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awais2o

devops-deploy-guard-mcp-server

by awais2o

Plan Dynamic Production Deployment (v1.5.0 Context-Aware)

plan_dynamic_deployment
Read-onlyIdempotent

Analyze git diffs, dependency changes, schema updates, and pending migrations to generate a conditional deployment plan for production.

Instructions

Analyzes git diffs, dependency changes, schema updates, and pending migrations to generate a production-first conditional deployment plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_nameNoPM2 app name or ecosystem file
app_pathNoAbsolute path to application directory on remote server (auto-resolved if omitted)
auto_analyzeNoWhether to SSH into server and auto-detect changes, runtimes, and migration status
target_branchNoRemote git target branch for change diff analysis (default: upstream default / main)
force_all_stepsNoSet to true to force dependency install and migration steps regardless of git diff
custom_build_cmdNoOptional override for build command
custom_install_cmdNoOptional override for dependency install command
migration_frameworkNoDatabase migration frameworkauto
custom_migration_cmdNoOptional override for production database migration command
Behavior3/5

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

Annotations declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds detail about the analysis inputs (git diffs, schema, migrations) and conditional nature, but does not elaborate on outcome format, potential external calls, or runtime behavior beyond what annotations imply.

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 single, clear sentence that front-loads the purpose. However, it could be slightly restructured for readability, e.g., by listing key analyses separately. Still, it is concise without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (9 parameters, no output schema), the description covers core purpose but does not explain what a 'production-first conditional deployment plan' entails, nor does it address the absence of output schema or integrate with sibling tool usage. It is minimally adequate.

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 each parameter's meaning. The description does not add parameter-level information beyond what is in the schema, so baseline 3 is appropriate.

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 specifies the tool's action: analyzing git diffs, dependency changes, schema updates, and pending migrations to generate a production-first conditional deployment plan. It distinguishes from siblings like plan_docker_deployment by focusing on dynamic, change-based planning.

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 does not provide explicit guidance on when to use this tool versus alternatives. It implies usage for deployment planning but lacks when-not or alternative suggestions, leaving the agent without clear selection criteria among multiple deployment and diagnostic siblings.

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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