EU Fund Portal

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description says 'Fetch', implying a read-only operation, but it doesn't disclose authentication requirements, rate limits, pagination behavior, data freshness, or any side effects. It also doesn't explain whether the tool aggregates multiple records or returns a single item. The list of returned fields is useful but that's more about output than 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 a single, front-loaded sentence that immediately states the action and then lists the key data points. There is no wasted wording, and the purpose is immediately clear. This is an example of efficient, well-structured description.

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, the description must explain what the tool returns. It does: 'award winners, contract award values, AI conviction scoring, and company catalysts'. This is sufficient for an agent to understand the return type. However, it doesn't clarify whether the output is a list, how the 'recent' timeframe is defined, or whether country filtering applies to the winner or buyer. The description is reasonably complete but leaves a few minor 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?

The input schema provides 100% coverage, with descriptions for both parameters ('limit' and 'country'). The tool description does not add any additional meaning beyond the schema. Since the schema already documents the parameters fully, a baseline score 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 states a specific verb ('Fetch') and a clear resource ('European public procurement award winners') along with the specific data points (award values, AI conviction scoring, company catalysts). This is distinct from the sibling tools (get_grant_details, search_grants), which focus on grants, so there's no ambiguity about what this tool does.

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 on when to use the tool: 'for investor dealflow and competitor monitoring'. It doesn't explicitly mention alternatives or when not to use it, but the context implies it's for contract award signals, and the sibling names make the difference obvious. A clear exclusion or comparison would push this to 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It communicates that this is a read-style retrieval operation and previews the returned data categories, which is useful. However, it does not mention failure behavior, authorization requirements, or any operational constraints such as rate limits or data freshness.

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 front-loaded sentence that starts with the core action, then packs the most important output facets into a compact list. There is no filler or repetition, and every clause adds useful information for tool selection.

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 single-parameter tool with no output schema, the description is largely complete: it names the input, explains the purpose, and lists what the response will contain. The main gap is the lack of explicit guidance on how this tool relates to its siblings, but the description still provides enough for correct invocation.

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 adds the context that the ID refers to a European grant or tender, which slightly clarifies the parameter's domain, but it does not meaningfully expand on the schema's example-based explanation of grant_id.

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 a specific verb ('Retrieve') and resource ('specific European grant or tender by ID'), and it lists concrete output contents: eligibility checklists, award amounts, deadline countdown, and application links. This naturally distinguishes it from search_grants, which would be used for discovery rather than detail 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 clearly signals that this tool is for retrieving details once a specific grant_id is known, which gives the agent clear context for when to invoke it. It does not explicitly state when not to use it or name alternatives such as search_grants, but the by-ID requirement implies the intended use case.

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 itself must disclose behavior. 'Search' implies a read-only operation and the scope is clear, but there is no mention of result shape, pagination, or limits beyond the schema's default/max. These are useful behavioral details the agent would have to discover elsewhere.

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 the core scope and followed by the query dimensions. Every word earns its place and no unnecessary detail is included.

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 five optional parameters, all fully described in the schema, the description is nearly complete. The main gap is the absence of an output schema or any statement about what fields the returned opportunities contain.

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 provides 100% description coverage for all five parameters, so the description adds little meaning beyond what the schema already offers. The brief mention of query dimensions mirrors the existing 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 names a specific action ('Search') and a well-defined resource ('open European funding opportunities, Horizon Europe calls, national grants, and public tenders across 31 countries'). It also lists the dimensions by which to search, making the tool's role clear and distinct from detail/award retrieval.

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 for using the tool: discovering open funding across countries and categories. It does not explicitly contrast with get_grant_details or get_contract_awards, but the search-oriented wording makes the selection fairly obvious.

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