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build_list_capabilities

Read-only

List the platform's available services/integrations from the LIVE catalog (email, sms, slack, ai, stripe_checkout, google_oauth, push_notification, …) — so the intake's 'which connections/integrations?' question is accurate and you never guess a service id. Returns each service's exact catalog service_id (use it verbatim in config.py services — e.g. 'stripe_checkout', NOT 'stripe'), category, whether it needs a key, and YOUR connection's service permissions (can_import / can_configure). Descriptive — what EXISTS, never what to use. Pass service_id for one service's config fields.

Input Schema

NameRequiredDescriptionDefault
categoryNoOptional filter ('integration' or 'service').
service_idNoOptional: one service's detail incl. config fields.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=false; the description adds that the catalog is LIVE (freshness) and that results include per-connection permissions (can_import / can_configure), which the agent could not infer from annotations. It says nothing about auth requirements or failure modes.

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?

Verb and scope are front-loaded, and each sentence carries information (examples, id-verbatim warning, descriptive-only note). The heavy parentheticals and em-dash asides make it denser than necessary.

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?

With no output schema, the description does the work of describing return fields (service_id, category, key requirement, connection permissions), which is what an agent needs. Only minor gaps remain around call cost or result size.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds that passing service_id returns that one service's config fields, but that largely restates the schema text; the category filter is not elaborated at all.

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?

Specific verb + resource: 'List the platform's available services/integrations from the LIVE catalog', with enumerated examples. It is clearly distinguishable from siblings like build_recommend_integrations (which advises what to use) and build_get_service_contract (which returns contract detail).

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?

States the triggering context — answering the intake's 'which connections/integrations?' question — and the exclusion 'Descriptive — what EXISTS, never what to use', which implicitly routes recommendation questions elsewhere. It never names the alternative sibling explicitly, so it stops short of a 5.

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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