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estimate_uncertainty

Read-only

Calculate Bayesian uncertainty for tags using historical feedback data to assess reliability and confidence levels in memory retrieval systems.

Instructions

Estimate Bayesian uncertainty for a set of tags based on past feedback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoTags to analyze for uncertainty

Implementation Reference

  • The handler function that executes the estimate_uncertainty tool logic.
    function buildEstimateUncertaintyResponse(args = {}) {
      const tags = Array.isArray(args.tags) ? args.tags.map(String) : [];
      const { MEMORY_LOG_PATH } = getFeedbackPaths();
      const memories = readJSONL(MEMORY_LOG_PATH);
      const matching = memories.filter((entry) => {
        if (!tags.length) return Boolean(entry && entry.bayesian);
        const entryTags = Array.isArray(entry && entry.tags) ? entry.tags : [];
        return entry && entry.bayesian && entryTags.some((tag) => tags.includes(tag));
      });
    
      const uncertainties = matching
        .map((entry) => Number(entry.bayesian && entry.bayesian.uncertainty))
        .filter((value) => Number.isFinite(value));
      const averageUncertainty = uncertainties.length > 0
        ? Number((uncertainties.reduce((sum, value) => sum + value, 0) / uncertainties.length).toFixed(4))
        : 0;
    
      return toTextResult({
        tags,
        matches: matching.length,
        averageUncertainty,
        minUncertainty: uncertainties.length > 0 ? Math.min(...uncertainties) : 0,
        maxUncertainty: uncertainties.length > 0 ? Math.max(...uncertainties) : 0,
      });
    }
  • Registration of the estimate_uncertainty tool in the registry.
    readOnlyTool({
      name: 'estimate_uncertainty',
      description: 'Estimate Bayesian uncertainty for a set of tags based on past feedback.',
      inputSchema: {
        type: 'object',
        properties: {
          tags: { type: 'array', items: { type: 'string' }, description: 'Tags to analyze for uncertainty' },
        },
      },
Behavior3/5

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds context by specifying that uncertainty estimation is 'based on past feedback', which implies reliance on historical data, but it does not disclose additional behavioral traits such as computational intensity, data sources, or output format. No contradiction with annotations exists.

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 a single, efficient sentence that directly states the tool's purpose without any redundant or unnecessary information. It is front-loaded and appropriately sized for its content, making it easy to parse.

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

Completeness3/5

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

Given the tool's complexity (Bayesian uncertainty estimation), the description is minimal but covers the core purpose. With annotations indicating a read-only operation and no output schema, the description does not explain return values or error conditions, which could be important for an agent. It is adequate but lacks depth for full contextual understanding.

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

Parameters3/5

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

The input schema has 100% description coverage, with the 'tags' parameter fully documented. The description mentions 'a set of tags' but adds no further semantic details beyond what the schema provides, such as tag format or examples. With high schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Estimate Bayesian uncertainty') and the target ('for a set of tags based on past feedback'), providing a specific verb and resource. However, it does not explicitly differentiate this tool from its many siblings, such as 'feedback_stats' or 'describe_reliability_entity', which might also involve feedback analysis, leaving room for ambiguity in sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus alternatives. With siblings like 'feedback_stats' and 'feedback_summary' that might relate to feedback analysis, there is no indication of specific contexts, prerequisites, or exclusions for using 'estimate_uncertainty', leaving the agent without usage direction.

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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