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Backend Render

backend_render
Idempotent

Render scaffolded backend from app.spec.json offline and idempotently: prune Supabase to monetization mode and generate shared config, legal sources, listing locales. Use after spec edits; no deploy.

Instructions

Render the scaffolded backend from app.spec.json (offline, idempotent): prune supabase/ to the monetization mode, generate shared config, legal sources and listing locales.

Use when: after editing the spec, before backend_deploy. Nothing is deployed. Returns: {ok, mode, render, legal, listing?}.

Input Schema

NameRequiredDescriptionDefault
app_dirYesAbsolute path to the app project directory (contains app.spec.json), e.g. /Users/me/Apps/MyApp.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.5
    • addedInput schema / properties / app_dir / description
      Added value: +"Absolute path to the app project directory (contains app.spec.json), e.g. /Users/me/Apps/MyApp."
  2. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds genuinely useful context beyond them: it is offline, it mutates the workspace by pruning supabase/ to the monetization mode, and nothing is deployed. It stops short of saying what pruning destroys or how failures are surfaced.

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?

Three tight lines: purpose with parenthetical qualifiers first, then when-to-use, then return shape. Every sentence carries information and the most important scoping fact (offline, nothing deployed) is front-loaded.

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?

For a single-parameter, annotated mutation tool with an output schema, the description covers purpose, timing, side-effect scope, and return fields. The returns line is largely redundant with the existing output schema, and error behavior (ok=false cases) is not touched.

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?

Only one parameter exists and schema description coverage is 100%, so the schema already documents app_dir fully. The description's reference to app.spec.json adds modest context (the spec file drives the render) but no syntax or format detail beyond the schema.

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 and resource ('Render the scaffolded backend from app.spec.json') and enumerates the concrete operations performed (prune supabase/, generate shared config, legal sources, listing locales). This is clearly distinguishable from siblings like backend_deploy or legal_render.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit sequencing ('after editing the spec, before backend_deploy') and names the sibling it precedes, plus the key negative constraint 'Nothing is deployed'. The agent knows exactly when this tool is the right choice versus the deploy tool.

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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