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Verify scaffold

verify_scaffold

Runs a real npm install && npm run build against the given files on an isolated GitHub Actions runner and reports whether the project builds. Two-call protocol: pass files to start (returns WAIT + a jobId), then call again with that jobId to get the verdict (OK or FAIL). A full install and build usually takes one to two minutes. Requires the projectid of a project this account purchased via purchase_scaffold — attributes every build to a real customer. Use this after editing a get_scaffold result to check the edited project still builds, before handing it to the user. Send the full project — every file, not just the ones you changed. On FAIL, the response includes the tail of the failing step output (compiler/install errors). Fix the files and retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNoThe full project to verify — a scaffold's files with your edits applied. Omit when polling with jobId.
jobIdNoPoll a previously started verification. Omit on the first call (pass files), pass the returned jobId on subsequent calls.
projectidYesThe project id from a previous purchase_scaffold result — must be owned by this account. Required.
envVariablesNoEnv var names to write placeholder values for before building (typically get_component's `envVariables` output) — needed for components that read process.env at build time (e.g. a Supabase client).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does a good job: it discloses real build execution on an isolated runner, the 1–2 minute delay, the two-call async protocol, the attribution to a purchased project, and the failure output tail. It doesn't mention rate limits or error cases like an invalid projectid, but the core behavioral profile is transparent.

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 dense but every sentence earns its place: purpose, async protocol, timing, prerequisite, usage context, full-project requirement, and failure behavior. It front-loads the core purpose and then layers necessary operational details without redundancy.

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?

Given there is no output schema and no annotations, the description is remarkably complete: it explains the WAIT + jobId response, the OK/FAIL verdict, the failure output tail, the polling call pattern, and the required project ownership. An agent has enough information to invoke and interpret the tool correctly.

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 documents each parameter. The description adds real value beyond that by explaining the interaction between files and jobId (omit files when polling), requiring projectid from a prior purchase_scaffold result, and clarifying that envVariables are placeholder values needed for build-time process.env reads.

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 action ('Runs a real npm install && npm run build against the given files') and a clear outcome ('reports whether the project builds'). It also distinguishes itself from siblings by explicitly framing this as the check to run 'after editing a get_scaffold result', which differentiates it from get_scaffold and purchase_scaffold.

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 description gives concrete when-to-use guidance: verify edited scaffolds 'before handing it to the user', and it explains the two-call protocol and the prerequisite (a project purchased via purchase_scaffold). It stops short of naming alternatives or stating explicit 'do not use when' conditions, but the usage context is clear.

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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