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post_pr_comments

Batch-post comments to a pull request with optional file and line anchoring, enabling targeted feedback on specific code changes.

Instructions

Batch-post comments to a PR with optional file/line positioning.

Each comment dict has keys: content: str (required) file_path: str | None (optional — anchors to file) line_number: int | None (optional — anchors to line, requires file_path) status: str (optional — default "active")

Iteration context is auto-resolved. Comments are positioned on the latest iteration.

dry_run=True validates and returns what would be posted.

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. working_directory: Optional path for context resolution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pr_url_or_idYes
commentsYes
dry_runYes
working_directoryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Given no annotations, the description covers iteration context auto-resolution, dry_run behavior, and comment positioning, but omits batch limits or partial failure handling.

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 well-structured with bullet points and clear sections, but includes some redundant phrasing that could be tightened.

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?

Covers essential behaviors and parameters; output schema exists, so return details are less needed. Missing error handling notes, but sufficient for selection and invocation.

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?

With 0% schema coverage, the description fully compensates by detailing each comment dict key, their optionality, and explaining all parameters (pr_url_or_id, comments, dry_run, working_directory) beyond schema types.

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 the tool posts multiple comments to a PR with optional file/line positioning, distinguishing it from single-comment sibling 'post_pr_comment' and 'post_rich_comments'.

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

Usage Guidelines4/5

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

The description explains the batch behavior and dry_run validation, but does not explicitly compare to alternatives like 'post_pr_comment' or state when to use batch vs single.

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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