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Glama

Deal Details

get_deal
Read-only

Full detail for one posted deal by slug: booking airline, dates, booking steps, caveats, transfer options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and openWorldHint, so the description need not restate safety. It adds behavioral context by listing the exact types of information returned (airline, dates, steps, caveats, transfer options), giving the agent a clear expectation of the response content.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One concise sentence, front-loaded with the main purpose ('full detail') followed by a compact list of content areas. No redundancy or filler words; every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple lookup tool with a single parameter, the description outlines both the input (slug) and the output categories, enabling the agent to anticipate the result structure. Annotations cover safety and world assumptions. Missing an explicit mention of not-found behavior is a minor gap, but overall the description is complete enough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by stating that the slug identifies a specific posted deal. For a single required string parameter, this is adequate semantics, though it could be improved by noting where the slug comes from (e.g., from list_live_deals).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'get' and resource 'deal', clearly scoped to a single posted deal identified by slug. It distinguishes from sibling list_live_deals by emphasizing singular detail and enumerating the content (booking airline, dates, steps, caveats, transfer options).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use this tool: when you need full details for a specific deal identified by a slug. It does not explicitly compare to alternatives or state exclusions, but the context of a single deal versus listing is sufficient for basic usage differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.5/5.0
Disambiguation5/5

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).

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness5/5

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.

Resources