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 destructiveHint=false, covering the safety profile. The description adds useful behavioral context such as scope ('caller's subscriptions') and return fields ('id, type, params, created_at, last_fired_at, fire_count'), which goes beyond the annotation-only view. However, it doesn't explicitly mention the include_inactive filter behavior.
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, with the first stating the function and return fields, and the second giving usage guidance. Every sentence earns its place, with no superfluous words.
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 simple read-only list tool with rich annotations and full schema coverage, the description is complete. It states purpose, return values, and when to use it, requiring no additional information for an agent to invoke it correctly.
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 schema already fully documents the only parameter (include_inactive) with its description and default. Schema coverage is 100%, so the description doesn't need to add parameter details; it adds no parameter-specific meaning but the baseline of 3 applies.
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: 'List the caller's active subscriptions.' It also specifies the returned fields, making it distinct from sibling tools like subscribe and unsubscribe.
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 provides explicit usage context: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This tells the agent when to use the tool and for what purpose, effectively differentiating it from subscription-modifying tools.
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 five BambooHR tools are distinct, but the set is dominated by overlapping Pipeworx/Polymarket search and research tools: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve similar lookup purposes, and polymarket_edges/polymarket_edge_tracker/polymarket_arbitrage/polymarket_fill_risk/polymarket_kalshi_spread occupy closely related prediction-market territory. Descriptions help differentiate them, but an agent could easily select the wrong one.
Naming conventions are heavily mixed: camelCase (ai_visibility_check, ask_pipeworx_grounded), snake_case with varying verb positions (bamboohr_get_directory, list_subscriptions, resolve_entity), and domain-prefixed families that do not share a consistent pattern. Some tools are named by action (bet_research, compare_entities) rather than resource-object style, and the Pipeworx meta-tools follow a different convention than the BambooHR tools.
36 tools is excessive for a server ostensibly named Bamboohr, and the vast majority are unrelated to HR—they cover general data research, prediction markets, AI visibility, and memory storage. The BambooHR-specific surface is only 5 tools buried inside a much larger third-party platform, making the count disproportionate to the stated server purpose.
The BambooHR domain is severely under-covered: read operations exist for directory, employees, employee files, and time off, but there are no create/update/delete operations, no time-off request management, no org chart access, no payroll or benefits tools, and no employee lifecycle workflows. Meanwhile, the many non-HR tools are extensive for their own domains but do not fill the obvious HR gaps.