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grimlor

ado-workflows-mcp

by grimlor
OverviewSchemaRelated ServersScoreDiscussions
Python
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post_rich_comments

Add structured review comments to Azure DevOps pull requests with severity, type, and formatting, supporting batch posting and dry-run validation.

Instructions

Batch-post structured review comments with severity, type, and formatting.

Each comment dict has keys: comment_id: str (required — unique identifier) title: str (required — short heading) content: str (required — comment body) severity: str (optional — "info","suggestion","warning","error","critical") comment_type: str (optional — "general","line","file","suggestion","security","performance") file_path: str | None (optional — anchors to file) line_number: int | None (optional — anchors to line, requires file_path) suggested_code: str | None (optional) reasoning: str | None (optional) business_impact: str | None (optional) tags: list[str] (optional) status: str (optional — default "active") parent_thread_id: int | None (optional — reply to existing thread)

String severity/comment_type values are coerced to enums at this layer. Invalid values return an ActionableError listing valid options.

dry_run=True validates and shows what would be posted without calling the API. filter_self_praise=True (default) removes praise comments authored by the caller.

Args: pr_url_or_id: A full PR URL or numeric PR ID. comments: List of comment dicts to post. dry_run: If True, validate without posting. batch_size: Number of comments per API batch (default 5). filter_self_praise: If True, filter out self-praise comments. working_directory: Optional path for context resolution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pr_url_or_idYes
commentsYes
dry_runYes
batch_sizeYes
filter_self_praiseYes
working_directoryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.2/5.0
Behavior4/5

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

The description discloses enum coercion, dry_run, and filter_self_praise behavior. With no annotations, it carries full burden and does well, though it omits permission requirements or side effects.

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 front-loaded with purpose and structured, but the detailed dict key list and behavior notes are justified given the complexity. It is clear and well-organized.

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?

The description covers purpose, parameters, and key behaviors. The output schema is separate, so that is not a gap. Minor ambiguity in 'working_directory' context resolution, but overall complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds extensive meaning beyond the schema: each comment dict key is detailed, and each parameter (dry_run, batch_size, etc.) is explained, compensating for 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it batch-posts structured review comments with severity, type, and formatting, distinguishing it from simpler comment posting tools like post_pr_comment and post_pr_comments.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for batch-structured comments but does not explicitly state when not to use it or compare to sibling tools. The context from the name and detail provides implicit guidance.

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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