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saidsef

GitHub PR Issue Analyser

by saidsef

add_inline_pr_comment

Add an inline review comment to a specific line in a file within a GitHub pull request, enabling targeted feedback on code changes.

Instructions

Adds an inline review comment to a specific line in a file within a pull request on GitHub. Args: repo_owner (str): The owner of the repository. repo_name (str): The name of the repository. pr_number (int): The pull request number. path (str): The relative path to the file (e.g., 'src/main.py'). line (int): The line number in the file to comment on. comment_body (str): The content of the review comment. Returns: Dict[str, Any]: The JSON response from the GitHub API containing the comment data if successful. None: If an error occurs while adding the comment. Error Handling: Logs an error message and prints the traceback if the request fails or an exception is raised.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_ownerYes
repo_nameYes
pr_numberYes
pathYes
lineYes
comment_bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
bodyYes
userYes
created_atYes
updated_atYes
Behavior3/5

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

The description discloses error handling and return types (Dict or None on failure). However, it does not mention required permissions, rate limits, or any side effects beyond adding a comment. With no annotations, the description should be more thorough about behavioral implications.

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 Args, Returns, and Error Handling sections. It is clear and not overly verbose, though the Args list repeats schema information unnecessarily.

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 the purpose, parameters, return values, and error handling. For a simple creation tool, this is fairly complete, though it could mention prerequisites (e.g., PR must be open).

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

Parameters2/5

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

The description lists parameters with types but adds no additional meaning beyond the schema. With 0% schema description coverage, the description should explain constraints (e.g., valid line numbers, path format) but does not.

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 adds an inline review comment to a specific line in a file within a pull request on GitHub. This is a specific verb-resource pairing and distinguishes from the sibling 'add_pr_comments' which likely adds general comments.

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 like 'add_pr_comments'. There is no mention of prerequisites or contexts where this tool is inappropriate.

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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