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 idempotentHint=true, so the description focuses on additional context like return fields (id, type, params, etc.) and that it lists only active subscriptions by default. This adds value beyond the annotations 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 sentences, front-loaded with purpose, each sentence adds value. No redundant or extra content.
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 simple list tool with one optional parameter and annotations covering safety, the description fully explains what it does, what it returns, and when to use it. No output schema is needed as return fields are listed.
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% for the single parameter 'include_inactive,' which is already described in the schema. The description does not add any parameter-specific information, so it meets the baseline of 3.
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?
Description explicitly states 'List the caller's active subscriptions,' clearly identifying the verb (list) and resource (subscriptions). It distinguishes itself from sibling tools like subscribe and unsubscribe by focusing on reading rather than creating or deleting.
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?
Provides explicit guidance: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This tells the agent when to choose this tool over alternatives, making it highly actionable.
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 clearly distinct purposes, and the long, detailed descriptions make it easy for an agent to pick the right one. However, there is some functional overlap between research-oriented tools (e.g., ask_pipeworx vs deep_research vs bet_research) and between visibility-checking tools (ai_visibility_check vs scan_competitor_ai_presence), which could potentially confuse an agent without careful reading.
Tool names are uniformly lowercase with underscores, and related tools share consistent prefixes (e.g., polymarket_*, ask_pipeworx, check_*). While most follow a verb_noun pattern, some are noun-first (entity_profile, polymarket_arbitrage) or compound (scan_competitor_ai_presence), creating minor inconsistency, but overall the naming is readable and not chaotic.
With 37 tools, the count is on the higher end but appropriate for a broad data/research platform that covers HIBP breaches, multiple data-pull/research modes, Polymarket analytics, memory, subscriptions, and meta-tools. The number is justified by the diversity of capabilities, though it exceeds the typical 3-15 range for a narrowly-scoped server.
The tool set appears thorough for its intended scope: HIBP breach lookup is fully covered (check_account, check_password, get_breach, list_breaches, list_data_classes), research and entity resolution are extensive (entity_profile, compare_entities, deep_research, validate_claim, etc.), Polymarket has dedicated arbitrage/edge/fill-risk tools, and memory/subscription/meta capabilities are present. No obvious gaps for the stated functionality.