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Glama

Get Usage Limits

get_usage_limits
Read-only

Get current usage against the plan limits, one entry per category (projects, specs, members, …) with the current count, the maximum and whether the category is unlimited. This is the tool that answers 'why can I not create another one'. Requires organization context. Read-only: plan, seat and top-up changes are not available through MCP by design — a human does those in the web app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The readOnlyHint annotation already signals a non-destructive operation, and the description reinforces this by stating it is read-only and that changes are done by a human in the web app. This adds useful behavioral context beyond the annotation alone.

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?

The description is slightly wordy but well-structured, front-loading the core purpose and then adding output details and usage guidance. Each sentence contributes meaningful information without excessive repetition.

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?

Since there is no output schema, the description adequately describes the response shape: one entry per category with current count, maximum, and whether the category is unlimited. It also explains the common use case and the read-only nature, making the tool self-contained enough for an agent to use correctly.

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?

The input schema has no parameters, so there is little parameter detail to add. The description still provides relevant context by noting that organization context is required, which helps the agent understand the expected invocation environment.

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 identifies the specific action ('get current usage against the plan limits') and distinguishes this tool from related getters like get_credit_balance or get_subscription by focusing on category-level usage counts and limits. The phrasing 'the tool that answers why can I not create another one' makes its purpose immediately understandable.

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 states when to use the tool ('answers why can I not create another one') and notes that it requires organization context. It also clarifies that plan, seat, and top-up changes are not available through MCP, which helps set expectations, though it does not explicitly contrast with alternative tools.

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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TDQS

A3.9/5.0
Disambiguation4/5

The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.

Tool Count1/5

With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.

Completeness5/5

The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.

Resources