list_subscriptionsList 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.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and other traits. Description adds value by listing return fields and clarifying the default behavior (active only) and the effect of the include_inactive parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no unnecessary words, front-loaded with purpose and return fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description lists return fields. Covers purpose, usage, and parameter behavior adequately for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description does not need to add parameter details. The description implies default behavior (active) but no additional semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List the caller's active subscriptions', specifies return fields (id, type, etc.), and distinguishes from siblings like 'subscribe' and 'unsubscribe'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises to use this tool before adding more subscriptions or to find an id to cancel, providing clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The server mixes three near-identical ask_pipeworx variants (stable, beta, grounded) where beta is currently described as functionally identical to stable, plus several overlapping discovery and research tools (discover_tools, suggest_questions, deep_research, validate_claim, ask_pipeworx). Multiple entity/comparison/change tools (entity_profile, compare_entities, recent_changes) and several Polymarket tools further blur boundaries, requiring careful reading of long descriptions to pick correctly.
Many tools follow a clear verb_noun snake_case pattern (list_dataflows, get_data, compare_entities, validate_claim, resolve_entity), and the polymarket_* prefix groups the prediction-market family consistently. However, naming is mixed: bare verbs (remember, forget, recall), noun phrases (dataflow_structure, entity_profile), brand-prefixed tools (pipeworx_feedback, pipeworx_trending), and inconsistent verb choices like ask_pipeworx vs ask_pipeworx_grounded vs suggest_questions.
34 tools is heavy for a server named Ilostat, especially since only three tools (list_dataflows, dataflow_structure, get_data) actually serve ILOSTAT data. The rest form a broad general-purpose data/prediction-market platform that appears bolted on rather than scoped to the server's stated identity.
For the ILOSTAT domain specifically, the read-only lifecycle is complete: list_dataflows discovers datasets, dataflow_structure explains dimensions/codes, and get_data retrieves observations — no obvious dead ends for public data access. Other embedded subsystems (memory, subscriptions) also have full CRUD, though the overall server lacks a coherent single-domain surface to judge against.