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gleachkr
by gleachkr

list_recent_projects

Retrieve recently submitted mathematical projects from the Aristotle API to track formal Lean code and natural language problem submissions.

Instructions

Lists the most recent projects submitted to Aristotle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
save_toNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:105-124 (handler)
    The main handler function for the 'list_recent_projects' tool. It fetches the most recent projects using Project.list_projects, formats a list of project summaries (ID, status, created date), and returns the formatted string or saves it to a file if specified.
    async def list_recent_projects(
        limit: int = 10,
        save_to: Optional[str] = None,
    ) -> str:
        """
        Lists the most recent projects submitted to Aristotle.
        """
        projects, _ = await Project.list_projects(limit=limit)
        
        lines = []
        for p in projects:
            lines.append(f"Project: {p.project_id}, Status: {p.status.value}, Created: {p.created_at}")
        
        result = "\n".join(lines)
        
        if save_to:
            Path(save_to).write_text(result)
            return f"Project list saved to {save_to}"
        
        return result
  • main.py:104-104 (registration)
    The @mcp.tool() decorator that registers the list_recent_projects function as an MCP tool.
    @mcp.tool()
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists projects but lacks details on permissions, rate limits, pagination, or what 'submitted to Aristotle' entails. This leaves significant gaps in understanding how the tool behaves in practice.

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 with no wasted words. It is front-loaded with the core purpose, making it easy to scan and understand quickly, which is ideal for conciseness.

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 low complexity (2 parameters, no annotations, but has an output schema), the description is minimally adequate. It states what the tool does but lacks details on usage, parameters, and behavioral traits. The output schema may cover return values, but the description doesn't provide enough context for full 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?

Schema description coverage is 0%, so the schema provides no parameter details. The description doesn't mention parameters at all, failing to compensate for the coverage gap. However, with only 2 parameters and a default 'limit' of 10, the baseline is 3 as the tool is simple, but no value is added beyond the schema.

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 ('Lists') and resource ('most recent projects submitted to Aristotle'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_project_status' which might also retrieve project information, leaving room for ambiguity in tool selection.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'most recent projects' but doesn't specify scenarios or exclusions, such as whether this is for monitoring submissions or retrieving metadata, nor does it reference sibling tools for comparison.

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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