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Glama

show_map

Returns a Markdown data-source map for a chosen sector, covering available sources, macro features, and market share to support ML dataset planning.

Instructions

Bir sektörün veri kaynağı haritasını (kaynaklar, makro feature'lar, pazar payı) markdown olarak döner.

Input Schema

NameRequiredDescriptionDefault
sectorYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden; it does disclose the output format (markdown) and the content composition of the map, which is genuine value. However, it says nothing about whether valid sectors are validated, what happens for an unknown sector, or whether the call has any side effects – gaps that matter with zero annotation coverage.

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?

A single dense sentence with no filler, and the output format and payload are front-loaded. Slightly more structure (e.g. separating what it returns from what it takes) would earn a 5.

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

Completeness3/5

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

An output schema exists, so return-value detail is not required, and the tool is a simple single-parameter read. Still, for an agent to call it correctly it needs the sector value domain and its relationship to list_sectors, neither of which is present.

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

Parameters2/5

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

There is one required parameter with 0% schema description coverage, so the description must compensate. It only implies that 'sector' is the subject via the possessive 'bir sektörün' and gives no format, casing, or valid-value guidance; list_sectors might enumerate valid values but that link is not stated.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description pairs a specific verb ('döner' – returns) with a specific resource ('veri kaynağı haritası') and enumerates the contents: sources, macro features, market share, as markdown. An agent immediately knows what the tool produces. It stops short of naming a sibling it is distinct from, so it is not a 5.

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?

There is no guidance on when to call show_map versus list_sources, build_panel, or discover_series, nor any mention of prerequisites or exclusions. The agent must infer the use case purely from the noun.

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