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init_configure_ci

Configure a CI/CD pipeline for your project with automated checks and deployment target support. Specify project name, language, and CI platform to generate build, test, and deploy workflows.

Instructions

Configure CI/CD pipeline for the project with automated checks (Pro)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoAPI key for authentication
languageYesProgramming language
ci_platformYesCI/CD platform
project_nameYesName of the project
deploy_targetNoDeployment target (e.g. aws, gcp, vercel, k8s)
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 says 'Configure' without explaining whether this modifies the repository, generates config files, requires authentication via api_key, whether it is destructive, or what the 'Pro' designation means. This is a significant transparency gap for a mutating tool.

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

Conciseness5/5

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

The description is extremely concise and front-loaded: the verb 'Configure' and object 'CI/CD pipeline' appear immediately. Every remaining word adds relevant context, and there is no superfluous filler.

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?

For a tool with five parameters, no annotations, and no output schema, the description is too thin. It does not explain prerequisites, side effects, when to use this versus a platform-specific generator, or how the optional api_key and deploy_target affect behavior. An agent could easily invoke this tool incorrectly or in the wrong context.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all parameters clearly. The description adds only minimal conceptual framing around 'CI/CD pipeline' and 'automated checks' but does not explain the meaning of api_key, deploy_target, or how ci_platform influences behavior. Baseline 3 is appropriate because the schema does the heavy lifting.

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 states a clear verb and resource: 'Configure CI/CD pipeline for the project with automated checks (Pro)'. It makes the general intent unambiguous. However, it does not explicitly distinguish this tool from closely related siblings like gha_generate_workflow or mobileci_setup_fastlane, so it misses the top tier of clarity.

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?

The description gives no guidance on when to use this tool versus alternatives, no context about project setup prerequisites, and no exclusions. An agent is left to infer that this is the general CI/CD configuration entry point, but no explicit use-case direction is provided.

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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