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Glama

get_project_details

Retrieve details of an Ali Can Efe project using its ID. Use when you need answers about a specific project, initiative, or repository.

Instructions

Get detailed information about a specific Ali Can Efe project by its ID. Valid IDs include: 'ai-mri-strategy-methodology', 'clv-ib-segmentation-methodology', 'Ali-Can-Efe-Expert-MCP', 'financial-ai-cnn'. Use when the user asks about a specific Ali Can Efe project, professional initiative, or repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesProject identifier (e.g. 'financial-ai-cnn')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully enumerates valid IDs (a constraint absent from the schema) but says nothing about behavior for invalid IDs, error handling, or what 'detailed information' actually contains.

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?

Two sentences, front-loaded with the purpose and followed by usage context; nothing is wasted. The ID enumeration is slightly list-heavy but is the most actionable content in the description.

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?

For a single-parameter read tool with no output schema, the description supplies enough to select and call it: the lookup key, valid values, and the user intent that triggers it. A brief note on what the detail response includes would make it complete.

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%, so baseline is 3, but the description goes further by enumerating concrete valid project_id values ('ai-mri-strategy-methodology', 'financial-ai-cnn', etc.) that the schema only illustrates with one example. This adds real selection guidance beyond the schema.

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?

States a specific verb and resource ('Get detailed information about a specific ... project by its ID'), so the operation is unambiguous. It does not explicitly distinguish itself from the sibling get_projects, which an agent would have to infer.

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?

Gives a clear trigger condition: 'Use when the user asks about a specific Ali Can Efe project, professional initiative, or repository.' It does not state when NOT to use it or route to get_projects for non-specific queries, so the routing boundary with siblings is left implicit.

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