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mayai-it

bandiradar-mcp

by mayai-it

search_opportunities

Ranks Italian public funding opportunities matched to a company profile. Accepts a profile path or inline profile, with adjustable precision mode and options to include benchmark notes and attached document text.

Instructions

Rank opportunities for a profile (offline in sample mode).

Accepts EITHER ``profile_path`` OR an inline ``profile`` dict. Returns ranked
canonical views — no raw payloads. ``mode`` is the operating point
(precision|balanced|recall; precision needs an LLM key); an explicit ``min_score``
overrides it. ``with_benchmarks`` adds ANAC historical benchmark notes;
``with_documents`` folds attachment-PDF text into matching.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profile_pathNo
profileNo
sourceNo
sampleNo
modeNobalanced
min_scoreNo
limitNo
with_benchmarksNo
with_documentsNo
dbNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses offline sample mode, return format (canonical views, no raw payloads), mode options and the LLM key requirement for precision, and effects of min_score, with_benchmarks, and with_documents. This provides solid behavioral context.

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

Conciseness5/5

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

Three concise sentences with front-loaded purpose. Every sentence adds value; no wasted words.

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

Completeness4/5

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

Given 10 parameters and an output schema, the description covers input alternatives, mode behavior, key flags, and output format. It misses a few basic parameters (source, sample, limit, db) but these are self-explanatory from the schema, so overall complete.

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?

Schema description coverage is 0%, so description must compensate. It explains profile_path vs profile, mode, min_score, with_benchmarks, and with_documents, but omits source, sample, limit, and db. This partial coverage earns a 3.

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

Purpose5/5

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

The description clearly states the tool ranks opportunities for a profile in sample mode, distinguishing it from sibling tools like fetch_opportunities (which likely fetches existing opportunities) and get_matches.

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

Usage Guidelines3/5

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

It explains the mutually exclusive inputs (profile_path vs profile dict) and mode details, but does not explicitly state when to use this tool over alternatives like fetch_opportunities or get_matches.

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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