EU Fund Portal

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

With no annotations, the description carries the full behavioral burden, and it partially meets it: it states the EUR value semantics (original amount and currency retained) and that a source link is returned. It says nothing about ordering beyond 'recent', pagination beyond the schema's limit, rate limits, or whether any fetch requires authentication.

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 with no filler; the what-it-returns content is front-loaded and the filtering capability is placed last as a secondary detail. The field enumeration is dense but each item is meaningful, so little would be gained by trimming.

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?

There is no output schema, so the description's enumeration of return fields (winner name/ID, buyer, value, dates, source link) is genuinely necessary and is provided. For a 3-parameter, all-optional read tool this is nearly complete; only ordering/pagination behavior and the meaning of 'recent' are left unspecified.

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 limit, country, and winner_type are all already documented in the schema, including the enum examples. The description only reaffirms the startup-vs-commercial distinction and adds the EUR/original-currency note, which is output semantics rather than parameter meaning, so the baseline 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 names a specific verb and resource ('Fetch recent European public procurement and grant award winners') and enumerates the returned fields, so the agent knows exactly what it retrieves. It does not explicitly distinguish itself from the grant-oriented siblings (get_grant_details, search_grants), and because winner_type='startup' pulls in grants, the boundary with those siblings is blurred rather than clarified.

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 only usage signal is the trailing 'Supports filtering by startup grants vs commercial tenders', which implies the filter but gives no when-to-use guidance, no exclusions, and no reference to the sibling tools the agent should pick instead. Adequate as a hint, not as routing guidance.

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 carries the full burden and does so: it discloses source coverage per tier, which entity types are filtered out (project vehicles, banks, holdings, mid/large companies, known subsidiaries), and the important caveat that 'first award' means earliest in this dataset, not first ever. That is exactly the kind of non-obvious behavior an agent would otherwise get wrong.

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 key scope statement is front-loaded in the first sentence and every subsequent sentence adds verifiable information rather than filler. It is dense, with heavy parentheticals and semicolons, but the length is justified by the total absence of annotations.

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?

No output schema exists, yet the description enumerates the company-card fields returned (name, country, founding year, funder, amount, sector, one-line summary) plus the language caveat, and it explains the filtering logic that determines membership. An agent has everything needed to call it and interpret the results.

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%, so the schema defines all five parameters. The description still adds real meaning: it explains why tier A excludes German federal projects (no reliable founding date), clarifies that 'days' keys off first award in this dataset, and notes the whatLanguage caveat for French/German summaries.

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 resource with precise scope: a direct feed of young European companies that just received non-dilutive public funding, with explicit inclusion/exclusion criteria. It is clearly distinct from contract awards and grant search by resource, though it never names a sibling tool to contrast against.

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 through the tier semantics (A vs all) and the defaults (30 days, tier A), giving the agent a sense of the precision/recall tradeoff. However, there is no explicit 'use this when X, use search_grants or get_grant_details when Y' routing guidance.

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 search but says nothing about result ordering, pagination beyond the limit param, coverage freshness, or what a returned item contains. The winner_type field hints that the tool mixes open calls with awards, but this behavioral nuance is never explained in prose.

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, zero filler, with the breadth of coverage front-loaded before the queryable facets. Every clause earns its place.

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 six-parameter search tool with no annotations and no output schema, the description covers scope and query surface but leaves gaps: no guidance on which sibling to use for details or awards, and no statement about what results look like or how many are typically returned. Adequate but not complete.

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 schema already documents all six parameters, including enums and examples. The description restates the queryable facets (keyword, country, category, tech vertical) without adding syntax, defaults, or combination rules beyond the schema. Baseline 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 names a specific verb (Search) and a well-scoped resource (open European funding opportunities, Horizon Europe calls, national grants, public tenders across 31 countries). It is clear enough to distinguish the discovery function from get_grant_details and get_contract_awards, though it never explicitly names those siblings as alternatives.

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 when-to-use or when-not-to-use guidance and no mention of the sibling tools. An agent can infer this is the exploratory search entry point, but the description never states that get_grant_details should be used for follow-up detail or get_contract_awards for historical awards.

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