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 indicate safe, idempotent, read-only operation. Description adds default behavior (active only) and lists return fields, which aligns 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: one describing output, one giving usage guidance. No fluff, well-structured.
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?
With no output schema, description lists return fields. Covers default behavior and usage context. Complete 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 has 100% coverage for the single optional parameter (include_inactive). Description does not add extra meaning beyond schema, baseline 3.
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 the verb 'List' and resource 'active subscriptions', and lists returned fields (id, type, params, etc.). 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 says use it to review subscriptions before adding more or to find an id to cancel. Provides context but does not explicitly state when not to use.
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 have heavily overlapping purposes, notably ask_pipeworx vs ask_pipeworx_beta vs ask_pipeworx_grounded, and the cluster of polymarket tools covers adjacent prediction-market analysis territory. The PomBase-specific tools are distinct, but the overall set creates real selection ambiguity.
Most names follow a readable snake_case style and many use verb-first patterns, but there is notable mixing: ask_pipeworx is a brand-style exception, entity_profile and polymarket_arbitrage are noun-first, and remember/recall/forget form an inconsistent trio. Not chaotic, but not a clean predictable convention.
33 tools is excessive for a server named Pombase, where only get_gene and get_reference actually serve that domain. Even as a broad data-research server, the count is above the 25-tool threshold and includes many auxiliary utilities that feel bolted on rather than part of a focused surface.
The PomBase-specific coverage is severely thin: only systematic-ID gene lookup and PubMed-ID reference lookup, with no gene-name search, annotations browsing, phenotype data, or sequence access. The broader Pipeworx surface is extensive, but for the apparent Pombase purpose, agents will frequently hit dead ends.