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Analyze resource

analyze_resource
Read-onlyIdempotent

Check whether a resource and everything it depends on is sound — the deployability question. Pass 'hypothetical' to preview a change instead: hypothetical='delete' or 'unpublish' reports what would break WITHOUT changing anything (run it before deleting something other resources may use), and hypothetical='publish' checks whether the draft you are about to publish actually resolves. An APP is the usual subject: it walks every root the app contains (endpoints, schedules, domains) to the end of each chain and reports what would break. Returns findings {resource, path, severity, check, message}: errors are broken now (a reference that does not resolve, a dependency never published, a declared domain that routes elsewhere, a step naming a resource outside its workflow's scope, a call to a workflow that continues, which cannot run as a sub-workflow), warnings are risks (a published resource following @latest, a sub-workflow call cycle, a domain not yet verified, a sub-workflow step that the scope it runs under for one caller will refuse), info is advisory. deployable is true when there are no errors. Also reports incomplete_nodes: resources whose references are built at run time and so cannot be checked statically. For a non-root subject like a workflow, analysis starts there rather than from whatever reaches it, so severities are not weighted by reachability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesthe kind of resource to analyze: app, dynamic_endpoint, schedule, custom_domain, workflow, api_template, datafile, schema, secret. An app is the usual subject
resourceYesslug of the resource, optionally with a version suffix (e.g. 'shop/storefront' or 'shop/storefront@latest'); a bare slug means @published. For a custom_domain this is the hostname
hypotheticalNoinstead of checking the resource as it is, evaluate a change you are considering: 'delete' or 'unpublish' report what would break (nothing is changed — this is a preview), 'publish' checks whether the DRAFT resolves and flags what already follows this at @published. Run this before a delete or a publish

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
infosYes
errorsYes
subjectYes
findingsYes
warningsYes
deployableYes
incomplete_nodesYes
reachability_knownYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare the safe read-only profile, yet the description adds substantial behavior: the full return shape (findings {resource, path, severity, check, message}), the error/warning/info taxonomy with concrete examples of each, the deployable flag semantics, incomplete_nodes for run-time-built references, and the caveat that non-root subjects are not weighted by reachability. That is well beyond what structured fields provide.

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?

Front-loaded with the core question, then the preview modes, then the return taxonomy — a sensible information order. It is long and dense, and the severity enumeration is heavy, but each clause carries operational detail rather than filler.

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

Completeness5/5

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

For a multi-mode analysis tool with an output schema, the description covers everything an agent needs: what is checked, which subject kinds apply, when to use each hypothetical mode, how findings are graded, and the reachability caveat. Nothing material is left unstated.

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 coverage is 100%, so the schema already defines all three parameters. The description still adds intent the schema lacks: why hypothetical='delete'/'unpublish' is a preview that changes nothing, and that 'publish' checks the DRAFT specifically. The kind parameter explanation largely restates the schema's 'An app is the usual subject'.

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?

States a specific verb and scope: 'Check whether a resource and everything it depends on is sound — the deployability question', with a concrete subject list (app roots: endpoints, schedules, domains). The dependency-chain framing implicitly separates it from the narrower validate_workflow sibling, but no sibling is ever named, so an agent comparing the two must still infer which to pick.

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?

Gives clear conditional triggers: 'run it before deleting something other resources may use' and 'Run this before a delete or a publish'. That is actionable when-to-use guidance tied to the hypothetical parameter. It stops short of explicit when-not guidance or naming validate_workflow/get_resource_graph as the alternatives for narrower questions.

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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