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log_accomplishment

Track progress and reinforce achievements by recording completed tasks, helping users monitor accomplishments and maintain motivation.

Instructions

Log something the user accomplished.

This helps track progress and provides positive reinforcement.

Args: description: What the user accomplished

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual storage handler implementation for logging an accomplishment in the database.
    async def log_accomplishment(description: str) -> str:
        """Log something the user accomplished.
    
        Args:
            description: What the user accomplished
    
        Returns:
            Success message
        """
        db = await get_db()
    
        await db.execute(
            "INSERT INTO accomplishments (description) VALUES (?)", (description,)
        )
        await db.commit()
    
        return f"✓ Logged accomplishment: {description}"
  • The tool registration and delegator in the MCP server file.
    @mcp.tool()
    async def log_accomplishment(description: str) -> str:
        """Log something the user accomplished.
    
        This helps track progress and provides positive reinforcement.
    
        Args:
            description: What the user accomplished
        """
        return await storage.log_accomplishment(description)
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. While it mentions 'positive reinforcement' as an outcome, it fails to disclose persistence characteristics (is this stored permanently? retrievable?), whether it triggers side effects (notifications, summaries), or what the output schema contains despite the tool having an output schema.

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 efficiently structured with three distinct components: the action statement, the value proposition, and the parameter documentation. No words are wasted, and the front-loaded purpose immediately clarifies intent despite the informal 'Args:' formatting.

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 single-parameter logging tool, the description is minimally adequate but incomplete. It omits any mention of the return value despite the presence of an output schema, and doesn't address whether logged accomplishments can be retrieved, edited, or deleted later. Given the tool's simplicity, this is viable but leaves operational gaps.

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?

With 0% schema description coverage (the 'description' property has no description field), the tool description compensates by explicitly documenting the parameter under an 'Args:' section ('What the user accomplished'). It successfully adds necessary meaning the schema lacks, though it could enhance further with format examples or length constraints.

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 logs user accomplishments and mentions the benefit (tracking progress and positive reinforcement). However, it doesn't differentiate from siblings like `complete_todo` which also marks task completion/accomplishments, leaving ambiguity about when to use this general-purpose logger versus specific task completion.

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?

There is no guidance on when to use this tool versus alternatives like `complete_todo` (for task completion), `add_user_fact` (for persistent user data), or `add_daily_note_section` (for daily journaling). Without explicit when-to-use criteria, the agent may confuse this with other logging/tracking siblings.

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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