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=true and destructiveHint=false. Description adds value by listing returned fields and clarifying default behavior (active subscriptions only). No contradictions.
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 concise sentences, front-loaded with purpose and output, then usage guidance. No waste.
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?
Covers purpose, output fields, and usage. May lack error handling or pagination info, but for a simple list tool it is complete enough.
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% with a clear description for the only parameter. The description does not add much beyond the schema, but the default behavior is implied. Baseline 3 is appropriate.
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', resource 'subscriptions', and scope 'the caller's active subscriptions'. Distinguishes 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?
Explicitly tells when to use: 'to review what you're monitoring before adding more or to find an id to cancel'. No mention of when not to use, but sufficient for this context.
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 five Wiktionary tools are distinct, but the set is dominated by Pipeworx/prediction-market/memory tools with heavy overlap: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ask_pipeworx_grounded/deep_research/discover_tools all cover routed lookup. An agent would struggle to pick between these overlapping research entry points.
Most names use snake_case, but the style is inconsistent: noun-only names (definition, summary, etymology) sit alongside verb_phrase names (validate_claim, scan_dependency, ask_pipeworx) and compound names (recent_changes, polymarket_edges). No consistent verb_noun or resource_action convention is applied across the set.
36 tools is far too many for a Wiktionary server, and only 5 of them (definition, etymology, pronunciations, search, summary) actually serve Wiktionary. The remaining 31 are unrelated utilities (Pipeworx data routing, Polymarket betting, memory, subscriptions), making the count an extreme mismatch with the server's stated purpose.
For basic Wiktionary lookups the surface is usable: search, summary, parsed definitions, etymology, and pronunciations cover the core read path. However there are notable gaps for a dictionary server—no full-entry/wikitext fetch, translations, synonyms, usage examples, or random/word-of-the-day access—and the presence of dozens of unrelated tools does nothing to fill those gaps.