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list_offers

List every live product on the ANAMIZED desk (subscriptions, cycles, consulting, support).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOptional filter by product kind.

Schema Changelog

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

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full disclosure burden. It does reveal a behavioral trait by limiting results to 'live' products, but it omits pagination behavior, result limits, ordering, and authentication requirements, leaving gaps for a list operation.

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?

A single front-loaded sentence with no filler. Every word contributes to the tool's purpose, and the parenthetical adds useful category context despite the minor 'cycles' terminology issue.

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

Completeness3/5

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

For a tool with one optional parameter and no output schema, the description covers the core scope, but it omits return format and pagination details. The 'cycles' versus 'metered' mismatch also leaves a definitional gap, making the description adequate but not complete enough for a higher rating.

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

Parameters2/5

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

The input schema already fully documents the optional 'kind' parameter with an enum, so the baseline is 3. However, the description lists 'cycles' while the schema enum uses 'metered', an inconsistent term that could lead an agent to pass an invalid filter value, reducing the value the description adds.

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 a specific verb ('List') and a clear resource ('every live product on the ANAMIZED desk'), and the 'every' qualifier distinguishes it from the sibling get_offer, which presumably retrieves a single offer. The parenthetical enumerating categories further clarifies the scope.

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

Usage Guidelines3/5

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

The intended use is implied—list all live products—but there is no explicit guidance about when to use this tool versus alternatives like get_offer or checkout_link, and no when-not-to-use conditions are given.

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

C2.9/5.0
Disambiguation2/5

Several tools cluster around the same action: checkout_link and get_offer both return Stripe checkout URLs, list_offers/list_rack/list_systems/search_catalog overlap as catalog listings, and run_rack/constellation_run/swarm_run all trigger credit-spending cycles. The floor_* family is clear, but too many near-duplicate listing and run endpoints create real misselection risk.

Naming Consistency3/5

Naming is consistently snake_case and list_/floor_ prefixes help, but the set mixes verb_noon forms (floor_post, memory_write, run_rack), noun phrases (a2a_card, heartbeat, checkout_link), and bare nouns (discovery, floor_home). Still readable overall, but there is no single predictable naming pattern.

Tool Count2/5

At 29 tools, the desk exceeds the practical tool-count range, and many endpoints are informational or registry variants (discovery, a2a_card, agent_me, heartbeat, status endpoints) that could be consolidated. Even though the platform is broad, the set would be more coherent around 15-20 tools.

Completeness3/5

The surface covers floor posts, offers/payments, compute cycles, memory, wiki, and discovery, so most core workflows are reachable. However, there are noticeable gaps: no delete/edit for floor posts, no memory delete, no agent claim/unregister after register_agent, and no product lifecycle tools. Agents can work around some gaps, but the domain is not fully closed.