Skip to main content
Glama

record_thinking_event

Record signals about your thinking and work habits to personalize Metis. Each event helps tailor routing, suggestions, and tone to your preferences.

Instructions

Record one signal about how you think and work, to personalise Metis.

Each event is a small piece of evidence — you acted on a brainstorm, rated
an idea highly, flagged an agent's output — that feeds your evolving
"thinking profile". Over time these signals let Metis tailor its routing,
suggestions, and tone to your preferences. Call it whenever a meaningful
preference moment occurs; read the accumulated profile with
get_thinking_profile.

Args:
    event_type: The kind of signal. Must be one of: "brainstorm_acted_on",
        "brainstorm_ignored", "idea_rated_high", "idea_linked_project",
        "journal_revisited", "agent_output_accepted", "agent_output_flagged".
    source_type: Domain or category the signal belongs to (e.g. "biology").
        Optional; defaults to empty.
    content_id: ID of the related content record (idea, journal entry, etc.)
        if applicable. Optional; defaults to 0 (none).
    agent_slug: Agent identifier this signal relates to, used for the
        "agent_output_*" event types. Optional.
    context: Free-text note giving context for the event. Optional.

Returns:
    A confirmation that the signal was recorded, or an error listing the
    valid event types if an invalid one was supplied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_typeYes
source_typeNo
content_idNo
agent_slugNo
contextNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that it's a write operation, returns confirmation or error with valid event types, and that it personalizes Metis. Lacks detail on data persistence or mutability, but sufficient for a simple recording tool.

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?

Description is well-structured with a summary paragraph and explicit Args section. It is front-loaded with the purpose, though the Args section is somewhat verbose; however, every sentence adds necessary information.

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?

For a tool with 5 parameters (1 required) and an output schema, the description covers purpose, parameters, return values, and references a sibling tool. It is complete and leaves no significant gaps.

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?

Schema has 0% description coverage, but the description provides detailed explanations for all 5 parameters, including allowed values for event_type, defaults, and purpose. Fully compensates for missing schema descriptions.

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 records signals about thinking and working to personalize Metis, with specific examples. It explicitly references the sibling tool get_thinking_profile for reading, distinguishing the write operation.

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?

Provides explicit guidance: 'Call it whenever a meaningful preference moment occurs.' Mentions reading with get_thinking_profile but does not mention update_thinking_profile or other operations, though the core usage is clear.

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/SVerITG/Metis'

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