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saidsurucu

Mevzuat MCP

by saidsurucu

search_within_cbbaskankarar

Search Turkish Presidential Decisions using keyword Boolean operators or semantic queries to find relevant content from PDF-based documents.

Instructions

Search within a specific Presidential Decision's (CB Kararı) content using keyword or semantic search.

Presidential Decisions are PDF-based and use chunk-based splitting (no article structure).

Modes:

  • semantic=False (default): Keyword search with Boolean operators (AND/OR/NOT, uppercase required)

  • semantic=True: Natural language semantic search using AI embeddings (requires OPENROUTER_API_KEY)

Keyword examples: "atama AND görev", '"ihracat rejimi"', "vergi OR gümrük" Semantic examples: "kamu personeli atama kararları", "ihracat rejimi düzenlemeleri"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mevzuat_noYesThe Presidential Decision number to search within (e.g., '1733', '10452')
keywordYesSearch query. For keyword mode: supports AND/OR/NOT operators (uppercase). For semantic mode: use natural language.
mevzuat_tertipNoDecision series from search results (e.g., '5')5
case_sensitiveNoWhether to match case when searching (default: False). Only used in keyword mode.
max_resultsNoMaximum number of matching segments to return (1-50, default: 25)
semanticNoTrue: semantic search (natural language query, requires OPENROUTER_API_KEY). False: keyword search (Boolean operators AND/OR/NOT).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. It mentions chunk-based splitting (no article structure), Boolean operator requirements, and provides examples. Missing details on pagination or error handling, but sufficient for behavioral understanding.

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?

Well-structured with sections for modes and examples. Every sentence adds value, no fluff.

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 an output schema exists, description needn't explain return values. It covers search behavior, modes, and query syntax. Could mention result ordering or limitations like max results cap, but overall sufficient.

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% (baseline 3). The description adds value by explaining semantic mode, Boolean operators, and providing example queries for both modes, going 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 searches within a specific Presidential Decision's content using keyword or semantic search, distinguishing it from siblings like search_cbbaskankarar (cross-decision) and get_cbbaskankarar_content (retrieval).

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?

The description explains the two modes (keyword vs semantic) with examples and notes when to use each, including the requirement for OPENROUTER_API_KEY in semantic mode. However, it does not explicitly state when not to use this tool vs alternatives for cross-decision search.

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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