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, idempotentHint, destructiveHint. Description adds only 'active subscriptions' behavior, which is consistent but not additional 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 sentences with no wasted words; first sentence front-loads purpose and return fields, second provides usage guidance.
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 single optional parameter, no output schema, and comprehensive annotations, the description is complete enough for an AI agent to use the tool effectively.
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 covers 100% of parameters with description for include_inactive. Description does not add extra semantic meaning beyond the 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' with specific verb and resource, lists return fields, and distinguishes from siblings like subscribe/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 case: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' Does not explicitly state when not to use, but context is clear given sibling tools.
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 overlapping purposes, such as the ask_pipeworx family (standard, beta, grounded) and the multiple Polymarket analysis tools (edges, arbitrage, fill_risk, edge_tracker, kalshi_spread, bet_research). The detailed descriptions help differentiate them, but an agent could still misselect between deep_research vs ask_pipeworx or polymarket_edges vs polymarket_arbitrage.
Naming patterns are mixed: many tools use verb_noun (discover_tools, validate_claim, compare_entities), but others are noun_noun (entity_profile, polymarket_edges), single verbs (remember, recall, forget), or unusual forms (extension_for, search_within, ask_pipeworx). The polymarket_ prefix and ask_pipeworx family provide some consistency, but overall the style is not uniform.
33 tools is a large number for the server's scope. While it covers many domains (data querying, entity research, Polymarket analysis, subscriptions, memory, utilities), there is redundancy: three ask_pipeworx variants and six Polymarket-specific tools inflate the count. Several tools could be merged or dropped without losing functionality, making the set feel heavier than necessary.
The toolset covers its core domains well: data querying (ask_pipeworx, deep_research), entity resolution (resolve_entity, entity_profile, compare_entities), Polymarket analysis (research, arbitrage, risk, edges, tracking, cross-venue), subscriptions (subscribe/unsubscribe/list/alerts), memory (remember/recall/forget), and utilities (MIME lookup, dependency scan). Minor gaps exist, such as no direct fetch tool for pipeworx:// citation URIs and no update operation for subscriptions, but these are not critical.