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Glama

List Subscriptions

list_subscriptions
Read-onlyIdempotent

List the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
include_inactiveNoInclude cancelled subscriptions in the response (default false).

Schema Changelog

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

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context: it returns specific fields (id, type, params, created_at, last_fired_at, fire_count), scopes to the caller's subscriptions, and defaults to active ones. This goes beyond the annotations without contradiction.

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 two sentences, front-loaded with purpose, then return fields and use cases. There is no wasted wording; every sentence contributes to understanding the tool's purpose, output, and usage.

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?

For a simple list tool with one optional parameter, the description covers what it does, the returned fields (despite no output schema), and when to use it. Annotations provide the safety and idempotency context. No critical information is missing for an agent to invoke it correctly.

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

Parameters3/5

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

The schema covers the sole parameter include_inactive with 100% coverage, so the baseline is 3. The description mentions 'active subscriptions,' which aligns with the parameter's default false, adding slight contextual meaning. However, it does not explicitly describe the parameter behavior beyond the schema.

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 the tool's action and scope: 'List the caller's active subscriptions.' This distinguishes it from sibling tools like subscribe/unsubscribe, which modify subscriptions, and list_flows, which lists flows. The verb 'list' and resource 'subscriptions' are specific and unambiguous.

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 gives explicit use cases: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This tells the agent when to call the tool relative to subscribe and unsubscribe. However, it does not explicitly name alternative tools or say when not to use it, which would push it to a 5.

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

Most tools have distinct purposes (e.g., entity_profile vs compare_entities), but there is some overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as among polymarket tools, which could cause misselection.

Naming Consistency2/5

Tool names are inconsistent, mixing verb_noun (list_flows, get_series) with descriptive names (ask_pipeworx, bet_research) and varying conventions (snake_case vs no underscores).

Tool Count3/5

33 tools is on the high side but manageable for a broad platform; however, the server name 'Norges Bank' suggests a narrower scope, making the count feel bloated.

Completeness2/5

For a server named 'Norges Bank', many tools are irrelevant (polymarket, pipeworx meta-tools, memory, etc.), leaving significant gaps in core Norwegian banking data coverage.