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lt_get_act

Read-onlyIdempotent

Fetch Lithuanian act metadata by TAR code, including official title, date, and status from the Register of Legal Acts.

Instructions

Fetch Lithuanian act metadata by its TAR code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tar_kodasYese.g. ``"2014-21296"`` (from ``lt_search``).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNo
numberNo
eli_uriNo
eli_noteNoLithuania has no data.europa.eu ELI for the TAR dataset. eli_uri carries the canonical e-tar.lt legalAct URL (the stable national identifier), which is also the source_url.
validityNo
tar_kodasNo
source_urlNo
dataset_noteNoThe Lithuanian Register of Legal Acts (TAR) is served as open data via the data.gov.lt Spinta API (dataset gov/lrsk/teises_aktai/Dokumentas, CC BY 4.0). Acts are addressed by their TAR code (tar_kodas, e.g. '2014-21296'); discover acts with lt_search (matches the title). Full text is in the tekstas_lt field. Language: Lithuanian.
date_adoptedNo
document_typeNo
date_publishedNo
human_readable_citationNo
Behavior3/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds the boundary that it fetches 'metadata' (not full text), which is useful, but does not disclose any additional behavioral traits like output format, rate limits, or error conditions. Consistent with annotations, no contradiction.

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?

A single, front-loaded sentence conveys the core purpose without filler. Every word contributes, making it highly concise and well-structured.

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?

Given the simple one-parameter schema, strong annotations, and presence of an output schema, the description is adequate. It communicates the essential scope (metadata by TAR code) and the structured fields cover the rest, forming a complete picture for this tool.

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 coverage is 100% with a well-described parameter (tar_kodas) including an example and origin from lt_search. The description mentions the TAR code but adds no semantic detail beyond the schema, so baseline 3 is appropriate.

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 uses a specific verb ('Fetch') and resource ('Lithuanian act metadata') and highlights the key ('TAR code'). It clearly distinguishes from siblings like lt_search and lt_get_text by focusing on metadata retrieval by identifier.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or relationship to sibling tools. The schema's parameter description hints at lt_search but the main description lacks explicit usage direction.

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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