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Glama

open_pool

Cluster intents by spec hash. No deposits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intent_idYes
min_quantityYes

Schema Changelog

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

  1. First observed

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, but it only says no deposits are involved. It does not disclose side effects, permissions, failure modes, or what happens to intents after clustering, leaving the agent to guess.

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

Conciseness4/5

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

The description is very short with no filler, and the core purpose is front-loaded. The 'No deposits' fragment is elliptical but earns its place; the main flaw is under-specification rather than wordiness.

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 annotations and no output schema, the description must cover safety and return semantics, but it mentions neither. The minimal purpose statement is a good start yet insufficient for reliable invocation without guessing.

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?

Schema description coverage is 0%, and the description does not explain intent_id or min_quantity. The property names carry some inherent meaning, but the description adds nothing beyond those names.

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

Purpose4/5

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

The description gives a concrete operation—cluster intents by spec hash—and adds a useful constraint, 'No deposits.' It is not a tautology, so an agent can infer the tool's core behavior, though it does not explicitly differentiate from siblings like open_checkout.

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 on when to choose open_pool over its siblings, and no alternatives are named. 'No deposits' hints at a boundary but does not state a selection rule.

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.