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thinking_trajectory

Track how an idea evolves over time: discover its first appearance, frequency patterns, and stages of development in your conversation history.

Instructions

    Track the evolution of thinking about a topic over time.

    Args:
        topic: The concept/term to track
        view: What to show:
            - "full" (default): Complete trajectory with genesis, temporal pattern, semantic matches, thinking stages
            - "velocity": How often the concept appears over time with trend analysis
            - "first": When the concept first appeared — the genesis moment
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewNofull
topicYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It correctly implies a read-only tracking operation, but does not explicitly state it is non-destructive or mention any other behaviors like permissions or pacing. The existence of an output schema partially compensates for missing return value details.

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?

The description is concise and front-loaded with the main purpose. The structured 'Args' section with bullet points is clear, though some repetition could be trimmed (e.g., explaining each view option once instead of partly in the main text and again in args).

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 the tool has only two parameters and an existing output schema, the description provides adequate context for inferring usage. It covers the main purpose and parameter semantics. Minor gaps exist in behavioral and alternative tool guidance, but overall it is complete enough for an agent.

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?

The description adds significant meaning beyond the input schema: it explains the purpose of 'topic' and provides detailed options for 'view' with their meanings. This compensates well 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 what the tool does with a specific verb ('Track') and resource ('evolution of thinking about a topic over time'). This distinguishes it from siblings like 'cognitive_patterns' or 'what_was_i_thinking', which focus on different aspects of thinking.

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 provides clear context for the 'view' parameter, explaining what each option ('full', 'velocity', 'first') shows. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or when-not-to-use 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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