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. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate non-read-only, non-destructive, and idempotent. The description adds context: row is deactivated not deleted, historical events remain via recent_alerts. No contradiction 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, front-loaded with the key verb. No superfluous information; every sentence adds value.
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?
For a single-parameter mutation tool with good annotations, the description covers ownership, deactivation behavior, and relationship to recent_alerts. Complete for the complexity level.
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 parameter description 'Subscription id (uuid) returned by subscribe.' The description itself does not add additional meaning beyond the schema, but the linkage to subscribe is implicit. Baseline score of 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?
The description clearly states the action as 'Cancel a subscription by id,' identifying both the verb and the resource. This distinguishes it from siblings like 'subscribe' and 'list_subscriptions'.
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 ('you can only cancel your own subscriptions'), guiding when to use and when not. Also explains the deactivation behavior, helping the agent understand outcomes.
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: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve route/discover/research data needs, with ask_pipeworx_beta explicitly noted as currently identical to ask_pipeworx. Polymarket tools also blur together (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk), and ai_visibility_check vs scan_competitor_ai_presence are near-duplicates. An agent would frequently need to read long descriptions just to pick between near-equivalent entry points.
The set is mostly snake_case and generally readable, with clear verbs like list_subscriptions, resolve_entity, generate_llms_txt, and validate_claim. However, conventions are mixed: brand-prefixed nouns appear (pipeworx_feedback, pipeworx_trending), one tool reverses the pattern (conspiracy_theory_generate vs generate_llms_txt), and the ask_pipeworx family follows its own scheme. The inconsistency is noticeable but does not make the names unreadable.
32 tools is heavy, and the apparent scope is a scattered mix of general data research, prediction markets, memory, subscriptions, AI visibility, npm dependency checks, and conspiracy-theory generation. Many tools are meta-routers or aggregators that could be consolidated (e.g., the ask_pipeworx family, the polymarket family, the entity-research tools). The count feels like a growing internal toolkit rather than a deliberately scoped server.
The tools cover some complete sub-domains — memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and data lookup has multiple verification and research paths. But the server's nominal 'Conspiracy Theory' purpose is essentially one generation tool with no save, share, history, or validation workflow, while the bulk of the surface is unrelated general-purpose data tooling. The overall offering is broad but not coherently complete for any clear stated purpose.