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github_create_repo

Create a new GitHub repository with custom settings for visibility, README initialization, gitignore, license, and organization.

Instructions

Create a new GitHub repository.

Args: name: Repository name description: Repository description private: Make repository private (default: False = public) auto_init: Initialize with a README (default: True) gitignore_template: Gitignore template name (e.g., 'Python', 'Node', 'Go') license_template: License template (e.g., 'mit', 'apache-2.0', 'gpl-3.0') org: Organization to create repo under (empty = personal repo) session_name: GitHub session to use

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNo
nameYes
privateNo
auto_initNo
descriptionNo
session_nameNodefault
license_templateNo
gitignore_templateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden of behavioral disclosure. It documents parameter defaults (private: False, auto_init: True) which is helpful, but doesn't disclose consequences like whether a repo creation overwrites existing repos, what happens on name conflicts, or the behavior when auto_init is True/False. Given no annotations, more behavioral context would be expected.

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 compact, well-organized parameter listing following the Args pattern. Each parameter is on one line with a concise explanation. It's front-loaded with the core purpose statement. Slightly verbose on the full docstring format but efficient overall.

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?

With 8 parameters, an output schema, and no annotations, the description covers all parameters with defaults and examples. It doesn't describe return values, but an output schema exists so that's acceptable. For a creation tool with a session concept (session_name), it could explain more about the session concept, but the parameter list is complete. The example templates are genuinely useful.

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?

Schema description coverage is 0%, so the description must fully compensate. It documents all 8 parameters with examples for gitignore_template ('Python', 'Node', 'Go') and license_template ('mit', 'apache-2.0', 'gpl-3.0'), and explains private/auto_init defaults. The org field is clarified as empty = personal repo. This adds real meaning beyond the bare 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 'Create a new GitHub repository' with a specific verb+resource. It distinguishes from siblings like github_fork_repo, github_update_repo, and github_delete_repo which handle different operations on repositories.

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 creation use (first line states the purpose) but provides no explicit when-to-use guidance, prerequisites, or alternatives. The org field hints at usage context (personal vs organization repos) but there's no explicit exclusion or differentiation guidance beyond the obvious.

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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