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Glama

Unsubscribe from Alerts

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Idempotent

Cancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesSubscription id (uuid) returned by subscribe.

TDQS

A4.5/5.0
Behavior5/5

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

Adds significant behavioral context beyond annotations: ownership enforcement (only own subscriptions), soft deactivation (row not deleted), and linkage to recent_alerts for historical events. Annotations already indicate idempotent and non-destructive; description complements 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?

Two sentences, no redundant words. Action is first word. Every sentence adds value: effect, ownership, and impact on historical data.

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 mutation with one required parameter and no output schema, description covers action, constraints, and side effects. No missing information needed for agent to invoke 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?

Parameter 'id' has clear schema description (uuid from subscribe). Schema coverage is 100%. Description does not add additional semantics beyond referencing 'id', so baseline 3 is appropriate.

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?

Clear verb 'cancel' with specific resource 'subscription by id'. Distinguishes from 'subscribe' (create) and 'list_subscriptions' (list). Ownership enforcement and deactivation-not-deletion are stated, making purpose 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?

Implied usage: cancel your own subscriptions. Ownership enforcement is explicitly stated. Does not explicitly list alternatives or when-not-to-use, but context from sibling tools and description of historical events via recent_alerts provides guidance.

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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Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation3/5

Several tools occupy adjacent roles: ask_pipeworx and ask_pipeworx_beta are currently identical in behavior, discover_tools and suggest_questions both serve discovery, and the astronomy plus Polymarket scanners have overlapping boundaries. The descriptions are unusually detailed and do differentiate most tools, but the number of near-neighbor tools still creates real selection risk.

Naming Consistency3/5

Names are uniformly snake_case and mostly descriptive, which helps, but the grammatical pattern is inconsistent: verb_noun names (compare_entities, resolve_entity) sit alongside bare nouns (catalogs, object) and bare verbs (remember, recall, forget). It is readable but not a predictable verb_noun convention.

Tool Count2/5

At 35 tools, the surface is well beyond what an agent can comfortably hold in mind. The set mixes a data-research core with one-off utilities like generate_llms_txt, scan_dependency, and AI-visibility auditing, making it feel like a grab-bag rather than a scoped server.

Completeness4/5

The core data-research workflow is strongly covered: plain and grounded Q&A, deep research, entity resolution, profiles, comparisons, claim validation, recent changes, tool discovery, memory, and subscription lifecycle all exist. Minor gaps remain, such as no subscription-update operation and no generic citation-fetch tool, but there are no serious dead ends.