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). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only, idempotent, and non-destructive. The description adds value by disclosing the response shape (id, type, params, created_at, last_fired_at, fire_count) and scoping to the caller's own subscriptions. No contradictions with annotations.
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, front-loaded with the core action, then return fields, then explicit usage guidance. Every clause serves a purpose and there is zero redundancy.
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?
For a simple list operation with one optional parameter and no output schema, the description fully compensates by naming all return fields. It also connects to sibling actions, making the overall context complete.
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?
The sole parameter (include_inactive) has a full description in the schema, reaching 100% schema_description_coverage. The description adds no extra parameter semantics, but the baseline of 3 applies because the schema carries the burden adequately.
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?
The description uses a specific verb 'List' with a clear resource ('the caller's active subscriptions') and enumerates the exact return fields. It distinguishes itself from sibling tools like 'subscribe' and 'unsubscribe' by explicitly framing its role as reviewing active subscriptions.
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?
The description explicitly states when to use this tool: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This provides clear context for both pre-subscription review and pre-unsubscription lookups, effectively ruling out misuse.
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.
Most tools have distinct purposes, with clear descriptions differentiating similar ones like ask_pipeworx and ask_pipeworx_grounded. A few overlaps exist (multiple Polymarket analysis tools), but descriptions sufficiently resolve ambiguity.
Tool naming is inconsistent, mixing descriptive phrases (entity_profile, polymarket_edges) with verb-object patterns (generate_llms_txt, search). No strong convention is followed, and the 'polymarket_' prefix is applied to some betting tools but not others.
32 tools is high but not extreme. However, the scope is too broad for a single server, covering data queries, betting, memory, NYPL, and more, making the set feel bloated and unfocused.
The domain is unclear due to mixed tools, but within the NYPL subset there are clear gaps (only search and item, no CRUD). For the other domains, coverage is uneven and lacks clear lifecycle completeness.