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list_peps

List active Python Enhancement Proposals (PEPs) with compact metadata to track Python language development and proposals.

Instructions

List active Python PEPs with compact metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Tool handler registration and implementation for `list_peps`.
    @mcp.tool
    async def list_peps() -> list[dict]:
        """List active Python PEPs with compact metadata."""
        return await peps_client.list_active_peps()
  • Implementation logic for `list_peps` inside the PepsClient helper.
    async def list_active_peps(self) -> list[dict[str, Any]]:
        """Return compact metadata for active PEPs only."""
        index = await self._get_index()
        return self._to_compact_active_list(index)
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. It discloses behavioral traits by specifying 'active' PEPs only and 'compact metadata' output format, but fails to state safety properties (read-only, non-destructive) or pagination behavior.

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?

Single sentence, front-loaded with verb, no redundant words. Appropriate length for a zero-parameter listing tool.

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 presence of an output schema (which handles return value documentation) and zero input parameters, the description is sufficiently complete. Mentions 'compact metadata' to set expectations, though could note pagination if applicable.

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?

Input schema contains zero parameters. Per evaluation rules, zero-parameter tools receive a baseline score of 4.

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?

States specific verb ('List'), resource ('Python PEPs'), and scope ('active', 'compact metadata'). The 'compact metadata' phrase helps distinguish from sibling get_pep which likely returns full details, though explicit differentiation from search_peps is missing.

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?

Provides no guidance on when to select this tool versus siblings (get_pep for individual retrieval, search_peps for filtered queries). No mention of prerequisites or when not to use.

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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