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Analyze project for migration

analyze_project
Read-onlyIdempotent

Analyze a Docker Compose project to map containers, ports, env, volumes, and health checks to Kubernetes equivalents, and identify migration blockers.

Instructions

Explain how this project's Docker concepts map to Kubernetes: containers to Deployments or StatefulSets, port mappings to Services, environment to ConfigMaps and Secrets, volumes to PersistentVolumeClaims, HEALTHCHECK to readiness and liveness probes, and Compose service names to Service DNS. Also reports what cannot be migrated automatically (bind mounts, depends_on ordering, locally built images) as warnings and blockers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryNo
blockersNo
mappingsNo
servicesNo
warningsNo
project_nameYes
project_pathYes
service_countYes
stateful_servicesNo
externally_exposedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover read-only and idempotent behavior. The description adds useful behavioral context beyond that by stating that it reports warnings and blockers for bind mounts, depends_on ordering, and locally built images, which tells the agent what kind of analysis results to expect.

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 dense but well structured, front-loading the purpose and then listing the mappings and blocker reporting. The first sentence is long, but every clause adds concrete mapping detail, so there is little waste.

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?

Given the output schema exists, the description does not need to enumerate return fields. It covers the conceptual mappings, the blocker reporting behavior, and the read-only nature via annotations. It could be stronger on explicit path semantics and alternative tool routing, but it is generally complete for a one-parameter analysis tool.

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 coverage is 0% and the description does not explicitly define what `path` should point to, though 'this project' implies a project root. With only one obvious parameter, the gap is tolerable but not fully compensated.

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 names a specific verb ('explain'), a specific resource ('this project's Docker concepts'), and the target mapping to Kubernetes. It also clearly distinguishes itself from raw inspection tools like inspect_project or inspect_dockerfile by focusing on migration-oriented mapping and reporting blockers.

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 context is clear: this tool is for understanding how a Docker-based project maps to Kubernetes and what cannot be migrated automatically. It does not explicitly name alternatives, but the migration focus is strong enough that an agent can tell when to select it over inspection or manifest-generation siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.