SingChat

Configure AI agent

configure_agent

Configure this workspace's AI support agent. All fields are optional, only the fields you pass are updated; the rest keep their current values. Call with no fields to just read back the current configuration. Does not touch or return any API keys.

Input Schema

TableJSON Schema

Name	Required	Description
`model`	No	Chat model id, e.g. gpt-4o-mini.
`enabled`	No	Turn the automated AI agent on (true) or off (false).
`providerMode`	No	'platform' = platform-hosted keys (billed via AI credits); 'byok' = bring your own key.
`systemPrompt`	No	The agent's system prompt / persona and answering rules.
`greetingMessage`	No	First message visitors see when they open the chat. Pass an empty string to clear it.

Schema Changelog

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

First observedJul 16, 2026

TDQS

A4.4/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. Discloses partial update behavior, read-back capability, and that API keys are not touched/returned. Provides sufficient behavioral insight for a non-destructive configuration tool.

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?

Three short sentences, front-loaded with core purpose. Every sentence adds essential information without redundancy. Highly efficient.

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?

Given no output schema, the description compensates by explaining the read-back behavior. Covers optional parameters, partial update semantics, and safety (no API keys). Missing details on validation or error handling, but adequate for a simple config tool.

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?

Schema coverage is 100% with parameter descriptions, so baseline is 3. The description adds value beyond schema by stating all fields are optional and explaining the read-back pattern. Adds context on API key handling.

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?

Clearly states 'Configure this workspace's AI support agent', using a specific verb and resource. Differentiates from sibling tools which deal with knowledge, conversations, analytics, etc. No ambiguity.

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?

Explains when to use: update agent settings, with optional fields and the ability to read current config by calling with no fields. Mentions what is NOT done (no API keys). Lacks explicit when-not-to-use or alternatives, but context is clear.

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

A4.1/5.0

Disambiguation4/5

Tools are largely distinct, with clear purposes for knowledge management, conversations, FAQs, and setup. The only potential overlap is between 'search' (general help) and 'search_knowledge' (workspace KB), but descriptions clarify the context.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., add_knowledge, list_conversations, manage_faq). No mixing of conventions or vague verbs.

Tool Count5/5

17 tools is well-scoped for a live-chat and AI agent workspace server. The set covers setup, knowledge base, conversations, FAQs, analytics, keywords, and embedding without being overwhelming.

Completeness4/5

The tool surface is comprehensive for core workspace management and support: setup, knowledge ingestion/search, conversation handling, FAQs, analytics, and keywords. Minor gaps like user management or advanced channel configuration, but nothing that critically hinders agent workflows.

Resources

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