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Overfit — German tenders & procurement law

Anzahl der Ausschreibungen abrufen

get_tender_counts
Read-onlyIdempotent

Returns the counts of tender notices across the whole data set: open, urgent (deadline within 14 days), awarded and total, plus the size of the semantic search index, the embedding model name and the health of the portal links. Intended for requests where the user asks how many tenders are open overall or how large and current the tender data is. No parameters, so no filter by topic, region, CPV code or deadline: counts for a topic or region (e.g. open photovoltaic tenders per Bundesland) are the total and by_bundesland fields of a list_tenders result. Key output fields: open_count, urgent_count, awarded_count, total_count, index_size.

Example user questions: "Wie viele Ausschreibungen sind aktuell offen?"; "Wie aktuell ist die Vergabe-Datenbank?"; "Gibt es dringende Ausschreibungen mit Frist in 14 Tagen?"

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description correctly focuses on semantics instead: 'urgent' is defined as deadline within 14 days, and the response is disclosed to include index size, embedding model name and portal-link health. It stops short of describing freshness/latency of those counts, so not a full 5.

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

Conciseness4/5

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

Front-loaded with the return contents and the usage condition before the caveats and examples, so the essential information comes first. Slightly over-long: the no-filter limitation is stated twice (once narratively, once via the list_tenders pointer) and the German example questions add bulk for an otherwise simple tool.

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?

With no output schema, the description correctly enumerates key output fields (open_count, urgent_count, awarded_count, total_count, index_size) and the extra metadata. Combined with the urgent definition and the no-params caveat, an agent has everything needed to call and interpret this read-only counter.

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

Parameters4/5

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

Zero parameters gives baseline 4, and the description earns it by explicitly stating that no topic/region/CPV/deadline filtering is possible and pointing to where filtered counts live. No further parameter detail is applicable.

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?

Opens with a specific verb+resource ('Returns the counts of tender notices') and enumerates exactly which counts (open, urgent, awarded, total) plus index/model/link-health metadata. This clearly separates it from list_tenders, search_tenders and find_procurement_procedures, which return records rather than aggregates.

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?

States the intended trigger ('how many tenders are open overall', 'how large and current the tender data is') and explicitly excludes filtering, naming the alternative: topic/region counts come from the `total` and `by_bundesland` fields of a list_tenders result. Example user questions reinforce the routing decision.

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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