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Metis — Record Thinking Event

record_thinking_event

Log preference signals (e.g., idea ratings, agent output acceptance) to build a thinking profile that tailors Metis' routing, suggestions, and tone to your needs.

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
contextNo
agent_slugNo
content_idNo
event_typeYes
source_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations are provided, so the description fully covers behavior: it records a signal, returns confirmation or error for invalid event_type, and explains the long-term effect. This is transparent and complete.

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 an intro, purpose, usage guidance, parameter list, and return info. Every sentence adds value, making it informative without 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 parameter count (5), one required, and an output schema, the description covers behavior, parameters, return values, and usage. It is complete for a recording tool with clear context and no 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 description coverage is 0%, but the description includes an 'Args' section explaining each parameter, defaults, and constraints. This adds significant value beyond the schema, especially for event_type with its explicit list.

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 a signal about thinking and working to personalize Metis. It lists specific event types and explains how it feeds a thinking profile, distinguishing it from related tools like get_thinking_profile.

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?

The description advises to call it 'whenever a meaningful preference moment occurs' and points to get_thinking_profile for reading the profile. It does not explicitly state when not to use alternatives, but the examples and context provide clear guidance.

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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