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omniwaifu

Pydantic AI Documentation Server

by omniwaifu

list_available_changelogs

Retrieve available changelog files from the Pydantic-AI documentation repository to track version history and updates.

Instructions

Lists all available changelog files found in the Pydantic-AI documentation repository (e.g., in 'docs/history/').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the `list_available_changelogs` MCP tool, which scans the `docs/history/` directory for markdown files and returns them as a sorted list of `ChangelogFile` objects.
    @app.tool()
    async def list_available_changelogs() -> List[ChangelogFile]:
        """
        Lists all available changelog files found in the Pydantic-AI documentation repository (e.g., in 'docs/history/').
        """
        logger.info("list_available_changelogs called")
        changelogs: List[ChangelogFile] = []
        try:
            repo_root = get_repo_path()
            history_dir = repo_root / "docs" / "history"
    
            if not history_dir.is_dir():
                logger.warning(f"Changelog directory not found: {history_dir}")
                return []
    
            for file_path in history_dir.glob("*.md"):
                if file_path.is_file():
                    version_name = file_path.stem
                    relative_path = file_path.relative_to(history_dir).as_posix()
                    changelogs.append(
                        ChangelogFile(
                            name=file_path.name,
                            path=f"history/{relative_path}",
                            version=version_name,
                        )
                    )
    
            changelogs.sort(
                key=lambda cf: [
                    int(part) if part.isdigit() else part for part in cf.version.split(".")
                ],
                reverse=True,
            )
            logger.info(f"Found {len(changelogs)} changelog files.")
    
        except Exception as e:
            logger.error(f"Error listing available changelogs: {e}", exc_info=True)
            return []
        return changelogs
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. It states the tool lists files but doesn't describe return format, pagination, error handling, or any constraints (e.g., rate limits, authentication needs). This leaves significant gaps for a tool with no structured behavioral hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core action. It avoids unnecessary words, though it could be slightly more structured (e.g., by explicitly noting it returns a list of file names).

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

Completeness2/5

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

Given no annotations, no output schema, and a simple but undocumented behavioral profile, the description is incomplete. It doesn't explain what the output looks like (e.g., list of strings, JSON structure), error conditions, or any operational context, making it inadequate for reliable agent use.

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?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description adds no parameter information, which is appropriate here. Baseline is 4 for zero parameters, as there's nothing to compensate for.

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's purpose with a specific verb ('Lists') and resource ('all available changelog files'), and identifies the location ('Pydantic-AI documentation repository'). It distinguishes from some siblings like 'get_changelog_content' (which retrieves content) but doesn't explicitly differentiate from 'list_topics' or 'get_document_by_path'.

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. It doesn't mention prerequisites, context for usage, or comparisons to sibling tools like 'list_topics' or 'get_document_by_path', leaving the agent to infer usage based on tool names alone.

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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