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aida_highlight

Record notable development achievements like performance improvements and architecture optimizations to track progress in AI coding sessions.

Instructions

记录值得关注的亮点,如性能提升、架构优化等。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes亮点内容描述

Implementation Reference

  • Implementation of the handler function for 'aida_highlight'.
    function handleHighlight(args: any): any {
      const { path, data } = ensureRunJson();
      const highlight: HighlightItem = {
        content: args.content,
        source: 'auto',
        createdAt: now(),
      };
      data.highlights.push(highlight);
      addEvent(data, 'highlight_added', { content: args.content });
      save(path, data);
      return { success: true, message: `亮点已记录: ${args.content}` };
    }
  • Tool registration for 'aida_highlight'.
      name: 'aida_highlight',
      description: '记录值得关注的亮点,如性能提升、架构优化等。',
      inputSchema: {
        type: 'object',
        properties: {
          content: { type: 'string', description: '亮点内容描述' },
        },
        required: ['content'],
      },
    },
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While '记录' implies persistence, the description does not clarify side effects, visibility of the recorded highlights, authentication requirements, or what happens upon successful execution.

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 sentence with no redundant words. Information is front-loaded with the verb and resource, followed by illustrative examples that earn their place by clarifying scope.

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?

For a simple single-parameter tool with full schema coverage and no output schema, the description adequately covers the core use case. However, given the mutation-like nature (recording/creating entries) and lack of annotations, it omits important behavioral context that would help an agent understand the full impact of invocation.

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?

With 100% schema description coverage, the baseline is 3. The description provides examples of highlight content (performance improvements, architecture optimizations) which gives semantic context for the 'content' parameter, though this does not significantly exceed what the schema already documents.

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 tool records (记录) highlights/highlights (亮点) and provides concrete examples (performance improvements, architecture optimizations) that distinguish it from sibling bug-tracking and logging tools. However, it lacks explicit differentiation text comparing it to alternatives like aida_log_review.

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 explains what the tool does but provides no guidance on when to use it versus siblings (e.g., when to use aida_highlight vs aida_task_done or aida_log_review). There are no exclusions or prerequisites mentioned.

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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