profile

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 tells the agent what content will be returned, but it is a noun phrase rather than an explicit statement of behavior or side effects. Read-only behavior is inferable from the name, but the description itself does not state it.

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 containing only the essential information: the subject and the nature of the biography. It is front-loaded, concise, and contains 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?

For a zero-parameter, read-only retrieval tool, the description is nearly complete: it identifies the person and the content type. It does not specify an output format, but it does describe the expected payload. The main gap is the lack of differentiation from similar profile-related siblings.

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 the schema is complete and there is nothing for the description to clarify. The baseline of 4 applies because no parameter-level guidance 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 identifies the resource: the short professional biography of Jaroslav Kazejev. The verb is implicit in the tool name 'get', and the subject is unambiguous. However, it does not explicitly distinguish itself from get_profile_summary or query_profile, so it stops short of a 5.

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 get_bio versus its siblings such as get_profile_summary or query_profile. There are no exclusions, alternatives, or contextual conditions. The agent is left to infer the intended use solely from the tool name and title.

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, but it only adds the word 'public' to signal accessibility. It does not describe the response format, authentication needs, or any limitations, leaving the agent to infer the 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 short phrase with zero filler. The key return types, contact details and profile links, are front-loaded and immediately visible.

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 zero-parameter lookup, the description is minimally sufficient to distinguish this tool from siblings, but without an output schema it leaves the exact fields and structure of 'contact details' unspecified. It could be more explicit about what counts as contact details and profile links.

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 no parameters, so there is nothing for the description to clarify. The baseline of 4 applies because parameter ambiguity is not possible.

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 ('public contact details and the profile links') and the tool name supplies the verb ('get'), so it is clear this returns contact/profile-link data. It is distinguishable from siblings like get_bio or get_profile_summary by its resource, though it does not explicitly contrast itself with them.

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 prefer this tool over get_bio, get_profile_summary, or query_profile. The only implied trigger is needing contact details; no exclusions or alternative tool mentions are 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 full burden of behavioral disclosure. It accurately describes the content returned but does not mention any behavioral traits such as authentication requirements, rate limits, or whether the listing is read-only (though it is implicitly a read). For a zero-parameter fetch tool, this is acceptable but not enriched beyond the basic output description, so a 3 is appropriate.

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 that front-loads the core value ('The complete profile in one response') before enumerating the included sections. There is no superfluous wording, making it both concise and structured for quick parsing.

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 zero-parameter tool with no output schema, the description lists the expected fields and conveys that it returns a comprehensive summary. It does not describe the exact return format (e.g., JSON object structure) but that omission is minor given the simplicity of the operation. The description is sufficient for an agent to understand what it will receive and when to call it.

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 schema is effectively empty with 100% coverage being trivial. Since there are no parameters to explain, the baseline for such tools is 4. The description adds no parameter-specific semantics, but that is not needed here.

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 the complete profile as one response, listing specific fields (headline, location, work status, focus, strongest work, skills, education, links). This distinguishes it from siblings like get_bio (short bio) and get_contact_info (just contact details). The verb 'get' plus explicit resource and content make the 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?

The description implies when to use the tool by labeling it 'the complete profile in one response', which suggests this is the go-to when a full overview is needed. However, it does not explicitly mention alternatives or provide when-not-to-use guidance relative to get_bio, get_contact_info, or list_projects. The usage context is implied rather than stated, so it earns a 3.

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 does not state whether the operation is read-only, what the return format is, or any side effects. The description is nearly empty of 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 very short, which is concise, but it is an uninformative fragment rather than a well-structured sentence. It front-loads nothing meaningful, as 'The projects and the work' does not convey a clear action or resource.

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 absence of an output schema and annotations, the description must compensate by explaining what the tool returns and when to use it. It fails to clearly define the tool's purpose relative to siblings, making it incomplete for an agent to make an informed call.

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 schema coverage is trivially 100%, and the baseline for parameter semantics is 4. The description adds no parameter details, but none are needed for an empty 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 'The projects and the work' is a vague fragment that does not clearly state the tool's function. It implies listing projects, but the meaning of 'the work' is ambiguous. It does not distinguish itself from the sibling profile tools, which are also about listing information (e.g., list_skills).

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?

There is no guidance on when to use this tool versus the sibling tools. No context is given about the intended scenario or any alternatives, leaving the agent without a basis 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 must disclose behavior on its own. It only states that skills are technical and professional; it does not describe the return format, ordering, filtering, or any other behavioral detail. The 'list' verb in the title implies a read operation, but the description adds no 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 extremely terse, but it is under-specified to the point of being a fragment rather than a well-structured instruction. It lacks an explicit verb and conveys only the subject matter, not the operation or output.

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 list tool the scope is small, but with no output schema and no annotations, the description should at least clarify what the returned skills list contains. The brief phrase does not fully equip an agent to know what to expect from the 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 tool has zero parameters, so the baseline is 4. The empty schema fully defines parameter expectations, and there is nothing for the description to add about individual 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 title and name both include 'list' and 'skills', and the description identifies the resource as 'technical and professional skills'. However, the description itself is a noun phrase rather than a statement of what the tool does, and it does not differentiate the tool from siblings beyond naming a distinct 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 about when to use this tool versus alternatives such as list_projects or query_profile. There is no mention of use cases, context, or exclusions, leaving the agent to infer when skills are needed.

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 the tool returns evidence and that the result includes projects, skills, and education, which is useful. However, it does not specify the structure of the result, potential pagination, error behavior (e.g., no matches), or that it is a read-only operation. This is acceptable for a simple query tool but not fully transparent.

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

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

The description is concise, with the core action front-loaded in the first sentence. It avoids redundant phrasing and includes only essential clarifying details. The length is appropriate for a one-parameter search tool.

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

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

The tool is straightforward, but there is no output schema, so the description should indicate the return format more concretely. It mentions projects, skills, and education but does not describe how they are structured (e.g., list of objects, excerpts) or whether the response is flat or nested. Given the low complexity, this is a moderate 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?

Although schema coverage is 100%, the description adds meaningful examples ('MCP', 'C# performance', 'cryptography', 'physics') and clarifies that the topic should be a subject, technology, or skill. This goes beyond the schema's bare parameter description and helps the agent choose appropriate values.

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 'Searches' and the resource 'profile', and explains that it returns evidence for a given topic. It distinguishes itself from sibling tools like list_projects and list_skills by explicitly mentioning it returns matching projects, skills, and education, which sets it apart as a cross-category search rather than a simple list operation.

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 by the description: if you have a specific topic to search, use this tool. However, there is no explicit mention of when not to use it or alternatives such as list_projects for a full list. The description gives examples of topics but does not state a decision rule against using sibling tools.

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