Skip to main content
Glama

analyze_act_relationships

Analyze relationships and references between Polish legal acts. Retrieve amendments, repeals, legal bases, and consolidated texts using an ELI identifier. Filter by relationship type for targeted results.

Instructions

Przeanalizuj powiązania i referencje między aktami prawnymi.

Zwraca informacje o aktach zmienionych, zmieniających, uchylonych, podstawie prawnej i tekstach jednolitych.

Przykłady:

  • analyze_act_relationships(eli="DU/2024/1716") - Wszystkie powiązania

  • analyze_act_relationships(eli="DU/2024/1716", relationship_type="Akty zmienione") - Jakie akty zmienił

  • analyze_act_relationships(eli="DU/2024/1716", relationship_type="Podstawa prawna") - Na jakiej podstawie powstał

  • analyze_act_relationships(eli="DU/2024/1716", relationship_type="Akty zmieniające") - Co go zmienia

  • analyze_act_relationships(eli="DU/2024/1", relationship_type="Akty uznane za uchylone") - Uchylone akty

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eliYesIdentyfikator ELI aktu. Format: "{wydawca}/{rok}/{pozycja}". Wydawcy: DU (Dziennik Ustaw), MP (Monitor Polski). Przykłady: "DU/2024/1716", "MP/2023/500", "DU/2024/1".
relationship_typeNoFiltruj po typie powiązania (dokładne dopasowanie do klucza z API). Dostępne typy: 'Akty zmienione', 'Akty zmieniające', 'Akty uchylone', 'Akty uchylające', 'Akty uznane za uchylone', 'Podstawa prawna', 'Podstawa prawna z art.', 'Teksty jednolite'. None = zwróć wszystkie powiązania.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the returned information (changed acts, etc.), but does not disclose behavioral aspects like read-only nature, authentication needs, or rate limits. Minimal behavioral context beyond what is obvious.

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?

The description is concise and front-loaded with the purpose. Every sentence contributes meaning, and the examples are efficiently presented. 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 the tool's complexity (2 params, 100% schema coverage, output schema exists), the description covers the main aspects. It does not need to explain return values due to the output schema. Minor improvement could be adding guidance on when to use siblings.

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?

Schema coverage is 100% with descriptions for both parameters. The description adds value by explaining the ELI format in detail and providing concrete examples of relationship_type values, which go beyond the schema alone.

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 it analyzes relationships and references between legal acts, using a specific verb ('Przeanalizuj') and resource. It distinguishes from sibling tools like get_act_details or search_legal_acts by focusing on relationships.

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

Usage Guidelines4/5

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

Multiple examples demonstrate usage with different relationship_type values, implicitly guiding when to use each. However, it does not explicitly state when not to use this tool or mention alternatives for other tasks.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/numikel/law-scrapper-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server