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 declare readOnlyHint and non-destructive nature. Description adds return field details and default behavior (active subscriptions), adding value beyond 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 efficient sentences: first states purpose and output, second provides usage guidance. No unnecessary words.
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?
Fully specifies return fields, explains input parameter, and usage context. No output schema needed as description covers it.
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 has 100% coverage with clear description for the one parameter. Description reinforces default behavior ('active subscriptions') but does not add significant new semantics.
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?
Clearly states it lists subscriptions with specific fields returned, distinguishing from sibling tools 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?
Provides explicit use cases: review before adding more, find id to cancel. Contextualizes when to use the tool.
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.
Several tools intentionally overlap: ask_pipeworx_beta is explicitly identical to ask_pipeworx, and ask_pipeworx/ask_pipeworx_grounded/deep_research plus discover_tools/suggest_questions sit close together. The long descriptions clarify differences, but an agent still has to choose between near-equivalent entry points.
All names are readable snake_case, but there is no single consistent convention: verb-led names like list_tags and resolve_entity sit alongside noun-led names like random_cat, entity_profile, and polymarket_arbitrage. Domain prefixes like polymarket_ and pipeworx_ help, but the mixed grammar makes the surface less predictable.
34 tools is far beyond what a cat-image server needs; only 3 tools relate to Cataas, while the rest form a sprawling Pipeworx data, prediction-market, memory, and subscription suite. The count is in the 'too many' range and most tools are outside the server's apparent stated domain.
The cat-image core covers random cats, tag-filtered cats, and tag listing, but omits other Cataas-style operations like fetching by cat ID or creating cat images with text/effects. The embedded Pipeworx side is broad, but it does not fill the gaps in the server's named cat API purpose.