Tech.eu Funding Explorer

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering safety and non-exhaustive results. The description adds useful behavioral details: case-insensitive substring matching and the returned fields (id, location, verified funding totals). It does not elaborate on open-world aspects like result limits or pagination, but annotations cover that baseline.

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, front-loaded with the primary action, and every phrase adds value: matching mode, returned fields, and a pointer to get_company. No redundancy or 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 simple one-parameter search tool with strong annotations and no output schema, the description is complete. It covers the search semantics, return content, and onward workflow. The openWorldHint annotation handles potential result size ambiguity, so no further detail is necessary.

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 a documented 'query' parameter, so the baseline is 3. The description adds the case-insensitive substring behavior, which the schema does not explicitly state. This extra semantic nuance helps the agent understand how to form queries and what results to expect.

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 begins with 'Find companies by name (case-insensitive substring)', which is a specific verb, resource, and matching semantics. It clearly differentiates from siblings like get_company (which retrieves by id) and other search tools (search_investors, search_rounds) by focusing on company name 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 explicitly instructs to 'pass the id to get_company for the full profile', providing a clear next step and implicitly distinguishing this tool as a lightweight search. It does not explicitly mention when not to use it relative to other search tools, but the name and sibling context make the appropriate use case evident.

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=true. The description adds behavioral context by listing the exact data returned (funding rounds, backers, exit) and noting that figures are source-linked on the company page URL, which clarifies the provenance of the data.

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, information-dense sentence that front-loads the purpose ('Full company profile') and packs all key content into a compact line with 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?

With a single parameter, no output schema, and clear sibling context, the description fully specifies what the tool returns: all major company attributes, funding history, backers, and exit status, plus the source-link behavior. It is complete for an agent to select and invoke correctly.

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% with a single 'id' parameter clearly described as coming from find_companies or search_rounds. The tool description adds no parameter-specific semantics beyond this, 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 clearly states the tool retrieves a full company profile with specific content: description, location, sectors, funding rounds with stage/amount/investors, named backers, and exit if any. The verb is implicit in the name 'get_company' and the resource is specific, distinguishing it from sibling search tools like find_companies and search_rounds.

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 context: it is the detailed lookup after finding companies, confirmed by the parameter description 'Company id from find_companies or search_rounds'. It does not explicitly name alternatives or exclusions, but the workflow is clear and the sibling tools are differentiated by their search-centric roles.

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 adds context about the contents of the returned profile (deal count, companies backed, stage mix, etc.), which goes beyond the readOnlyHint annotation. However, it does not mention behavior like error handling, pagination, or any limitations. Given the annotations already declare safety, the description provides modest additional 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 a single, concise sentence that front-loads the tool's purpose. Every word earns its place, listing key data points without filler or repetition.

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 lists the key output categories, which is helpful given there is no output schema. However, it lacks details on how to use the tool (e.g., providing an investor name) and does not address the 'compact' parameter's effect. The tool is simple with good schema coverage, so this is adequate but not rich.

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% with both parameters ('name' and 'compact') already well-documented. The tool description adds no additional explanation of parameters, so it provides no extra value beyond the schema. Baseline of 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 conveys that this tool provides an investor profile with specific data fields (deal count, companies backed, stage mix, portfolio, recent deals). It distinguishes itself from siblings like 'get_company' and 'search_investors' by focusing on a single investor's detailed profile, though the verb 'get' is only implicit in the tool name rather than explicit in the description.

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 such as 'search_investors' or 'find_companies'. The description does not state that this is for retrieving a specific investor's details or mention any exclusions 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?

Annotations already provide read-only and open-world hints. The description adds value by disclosing provenance details (disclosed %, high-confidence %, ECB reconciliation Δ) and the default to the current year, enriching the behavioral profile 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?

Two dense sentences: the first lists all key outputs and quality metrics, the second gives the performance benefit and default. No wasted words, front-loaded purpose.

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 a single optional parameter and no output schema, the description succinctly enumerates all output categories (totals, concentration, breakdowns, provenance) and the default period, making it self-sufficient for invoking 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 single 'period' parameter is fully described in the schema with format examples and default. The description repeats the default and adds context, but provides no new semantic information beyond what the schema already covers.

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 aggregates the European funding picture for a period in one call, enumerating totals, concentration, breakdowns, and provenance. It distinguishes itself from sibling search tools by offering a market-level aggregate rather than individual records.

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 contrasts with paging through every round to sum client-side, indicating the intended use case for aggregate market stats. It implies when to use (high-level funding analysis) but doesn't name sibling tools as alternatives; still, the context is clear.

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 readOnly and openWorld. Description adds significant behavioral context: newest-first ordering, nextCursor pagination, and the data quality caveat that valueEur is null in ~65% of exits. This goes beyond the structured annotations and helps manage expectations about data completeness.

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, front-loaded with purpose, then filters, then a data caveat. Every sentence adds value; there is no redundancy or fluff. It is concise yet packs essential information.

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?

Provides purpose, ordering, pagination, filtering options, and a notable data caveat. With no output schema, it does not list full response fields, but it covers the essential information an agent needs to invoke and interpret results. A slight gap on response structure is acceptable given the schema provides parameter details and the description highlights a key field (valueEur).

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?

Input schema already covers 80% of parameters with descriptions (to, from, country, after). Description reinforces date window and country filtering but adds minimal new parameter semantics. The limit parameter lacks a textual description but has min/max constraints, leaving it reasonably inferable. With high schema coverage, 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?

Description clearly states it searches European tech exits and M&A (acquisitions, IPOs), sorted newest first with cursor pagination. It distinguishes from sibling search tools (companies, investors, rounds) by specifically targeting exits.

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?

Explicitly says 'use it for "European exits"' and describes filters (date window, country), giving clear context for when to apply this tool. Does not explicitly name alternatives or exclusions, but the scope is well-defined and distinct from 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?

Annotations already cover read-only and open-world behavior, lowering the burden on description. The description adds useful behavioral details: entity resolution (name variants merged) and sort options by deal/company count. It does not describe response format or pagination, but the added context is substantive, justifying a score above 3.

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 that front-load the main purpose immediately. There is no fluff or redundant information. Every sentence adds value: the first explains the core function and a key trait, the second mentions sorting capabilities.

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 4 optional parameters and no output schema. The description provides the essential purpose and two behavioral traits, but it omits details like default sort order, pagination behavior, and what fields appear in responses. Given the simplicity of a search tool and good annotations, it is minimally adequate 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 description coverage is 50% (type and query have descriptions; page and sort lack descriptions). The description adds meaning to sort by stating 'sortable by deal count or company count,' which maps to the enum values. However, it does not compensate for the lack of description for page, and type/query are already documented in the schema. The added value is partial.

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+resource: 'Search investors.' It adds a distinguishing feature (entity-resolved, merging name variants) and mentions sortability, which helps differentiate it from sibling tools like search_exits and search_rounds. This is specific and 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 a clear context of what the tool does (search investors with entity resolution and sorting) but does not explicitly mention when to use this tool versus alternatives like get_investor for fetching a single investor. There is no stated exclusions or alternative recommendations, so usage guidance is implied rather than 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?

Annotations already indicate readOnly and openWorld hints. The description adds valuable behavioral details: returns are EUR-normalized at ECB rate, ordered newest first, and paginated via nextCursor. It also notes data is cited. These go beyond the annotations and help predict 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 two sentences, front-loaded with the core purpose, then adding key behavioral details. Every word contributes value with no redundancy or 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 search tool with 8 parameters and no output schema, the description covers purpose, scope, currency normalization, ordering, and pagination. It does not list return fields, but the absence of an output schema and the simplicity of a search result make this acceptable. The description is sufficient to invoke the tool correctly.

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 has 100% description coverage, so baseline is 3. The description adds semantic context for parameters: 'EUR-normalized' clarifies minAmountEur and currency semantics, and 'newest first with nextCursor' explains the 'after' parameter and ordering. This extra context raises the score above baseline.

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 European tech funding rounds, with specific scope (European, tech) and resource (rounds). It also specifies currency normalization and ordering, which distinguishes it from sibling search tools like search_exits and search_investors.

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 this tool (searching funding rounds) and the scope makes alternatives obvious (exits, investors, companies). It does not explicitly name alternatives or exclusions, but the sibling tool names and the specific resource make the usage context clear.

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