is present but not fully 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?

No annotations are provided, so the description carries the full burden. It usefully discloses case-insensitivity, exact-match ranking, and the substring fallback behavior with a concrete example. However, it does not describe no-result behavior, pagination/limit effects, or return shape, which are meaningful gaps for a search 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 leads with the tool's core function and immediately follows with the most decision-relevant behavioral nuance. The example is compact and instructive. 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?

For a simple two-parameter search tool, the description covers matching semantics well enough to invoke it, but the lack of any annotation, output schema, or explanation of the limit parameter leaves the agent with notable gaps around result count and return values.

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

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

Schema description coverage is 0%, so the description must compensate for the two parameters. It gives an example for 'query' that implies the query should be a natural-language question, but it never mentions 'limit', its meaning, or its bounds. Half the parameters remain undocumented in both schema and 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?

States a specific verb and resource: 'FAQ search' with the additional qualifier 'Case-insensitive.' The example also clarifies what type of query produces what result. None of the sibling tools overlap with FAQ searching, so the purpose is 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 makes clear this is the tool for searching FAQ content, and none of the listed siblings are search tools. It does not explicitly state when not to use it, but the resource scope is obvious enough that an agent can select it correctly.

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