GP Intel

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

Annotations already declare readOnlyHint=true, so the description adds value by detailing the output structure (company, exit year, exit route, hold period) and the optional year filter. No contradictions, and it provides helpful context beyond annotations.

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

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

Two concise sentences with a clear front-load of purpose, then a list of return fields. No unnecessary words or redundancy. Perfectly structured for quick comprehension.

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 2-parameter tool with no output schema, the description adequately covers the return fields and the key limitation of generic search. It lacks details on pagination, ordering, or error cases, but these are reasonable omissions for such a straightforward 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 description coverage is 100%, so the baseline is 3. The description reiterates the parameter purpose ('optionally for a specific year') but does not add new semantic details like name formatting or constraints beyond what the schema provides.

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 ('List'), the resource ('exits/realised divestments'), and the scope ('of a private equity firm, optionally for a specific year'). It also lists the specific return fields (company, exit year, exit route, hold period), which differentiates it from sibling tools like gp_portfolio. No tautology or vagueness.

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 a concrete example of when to use this tool ('what did GP X sell in YEAR') and notes that general AI search cannot answer it reliably. However, it does not explicitly compare to siblings or mention when not to use it, leaving some ambiguity.

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

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

Annotations already mark as readOnlyHint=true. Description adds output fields but no extra behavioral details like auth needs or rate limits.

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

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

Two sentences: first for purpose and filter, second for output fields. No fluff, front-loaded.

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?

Covers main purpose, filter, and output fields. Missing minor details like pagination or sorting, but adequate for a simple 2-param 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 description coverage is 100%, so schema fully documents parameters. The description adds no new semantic info beyond schema examples.

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?

Clearly states verb 'List' and resource 'portfolio companies of a private equity firm'. Differentiates from siblings like gp_exits (exits focus) and search_companies (broader).

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?

Mentions optional filter for active/exited positions, giving context. Lacks explicit when-not-to-use or comparison with sibling tools like search_companies.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds that it searches over '21,000+ PE-backed companies' and uses name matching. This adds moderate context over annotations but does not discuss pagination, rate limits, or result format.

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

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

The description is a single sentence, front-loaded with the action and resource. Every word is meaningful 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 search tool with no output schema, the description covers the core purpose adequately. It could mention the default limit or result count behavior to be fully complete, but it is sufficient 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 description coverage is 50% (query described, limit not). The description reinforces 'query' by stating 'by name' but does not clarify 'limit'. This partially compensates for the missing schema description, but more detail on limit behavior would improve completeness.

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 'Search', the resource 'PE-backed companies', the scope 'tracked on GP Intel', and the method 'by name'. It effectively distinguishes from sibling tools like 'search_gps' (likely searching GPS) and 'who_owns' (ownership lookup).

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

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

The description provides no guidance on when to use this tool versus alternatives (e.g., search_gps, gp_portfolio). It only states what the tool does, not when it is appropriate or not.

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?

Annotations already indicate readOnlyHint=true, so the description doesn't need to restate. It adds useful info: 'Buyer names and MOIC stay locked unless authenticated as Pro', revealing data access restrictions. No contradictions with annotations.

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

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

Two sentences: first packs all key features, second adds an example and authentication note. Every phrase adds value, no repetition or fluff.

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

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

For a complex search with 10 parameters and no output schema, the description covers essential aspects: cross-firm scope, filters, grouping, and restrictions. Could mention pagination behavior, but schema already defines limit/offset.

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. Description enhances this by showing usage of group_by for counts and clarifying year_from/year_to as a range. Provides an example query that ties parameters together.

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's a cross-firm investment search tool across all European PE firms with specific filters (entry year, sector, geography, status). It distinguishes from sibling tools like search_gps and search_exits by focusing on deals across firms.

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?

Description provides explicit usage context with an example query and explains the group_by parameter for counting. It also mentions authentication restrictions, but lacks explicit when-not-to-use or direct comparisons with all sibling tools.

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

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

The description aligns with readOnlyHint true by referring to searches and filters. It discloses behavioral traits: authentication requirements for certain data (buyer names, MOIC) and that group_by changes output from list to count. No contradictions with annotations.

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 yet informative, front-loading the key differentiator and usage example. Every sentence contributes value, though it could be slightly tighter by merging some details. It avoids redundancy with the schema.

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 explains the two output modes (list vs. count) and covers all parameters. It provides enough context for an agent to use the tool correctly, including authentication restrictions. A minor gap: it does not mention pagination behavior beyond limit/offset schema descriptions.

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%, but the description adds meaning beyond the schema: it explains the group_by parameter's purpose with an example, defines 'GP-led' exit type, and notes that the buyer parameter is ignored for anonymous callers. This adds value, though some parameters (e.g., geo, sector) receive no extra explanation.

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 cross-firm exit searches across all European PE firms, distinguishing it from per-firm tools like gp_exits. It specifies filtering capabilities (year, exit route, sector, geography) and provides examples, making 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 gives specific usage guidance, such as using group_by for counts and the example query for GP-led exits. It contrasts with per-firm tools and notes Pro restrictions for buyer names and MOIC. However, it does not explicitly state when not to use this tool versus alternatives, which is a minor gap.

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?

Annotations already declare readOnlyHint=true, so no destructive behavior is expected. The description adds that it returns specific fields (country, AUM, strategies), providing positive behavioral insight without contradicting annotations.

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

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

The description is a single, efficient sentence that immediately states the action and scope. Every word adds value, and no unnecessary information is present.

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 covers essential functionality: search scope, input (name), and output fields. However, it lacks details on result ordering, pagination, or default limit behavior, which would be useful for a search tool without an 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 50% (only 'query' described). The description adds no detail for the 'limit' parameter, which has no schema description. It does not compensate for the missing parameter documentation.

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

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

The description clearly states the tool searches for European private equity firms by name and specifies the return fields (country, AUM, strategies). It distinguishes itself from sibling tools like gp_exits and search_companies by focusing on GPs.

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 looking for a GP by name but does not provide explicit when-to-use/when-not-to-use guidance or mention alternative sibling tools. The context is clear but guidance is only implicit.

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?

Annotations already provide readOnlyHint=true, but description adds significant behavioral context: covered companies, hand-verified, ownership history details. No contradictions.

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

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

Two sentences, front-loaded with purpose, no redundant text. 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?

Covers purpose, scope, output details, and data source. Lacks explicit return format but no output schema exists; acceptable for a simple lookup 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?

Only one parameter with 100% schema coverage; description adds value by explaining the input can be company name or slug and provides examples.

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 finds current private equity owner(s) and full ownership history, including entry years and exits. It specifies the scope (21,000+ European PE-backed companies) and distinguishes from sibling tools by focusing on ownership details of a specific company.

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 use cases given ('who owns X', 'X parent company'), but no explicit when-not-to-use or direct comparison to siblings, though sibling list provides context.

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