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Diavgis — Greek Public Procurement

by gr.diavgis

Find Entity by Name

find_entity
Read-onlyIdempotent

Resolve a Greek buyer or supplier NAME to its ΑΦΜ. Use this first whenever you have a name but no ΑΦΜ — get_entity, entity_counterparties and the buyer_afm/supplier_afm filters all need the 9-digit number. Matching is accent- and case-insensitive; returns the closest names with their ΑΦΜ, so pick the right one before calling anything else.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoRestrict to public bodies (buyer) or companies (supplier). Omit for all.
nameYesFull or partial name, e.g. "Δήμος Αθηναίων". Accents and case are ignored.
limitNo1-20, default 8

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
matchesYes

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses that matching is accent- and case-insensitive and that the tool 'returns the closest names with their ΑΦΜ,' which is crucial behavioral information for an agent expecting a single exact match. It also warns that the user must 'pick the right one,' signaling possible ambiguity. This goes well beyond the readOnlyHint/idempotentHint annotations, which already cover safety but not matching semantics.

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 sentences, each with a distinct job: purpose, usage context, and matching behavior. The most important information is front-loaded, and every clause adds value. There is no filler or redundant restating of the title or annotations.

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

Completeness5/5

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

The description, combined with rich annotations (readOnlyHint, idempotentHint, openWorldHint) and a full output schema, gives an agent everything needed to decide when and how to call this tool. It covers the lookup semantics, the multi-result behavior, and the dependency relationship with sibling tools. Nothing critical is missing.

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 100%, so baseline is 3. The description partially reinforces the 'name' parameter semantics by framing it as a fuzzy lookup and hinting at multiple results with 'closest names,' but it adds little detail about 'kind' or 'limit' beyond what the schema already documents. It does not repeat or contradict the schema, but it also does not substantially enrich parameter understanding.

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 opens with a specific verb and resource: 'Resolve a Greek buyer or supplier NAME to its ΑΦΜ.' This clearly distinguishes the tool as a name-to-tax-id lookup, which is different from siblings like get_entity or entity_counterparties that require an ΑΦΜ. The purpose is unambiguous and immediately actionable.

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

Usage Guidelines5/5

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

The description states exactly when to use the tool: 'Use this first whenever you have a name but no ΑΦΜ.' It explicitly names dependent tools and filters (get_entity, entity_counterparties, buyer_afm/supplier_afm) that need the 9-digit number, and advises picking the right match before calling anything else. This provides both positive and negative usage guidance.

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

All Diavgis — Greek Public Procurement toolsInspect
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TDQS

A4.4/5.0
Disambiguation4/5

Each tool targets a distinct concern: entity resolution, entity profiles, counterparties, rankings, spend aggregates, search, act detail, lifecycle chains, expiring contracts, and quota. Minor overlap exists between get_act and get_chain since get_act can include lifecycle chain data, but the descriptions make the intended primary use clear.

Naming Consistency4/5

All names use snake_case and most follow a verb_noun pattern like find_entity, get_entity, search_tenders, and rank_entities. A few tools such as entity_counterparties and expiring_contracts are noun-phrase names, and spend_by_cpv uses a different structure, so the pattern is mostly consistent but not uniform.

Tool Count5/5

Ten tools is well-scoped for a Greek public procurement data API: the count is large enough to cover discovery, search, entity analytics, spend analytics, lifecycle detail, and quota management without feeling bloated. Each tool appears to earn its place with no obvious redundant duplicates.

Completeness5/5

The tool surface covers the full read-only procurement workflow: resolve names to tax IDs, profile entities, find counterparties, rank entities, search tenders with filters, inspect individual acts, follow lifecycle chains, monitor expiring contracts, and aggregate spend by CPV. There are no major missing operations for the stated purpose.

Resources