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?
The annotations already indicate non-read-only and idempotent, but the description adds critical behavioral details: ownership enforcement and soft-delete semantics (deactivated, not deleted, history preserved). This goes well beyond what annotations provide.
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?
Three sentences, each adds substantive information (operation, ownership, deactivation behavior). No redundant content; well front-loaded with the core action.
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 with no output schema, the description adequately explains the effect, side conditions, and historical data access, making it complete for selection and invocation.
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 of 'id' (uuid returned by subscribe). The description only reiterates 'by id' without adding new parameter-specific meaning, so the schema carries the burden.
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 uses a specific verb 'Cancel' with the resource 'subscription by id', clearly distinguishing it from siblings like 'subscribe' and 'list_subscriptions'. It also adds scoping details (ownership enforced, deactivation vs deletion) that further differentiate the tool.
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?
It provides clear context: ownership is enforced, and deactivation preserves historical events via 'recent_alerts'. However, it doesn't explicitly contrast with alternatives or state when not to use it, so it falls short of a 5.
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.
Most tools have clear, distinct purposes, but the three ask_pipeworx variants (especially ask_pipeworx_beta, identical to ask_pipeworx) and the six Polymarket tools overlap conceptually and could cause misselection. Detailed descriptions largely compensate, but the boundaries between some meta-tools (e.g., ask_pipeworx vs deep_research vs bet_research) require careful reading.
All names are snake_case, but conventions are mixed: verb-first (ask_pipeworx, compare_entities, discover_tools), noun-first compounds (entity_profile, polymarket_arbitrage), and single-word nouns (event, events, rss). The pattern is predictable for common actions but inconsistent across the set, making it harder to guess names for related tasks.
At 35 tools, the count is heavy and the server named 'Gdacs' includes many unrelated tools (Polymarket, npm scanning, AI visibility), indicating scope creep. Several tools could be consolidated (e.g., the ask_pipeworx family and multiple pattern-market scanners), and the breadth dilutes the disaster-alerting focus implied by the server name.
The surface covers core workflows: data querying (ask/research/validate), entity profiling, prediction-market analysis (arbitrage/edges/fill risk), and subscription management (create/list/cancel). Minor gaps exist, such as no direct fetch tool for a specific Pipeworx pack and limited GDACS event management (only read operations), but these are workable with the provided meta-tools.