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search_supply

Free supply scan. Every query is written to the demand tape. Misses become implicit intents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
ship_to_countryYes

Schema Changelog

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

  1. First observed

TDQS

C2.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It notably discloses a non-obvious side effect: every query is written to a 'demand tape' and misses become 'implicit intents.' This is valuable because the name suggests a read-only search, but the description warns of persistent side effects. However, it omits other behavioral details such as auth needs, rate limits, or return payload.

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

Conciseness3/5

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

The description is short and front-loaded, but the first sentence is a slogan ('Free supply scan') rather than a specification, and the second uses unexplained jargon ('demand tape', 'implicit intents'). It is concise but sacrifices clarity.

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

Completeness2/5

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

With no output schema, no annotations, and three undocumented parameters, the description leaves major gaps: return format, parameter semantics, error behavior, and operational constraints. It does mention the crucial side effect, which prevents a score of 1, but it is far from complete for safe and correct invocation.

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

Parameters1/5

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

The input schema has 0% description coverage, and the description adds no meaning for 'query', 'ship_to_country', or 'limit'. An agent is left to guess that 'query' is free text, 'ship_to_country' is a destination, and 'limit' caps results — none of this is stated.

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

Purpose3/5

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

The description identifies the resource ('supply') and a generic action ('scan'), but this mostly restates the tool name. It never explicitly states what the scan returns or what problem it solves, and it lacks enough specificity to distinguish search_supply from siblings like list_demand or post_offer.

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

Usage Guidelines2/5

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

No guidance is given for when to use this tool versus its siblings. There is no decision rule, no mention of alternatives, and no prerequisites. The agent must infer the appropriate context from the tool name alone.

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

B3.3/5.0
Disambiguation3/5

Most tools target distinct workflow stages, but get_quote and search_supply both scan supply and write to the demand tape, and list_demand and open_pool both center on demand clusters. post_intent could also be confused with search_supply's implicit-intent side effect. Descriptions help, but some misselection risk remains.

Naming Consistency5/5

All tool names follow a consistent lowercase verb_noun pattern: post_intent, post_offer, get_quote, list_demand, open_checkout, search_supply. Repeated verbs like post and open are paired with different clear objects, keeping the pattern predictable.

Tool Count5/5

Eight tools is well-scoped for a pre-transaction demand/supply matching and checkout server. Each tool covers a meaningful stage without unnecessary duplication. The count feels intentional and complete for the stated domain.

Completeness4/5

The server covers the core pre-transaction lifecycle: recording intents and offers, covering intents, quoting, supply scanning, demand visibility, and checkout URL generation. There are no explicit update/delete/cancel operations, but the descriptions repeatedly scope out deposits, orders, and payment, so those omissions appear deliberate.