unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
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?
Discloses ownership enforcement, deactivation (not deletion), and effect on historical events. Aligns with annotations (non-destructive, idempotent) without contradiction.
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, no waste. Purpose front-loaded, additional behavior stated efficiently.
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 one parameter, full schema coverage, and clear annotations, the description covers purpose, behavior, ownership, and impact on history. No gaps.
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 fully describes the 'id' parameter. Description adds context about ownership enforcement, linking parameter to the user's own subscriptions, adding value beyond 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?
Clearly states the action ('Cancel a subscription') and resource (by id). Distinguishes from siblings like 'subscribe' and 'list_subscriptions' by specifying deactivation vs deletion.
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 notes ownership enforcement ('can only cancel your own subscriptions') and the deactivation behavior. Could mention when not to use, but context is clear from sibling names.
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.
Many tools overlap in general purpose—ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all retrieve factual data—though their descriptions draw clear mode distinctions. The Polymarket family is similarly dense but each member has a distinct role. An agent must read carefully to pick the right one, but the boundaries are mostly decipherable.
Tool names overwhelmingly follow snake_case verb_noun or domain_noun patterns (search_publications, resolve_entity, polymarket_edges, ask_pipeworx). Minor exceptions like the bare verbs recall and forget break the pattern slightly, and mixed prefixes (pipeworx_, ask_, search_) are still predictable.
At 34 tools, the set is heavy, but the deeper problem is scope mismatch: the server is named Dblp yet only 3 of 34 tools (search_authors, search_publications, search_venues) relate to DBLP. The remaining 31 tools form a broad general-purpose data platform that dwarfs and obscures the apparent purpose.
For a DBLP server, the surface is minimal: only search operations exist, with no record fetch-by-id, citation metrics, or author profile detail beyond what search returns. The bulk of the toolset addresses unrelated domains, leaving the actual DBLP workflow thin and incomplete.