Skip to main content
Glama

chat_configure

Configure a notebook's chat behavior via preset modes or custom goal and response length. Presets replace settings; partial custom calls merge with existing configuration.

Instructions

Configure a notebook's chat behavior. Accepts a notebook name or ID.

Two mutually-exclusive ways to configure:

  • chat_mode is a preset — one of default / learning-guide / concise / detailed. It replaces the whole block, so it can't be combined with goal / response_length (that's rejected).

  • goal (custom persona; selects the CUSTOM goal) and response_length (default / longer / shorter) set a custom config. A partial call (just one) merges with the current settings — the omitted field is preserved. Only a bare call (no preset, neither field) is rejected, as it would reset every setting to its default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNo
notebookYes
chat_modeNo
response_lengthNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full disclosure burden. It explains that chat_mode replaces the whole block, custom fields merge with existing settings, and a bare call is rejected. It stops short of discussing persistence or permissions, but the key behavioral traits are well covered.

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?

The description is well-structured with a clear opening sentence and bullet-style explanation of configuration modes. Every sentence contributes to understanding behavior, with no filler or redundancy.

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

Completeness5/5

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

Given the output schema exists, the description needn't document return values. It covers all parameters, required field, edge cases, and interaction rules, making it complete for a configuration tool.

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

Parameters5/5

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

The description adds substantial meaning to all four parameters beyond the schema, mapping notebook to name/ID, enumerating chat_mode and response_length values, and explaining goal's role as a custom persona. It clarifies interaction semantics (mutual exclusion, merging, rejection), which the schema alone does not convey. This fully compensates for the 0% schema description coverage.

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 clearly states the tool configures a notebook's chat behavior, using a specific verb and resource. It distinguishes itself from sibling chat_ask by focusing on configuration rather than querying. The two configuration modes add specificity.

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?

It provides detailed usage guidance through two mutually exclusive configuration paths, including what combinations are rejected and how partial calls merge. It implies when to use it (when needing to set chat behavior) though it doesn't explicitly name alternative tools. This is clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Solar2004/nblm-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server