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EU & Nordic Grant Finder (AI-matched)

eu_grant_finder
Read-only

Find relevant EU and national grants for your company with AI — matched to your…. Find relevant EU and national grants for your company with AI — matched to your profile, with deadlines and eligibility at a glance.

Input Schema

NameRequiredDescriptionDefault
inputNoInput for EU & Nordic Grant Finder (AI-matched). See https://apify.com/noniner/eu-grant-finder.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that results are AI-matched to a profile and surface deadlines and eligibility — useful output-oriented context since no output schema exists. It says nothing about cost, latency, or auth requirements, so it does not exceed a middling bar.

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

Conciseness2/5

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

The sentence is duplicated verbatim and the first copy is cut off mid-phrase ('matched to your….'). This is pure noise: roughly half the text earns nothing, and the repetition makes the definition look broken rather than front-loaded.

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

Completeness2/5

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

No output schema exists, so the description must carry the return-value burden — and it only gestures at 'deadlines and eligibility at a glance' without describing shape or format. Combined with a nested input object documented only by an external URL, an agent lacks enough to invoke it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is a single 'input' object parameter with 100% schema description coverage, so the baseline is 3. That 'coverage' is only a link to an external Apify page, and the description adds no field-level meaning at all, leaving the nested object effectively opaque — but the rubric's high-coverage baseline applies.

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

Purpose3/5

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

The description does convey a specific verb and resource ('Find relevant EU and national grants for your company'), and the AI-matching plus deadlines/eligibility framing signals the value. However, the text is a truncated marketing blurb followed by an identical repetition, and it never distinguishes itself from closely related siblings such as nordic_public_tenders or nordic_tender_matcher. Discernible purpose, but degraded by the broken copy.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no routing to alternatives. With many grant/tender-adjacent siblings in the list (nordic_public_tenders, nordic_tender_matcher, greenlit), the absence of any disambiguation leaves the agent to guess.

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

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