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). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate it's read-only, idempotent, and non-destructive. The description adds that it returns specific fields and is scoped to the caller's subscriptions, which are useful behavioral traits beyond the 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?
The description is two sentences, front-loads the core action, and contains no extraneous information. Every sentence serves a purpose.
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 the tool's simplicity (one optional parameter, no output schema), the description is reasonably complete. It lists the return fields and provides usage context, though it could mention that subscriptions are scoped by default to active ones.
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?
The input schema has 100% description coverage for its single parameter (include_inactive). The description does not add extra meaning beyond the schema's parameter description, so the 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 identifies the tool as listing the caller's active subscriptions, specifying the returned fields. It distinguishes itself from sibling tools like subscribe and unsubscribe by indicating it's a read-only review operation.
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?
The description explicitly states when to use the tool: 'to review what you're monitoring before adding more or to find an id to cancel.' This provides clear context, though it doesn't explicitly state when not to use it.
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 legislation-specific tools are distinct, but the server bundles dozens of unrelated Pipeworx/prediction-market/AI-visibility tools, making the set's purpose unclear. Several near-identical pairs exist: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ai_visibility_check overlaps heavily with scan_competitor_ai_presence. An agent would struggle to know which tool is the right entry point.
Naming is mixed: snake_case dominates, but camelCase appears in ask_pipeworx, ask_pipeworx_grounded, generate_llms_txt, and pipeworx_feedback. There is also inconsistency in verb style — get_/search_/list_ coexist with bare verbs like remember, recall, forget, and subscribe. The legislation tools themselves follow a clean get_legislation* pattern, but the wider set does not.
35 tools is too many for a server named 'Legislation Uk' where only 4 tools actually relate to UK legislation. The remaining 31 tools appear to belong to a broader data/prediction-market platform, which suggests severe scope creep or a mislabeled assembly. This bloats the surface area and makes the server harder for an agent to navigate.
For the stated UK-legislation purpose, the core read-and-search workflow is covered: search_legislation, get_legislation, get_legislation_section, and get_legislation_text together support discovery, metadata, targeted section lookup, and full-text retrieval with version selection. Obvious gaps remain, such as full-text content search and amendment/change history, but agents can complete the primary task of finding and reading legislation. The unrelated tools neither help nor complete this domain.