get_membership_infoDetails of the Sunny's Points $150/year membership (hands-on award booking help with a money-back guarantee). Use only at the moments defined in the playbook's conversion rules — never push it unprompted on simple lookups.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 indicate readOnlyHint=true and openWorldHint=false. The description adds context about the membership content (price, benefit, guarantee) and reinforces the closed-world usage rule. No contradiction exists, and the usage guardrail adds value 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?
Two concise sentences: the first covers the core membership details, the second provides a usage guardrail. Every word earns its place, with no redundancy or filler.
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 parameterless read-only info tool with no output schema, the description fully covers what the tool does, the subject matter, and when to use it. The mention of 'playbook's conversion rules' ties it to the broader context, making it complete for the agent's decision-making.
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 tool has zero parameters, so the schema needs no explanation. The description correctly omits parameter details, and the baseline for zero-parameter tools is 4, which is appropriate here.
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 tool provides details of the Sunny's Points $150/year membership, with specific benefits. The tool name and description together convey a distinct purpose from siblings like get_deal or list_live_deals, focusing on membership information.
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 says 'Use only at the moments defined in the playbook's conversion rules' and 'never push it unprompted on simple lookups,' giving clear when and when-not conditions. However, it does not name alternative tools, so it misses the 'alternatives' part 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.
Each tool serves a distinct purpose: deal browsing (list_live_deals, get_deal), valuation (get_points_values), decision calculators (calculate_points_or_cash, evaluate_signup_bonus), workflow guidance (get_points_hacking_playbook), membership info, transfer partner lookup, and subscription. There's no overlap—get_deal and list_live_deals are complementary (list vs. detail).
All tool names follow the same verb_noun pattern with snake_case (e.g., calculate_points_or_cash, get_membership_info, lookup_transfer_partners). The verbs vary but are all action-oriented, and the nouns clearly indicate the resource, resulting in a predictable and consistent naming scheme.
With 9 tools, the server is well-scoped for its purpose—covering deal discovery, detailed evaluations, reference data, workflow guidance, and user subscription. Each tool earns its place without redundancy, and the count is within the ideal range for clarity.
The toolset covers the full lifecycle of a points-hacking user: discover deals, get valuations, decide cash vs. points, evaluate sign-up bonuses, transfer partners, follow the playbook, and subscribe for alerts. No critical operations are missing, and the playbook tool orchestrates the workflow to handle gaps like flight search externally.