phonebook
Phonebook verwandelt Screenshots, die Ihr Team bereits besitzt, in eine Komponenten-Galerie im Storybook-Stil. Kein neuer Testcode, keine manuell zu pflegenden Design Tokens — es rendert das, was bereits in Ihrer Codebasis vorhanden ist, zu einer statischen Website, die Designer ganz ohne Installation öffnen können. Jedes Repository führt Phonebook unabhängig aus; v1 ist single platform, sodass ein Android-Repository oder ein iOS-Repository genau ein Bundle und eine Website erzeugt.
Funktionen
Kein neuer Testcode — verwendet die
@Previews /#Previews, die Sie bereits geschrieben haben.Kein SaaS-Konto — selbst gehostet, läuft vollständig in Ihrer CI oder lokal.
MCP-first — ein Coding-Agent kann das Setup prüfen, die Coverage analysieren, fehlende Previews ergänzen und die Galerie für Sie erstellen.
Intelligente Komponenten-Gruppierung —
component / state-Karten automatisch aus den Preview-Namen abgeleitet, keine Annotation erforderlich.Plattformübergreifend — Android (Roborazzi + ComposablePreviewScanner, läuft auf der JVM, ohne Emulator) und iOS (SnapshotPreviews, läuft auf einem Simulator).
Versionsbewusstes Setup —
init/doctorgleichen die Bibliotheksversionen mit der Kotlin-Version Ihres Projekts ab und erkennen Kotlin-/Roborazzi-Metadaten-Konflikte, bevor sie zu rätselhaften Compiler-Abstürzen führen.
Related MCP server: ios-agent
Demo


Eine Galerie, generiert aus samples/ios — component / state-Karten, die aus den eigenen #Previews der App gebildet werden, ohne zusätzliche Annotation.
Funktionsweise
phonebook generateführt die Preview-Rendering-Engine Ihrer Plattform aus und sammelt die Ausgabe in einem Bundle (manifest.json+images/).Android: Roborazzi und ComposablePreviewScanner, ausgeführt auf der JVM via Robolectric. Kein Emulator nötig, funktioniert auf Linux-CI.
iOS: SnapshotPreviews, ausgeführt über
xcodebuild testauf einem Simulator. macOS erforderlich.
phonebook buildverwandelt dieses Bundle in eine statische Website — standardmäßig schreibt esindex.htmldirekt in das Bundle-Verzeichnis (die vorhandenen Bilder werden wiederverwendet, nichts wird kopiert), sodass die Website unter<bundle>/index.htmlentsteht. Mit-o <dir>wird stattdessen alles in ein separates, eigenständiges Website-Verzeichnis kopiert, etwa zum Veröffentlichen an anderer Stelle oder zum späteren Zusammenführen mehrerer Bundles. Reines HTML/CSS/JS, funktioniert vonfile://oder jedem statischen Host.
Installation
npm install -g @stag-build/phonebookbrew install stag-build/phonebook/phonebookOder zuerst das Tap hinzufügen und dann installieren:
brew tap stag-build/phonebook
brew install phonebookFormula-Quelle: stag-build/homebrew-phonebook.
npx @stag-build/phonebook <cmd>Mit einem Coding-Agenten verwenden (empfohlen)
Die meisten Menschen werden die CLI nicht direkt ausführen — Phonebook ist dafür gebaut, von einem Coding-Agenten (Claude Code, Codex usw.) über seinen MCP-Server gesteuert zu werden. Der Agent fügt Previews hinzu, prüft das Setup und erstellt die Galerie für Sie; die CLI darunter ist die Engine, die er aufruft.
Der Server läuft über npx @stag-build/phonebook mcp — kein Installationsschritt nötig. Wählen Sie unten Ihren Client.
claude mcp add phonebook -- npx -y @stag-build/phonebook mcpFügen Sie in ~/.codex/config.toml ein:
[mcp_servers.phonebook]
command = "npx"
args = ["-y", "@stag-build/phonebook", "mcp"]Fügen Sie in Ihrer Claude-Desktop-Konfiguration ein (~/Library/Application Support/Claude/claude_desktop_config.json auf macOS):
{
"mcpServers": {
"phonebook": {
"command": "npx",
"args": ["-y", "@stag-build/phonebook", "mcp"]
}
}
}Fügen Sie in .cursor/mcp.json (Projekt) oder ~/.cursor/mcp.json (global) ein:
{
"mcpServers": {
"phonebook": {
"command": "npx",
"args": ["-y", "@stag-build/phonebook", "mcp"]
}
}
}Fügen Sie dies im Stammverzeichnis des Workspace Ihres Projekts in .codex/config.toml ein. Der Xcode-Agent läuft mit einem minimalen PATH, deshalb umschließt der Befehl npx mit einer Shell, die zuerst die üblichen Verzeichnisse von Homebrew/nvm hinzufügt:
[mcp_servers.phonebook]
command = "/bin/zsh"
args = [
"-lc",
"PATH=/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin; npx -y @stag-build/phonebook mcp"
]
enabled = trueFügen Sie den mcpServers-Block zu ~/Library/Developer/Xcode/CodingAssistant/ClaudeAgentConfig/.claude.json hinzu:
{
"mcpServers": {
"phonebook": {
"command": "/bin/zsh",
"args": [
"-lc",
"PATH=/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin; npx -y @stag-build/phonebook mcp"
]
}
}
}Android Studio (Gemini Agent Mode): derzeit noch nicht unterstützt — die MCP-Integration verbindet sich nur mit „Remote"-httpUrl-Servern, nicht mit lokalen stdio-Prozessen wie dem von Phonebook. Verwenden Sie stattdessen einen der terminalbasierten Clients oben (Claude Code, Codex CLI) aus dem Android-Repository.
Fragen Sie dann einfach im Chat Ihres Android- oder iOS-Repository:
„Nutze das Phonebook-MCP und erstelle einen Katalog für meinen Designer.“
Der Agent übernimmt den Rest — Setup prüfen, fehlende Previews ergänzen, generieren und die Website bauen. Für gezielte Aufgaben bietet er außerdem: check_setup (Setup-Diagnose, wie phonebook doctor), analyze_coverage (Komponenten ohne Previews oder Dark-Varianten), get_preview_guidance, run_generate und run_build.
Schnellstart: Android
Führen Sie zuerst phonebook init aus — das erkennt die Kotlin-Version Ihres Projekts und gibt diese Anleitung mit passenden Bibliotheksversionen aus (z. B. erhalten Kotlin-2.0-Projekte Roborazzi 1.60.0, Kotlin 2.2+ die aktuelle Version). Die Versionen unten gelten für ein Projekt mit aktuellem Kotlin (Beispiel in samples/android/app/build.gradle.kts ansehen):
// app/build.gradle.kts
plugins {
id("io.github.takahirom.roborazzi") // root build.gradle.kts: version "1.72.0" apply false
}
roborazzi {
generateComposePreviewRobolectricTests {
enable = true
packages = listOf("dev.stag.phonebook.sample") // your app's package
}
}
dependencies {
testImplementation("org.robolectric:robolectric:4.14.1")
testImplementation("io.github.takahirom.roborazzi:roborazzi:1.72.0")
testImplementation("io.github.takahirom.roborazzi:roborazzi-compose:1.72.0")
testImplementation("io.github.sergio-sastre.ComposablePreviewScanner:android:0.9.3")
testImplementation("io.github.takahirom.roborazzi:roborazzi-compose-preview-scanner-support:1.72.0")
testImplementation("androidx.compose.ui:ui-test-junit4") // version from your Compose BOM, or pin one
}Fügen Sie eine phonebook.config.json neben settings.gradle.kts ein:
{
"appName": "My Android App",
"platform": "android",
"android": { "modules": [":app"], "variant": "debug" }
}Dann, aus dem Repository, das Phonebook enthält:
npx @stag-build/phonebook generate -C /path/to/your/android/repo
npx @stag-build/phonebook build -C /path/to/your/android/repoÖffnen Sie phonebook-out/index.html.
Schnellstart: iOS
Fügen Sie Ihrem Projekt das SPM-Paket SnapshotPreviews hinzu und ein kleines XCTest-Target, das von SnapshotTest erbt (siehe samples/ios für ein vollständiges funktionierendes Beispiel):
// PhonebookSnapshotTests.swift
import SnapshottingTests
final class PhonebookSnapshotTests: SnapshotTest {
override class func snapshotPreviews() -> [String]? {
return nil // record every #Preview
}
}Fügen Sie phonebook.config.json neben Ihrer .xcodeproj ein:
{
"appName": "My iOS App",
"platform": "ios",
"ios": {
"project": "MyApp.xcodeproj",
"scheme": "MyApp",
"simulator": "iPhone 17 Pro"
}
}Ihr Scheme muss das Snapshot-Test-Target bauen und testen (siehe PhonebookSample.xcscheme im Beispiel). Dann:
npx @stag-build/phonebook generate -C /path/to/your/ios/repo
npx @stag-build/phonebook build -C /path/to/your/ios/repoÖffnen Sie phonebook-out/index.html.
Namenskonvention
Phonebook gruppiert Screenshots aus Ihren vorhandenen Preview-Namen in component / state-Karten — keine Annotation erforderlich. Die vollständigen Regeln und Beispiele finden Sie in docs/naming-convention.md.
Konfiguration
phonebook.config.json:
Key | Typ | Standard | Hinweise |
|
| — | Erforderlich. Wird in der Kopfzeile der Galerie angezeigt. |
|
| — | Erforderlich. |
|
|
| Ausgabeverzeichnis für das Bundle, relativ zur Konfigurationsdatei. |
|
|
| Gradle-Module, die aufgezeichnet werden sollen. |
|
|
| Build-Variante; Phonebook führt |
|
| — | Pfad zur |
|
| — | Pfad zur |
|
| — | Erforderlich. Scheme, das das SnapshotPreviews-Test-Target enthält. |
|
|
| Simulatorgerätename für |
|
| automatisch ermittelt |
|
Sowohl generate als auch build akzeptieren -C <dir> (Projektverzeichnis mit phonebook.config.json). generate nimmt -o <dir> mit an, um das Bundle-Ausgabeverzeichnis zu überschreiben, und --allow-empty, um einen Lauf zu tolerieren, bei dem keine Previews aufgezeichnet werden. Phone kann zusätzlich einen Bundle-Pfad übernehmen. Wenn keiner angegeben ist, wird das Bundle-Verzeichnis des Projekts verwendet, und -o <dir> für das Website-Ausgabeverzeichnis; ohne -o schreibt build index.html direkt in das Bundle-Verzeichnis und verwendet dessen images/ vorhanden (ohne Kopieren) — genau das tun die Schnellstarts oben. Mit -o <dir> werden die Bilder des Bundles stattdessen in ein separates, eigenständiges Website-Verzeichnis kopiert.
phonebook init und phonebook doctor
phonebook init erkennt Ihre Plattform und erstellt phonebook.config.json sowie die Abhängigkeits-Einrichtungssnippets — mit Bibliotheksversionen, die auf Ihr Projekt-Kotlin zugeschnitten sind, und mit Ihrem App-Paket, das bereits ausgefüllt ist. Es ändert jedoch nie selbst Ihre Build-Dateien.
phonebook doctor prüft, ob alles, was generate braucht, verdrahtet ist: Plugin- und Test-Abhängigkeiten (über die Gradle-Version-Kataloge, falls Sie sie verwenden), den packages-Wert des Scanners, die Kotlin-/Roborazzi-Kompatibilität und die Development-Toolchain (JDK/Xcode/Simulator). Fügen Sie --deep hinzu, um zusätzlich die Testquellen zu kompilieren — langsamer, aber maßgeblich, wenn eine statische Prüfung und die Realität nicht übereinstimmen. Unter iOS, wenn SnapshotPreviews verlinkt ist, aber noch keine SnapshotTest-Unterklasse existiert, benennt doctor das genaue Target und den Ordner, in dem sie anzulegen ist (aus der .pbxproj ausgelesen), sodass "Fügen Sie das Feld hinzu" nie ohne Ortsangabe bleibt.
phonebook init --write-snapshot-class ist die eine Ausnahme von der eigentlichen Funktion des Verbots: Wenn die iOS-Prüfung von doctor das Verlinkungs-Target identifiziert und der Quellordner dieses Targets zu den dateisystem-synchronisierten Gruppen von Xcode gehört, schreibt sie direkt <folder>/PhonebookSnapshots.swift — unbedenklich, da ein synchroner Ordner von Xcode automatisch übernommen wird, also keine project.pbxproj-Änderung erzwungen wird. In allen anderen Fällen wird die Aktion verweigert (mit Grund angegeben): noch keine SnapshotPreviews-Verkabelung, ein Projekt ohne Synchronisierung über EWS, oder eine Unterklasse, die bereits existiert.
phonebook mcp startet den MCP-Server — siehe „Mit einem Coding-Agenten verwenden“ oben für die Einrichtung und Beispiel-Prompts.
Anforderungen
Android: JDK 17+. Kein Emulator nötig – Roborazzi rendert über Robolectric auf der JVM, sodass generate auf einem Linux-CI läuft.
iOS: macOS mit installiertem Xcode sowie ein gestarteter oder startbarer Simulator (generate führt xcodebuild test gegen ein benanntes Simulator-Ziel aus). Erfordert einen macOS-Runner in CI.
Siehe docs/ci.md für CI-Rezepte und docs/naming-convention.md für die Namensregeln.
Roadmap
Nach v1 (M5), noch nicht umgesetzt:
Suche und Filter in der generierten Galerie
Multi-Bundle-Merge mit einer Seite-an-Seite-Ansicht (plattformübergreifende Apps)
Versions-Diff zwischen zwei Durchläufen (das Manifest enthält bereits Commit- und Bild-Hashes, um dies zu ermöglichen)
Zusätzliche CI-Rezepte-Dokumentation
License
MIT – siehe LICENSE.
Available Tools
5 toolsanalyze_coverageA
Scan the codebase for UI components and the previews that cover them, and report what each component is missing: states implied by its parameters, environment objects no preview supplies, dark theme, large text, and localization when the project ships one. Read-only — it reports the gaps, it does not write previews. After editing, pass changed: true (or paths) to hear only about what you touched; the whole project is always scanned either way, so the answers stay correct.
| Name | Required | Description | Default |
|---|---|---|---|
| dir | No | Project directory containing phonebook.config.json | . |
| paths | No | Report only components declared in these files or directories, relative to the project directory. The whole project is still scanned. | |
| changed | No | Report only components in files with uncommitted git changes — what you just edited. Ignored outside a git repository. Combined with paths when both are given. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states 'Read-only — it reports the gaps, it does not write previews,' and clarifies that the entire project is scanned even when filters are applied, ensuring the answers stay correct. This is honest and thorough for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense paragraph but each sentence serves a purpose: purpose, behavioral safety, and usage guidance. It is front-loaded with the main objective, and the filtering instructions are kept concise. Slightly long but no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with 3 optional parameters and no output schema, the description adequately explains what is analyzed, what is reported, and how filters behave. It does not specify the exact return format, but that is a minor gap given the clarity of the rest. The tool is fully callable correctly from the description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds valuable context beyond the schema: it explains that paths restrict reporting but not scanning, that changed is ignored outside a git repo, and that both combine when given together. This clarifies edge cases and adds meaning to each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Scan'), resource ('codebase'), and a precise objective: report what each UI component is missing in preview coverage (states, environment objects, dark theme, large text, localization). It clearly distinguishes itself from sibling tools like get_preview_guidance (which presumably offers guidance) and run_build/run_generate/check_setup (which are operational, not analytical).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the changed and paths parameters ('After editing, pass changed: true (or paths) to hear only about what you touched'), and notes that the whole project is always scanned regardless. It doesn't explicitly contrast with get_preview_guidance, but the analytical vs. guidance nature is implied, and the filtering usage is well covered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_setupA
Check that the project is correctly set up for phonebook generate (same checks as phonebook doctor): libraries wired, test target present, JDK/Xcode/simulator available.
| Name | Required | Description | Default |
|---|---|---|---|
| dir | No | Project directory containing phonebook.config.json | . |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does communicate that the tool performs checks, names the checks (libraries, test target, JDK/Xcode/simulator), and implies a read-only nature. However, it does not describe failure behavior, exit codes, output format, or whether the tool attempts any fixes, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one tight, well-structured sentence. It front-loads the purpose, gives the equivalence to `phonebook doctor`, and lists the main checks without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter check tool with no output schema and no annotations, the description covers the essential context: what is checked and why. It could be slightly more complete by stating what a successful or failed check returns, but the current level is adequate for selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter `dir` is fully documented in the schema with a clear description and default value, so schema coverage is 100%. The tool description adds no additional parameter semantics, which is acceptable given the schema already handles it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and resource ('project setup'), names the exact command it supports (`phonebook generate`), and enumerates the concrete checks performed. It clearly distinguishes itself from generation/build tools like `run_generate` and `run_build`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this is a precondition check for `phonebook generate`, and the reference to `phonebook doctor` provides an equivalence that helps the agent understand behavior. It does not explicitly state 'use before run_generate' or list when not to use it, so it falls just short of full explicit routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_preview_guidanceA
Return the preview naming convention plus a ready-to-paste preview code template for a component, so any agent writes consistent previews.
| Name | Required | Description | Default |
|---|---|---|---|
| states | No | State names, e.g. ["Enabled", "Disabled"] | |
| platform | Yes | Target platform | |
| component | No | Component name, e.g. "Button" |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral disclosure burden. It clearly discloses a non-mutating return ('Return') and the output type (naming convention + template), but it does not describe output format, failure behavior, or prerequisites. For a simple getter this is adequate but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no filler, and the key deliverable is front-loaded before the outcome clause. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Only three parameters with 100% schema coverage reduce the burden on the description. However, with no annotations and no output schema, the description could usefully state how platform, states, and component are handled, or when this guidance should be fetched relative to run_generate and run_build. These are gaps but not fatal ones.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline for this dimension is 3. The description's 'for a component' aligns with the 'component' parameter but adds no value beyond the schema's documented parameters; nothing is said about how states or platform affect the returned template.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') and identifies a concrete resource ('preview naming convention plus a ready-to-paste preview code template'), with the desired outcome 'so any agent writes consistent previews.' It clearly separates itself from execution-oriented siblings like run_generate and run_build, though it does not explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'so any agent writes consistent previews' implies this tool should be consulted before writing a preview, but there is no explicit statement of when to use it versus siblings or when not to use it. It lists no alternatives and no exclusion conditions, leaving agents to infer its place in the workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_buildA
Build the static gallery site from a bundle, same as phonebook build <bundle>.
| Name | Required | Description | Default |
|---|---|---|---|
| bundle | Yes | Bundle directory produced by run_generate / `phonebook generate` | |
| output | No | Site output directory (default: the bundle directory itself, reusing its images) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the core action; it does not disclose side effects such as writing into the bundle directory, overwriting output, or requirements. The output default noted in the schema is useful but outside the description, so the description itself carries too little behavioral burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler, and the CLI-equivalent note is a compact way to anchor expected behavior. It is appropriately sized for a simple build command.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with full schema coverage, the inputs are adequately specified, but the missing usage routing and side-effect disclosure leave the agent to infer workflow and safety. With no annotations or output schema, a bit more context would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'bundle' and 'output' documented, so the baseline applies. The description adds no parameter semantics beyond the schema other than echoing 'bundle'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with an explicit verb ('Build') and resource ('static gallery site'), and identifies the input ('from a bundle'), which clearly separates it from the sibling generation/analysis/check tools. The CLI alias reinforces the exact operation without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'from a bundle' wording and the schema's 'produced by run_generate' hint imply a build-after-generate workflow, but the description does not explicitly say when to use this tool versus siblings like run_generate or analyze_coverage. No when-not or alternative conditions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_generateA
Run the platform engine to render all previews and produce a bundle (manifest + images), same as phonebook generate. When previews crash, keeps what rendered and says which previews did not, by file and line. Pass changed or files to render only the previews declared in those files, for a faster loop while iterating.
| Name | Required | Description | Default |
|---|---|---|---|
| dir | No | Project directory containing phonebook.config.json | . |
| files | No | Render only previews declared in these files, relative to the project directory. | |
| changed | No | Render only previews declared in files with uncommitted git changes. Ignored outside a git repository. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It does disclose crash handling (keeps what rendered, reports failures by file and line) and the bundle output, which is valuable. However, it omits other behavioral traits like side effects, idempotency, and prerequisites, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no filler. It front-loads the core purpose, then adds crash behavior and usage tips. Every sentence earns its place and the structure is clean.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should clarify return values and side effects. It mentions the bundle output but does not specify what the tool returns to the agent. It also does not state prerequisites like the config file beyond the dir parameter, leaving completeness gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are fully described in the schema (100% coverage), so the description adds little beyond what is already structured. It mentions passing files or changed but does not elaborate on their semantics beyond the schema's descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs the platform engine to render previews and produce a bundle, referencing 'phonebook generate' for familiarity. It does not explicitly distinguish from sibling tools like run_build, but the core action is unambiguous and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear guidance on using the files and changed parameters to limit rendering to specific files for a faster iteration loop. However, it does not mention when to use this tool over siblings or any exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v0.1.7- Changed
analyze_coverage2 fields changed- added
Input schema / properties / changedAdded value: +{ + "description": "Report only components in files with uncommitted git changes — what you just edited. Ignored outside a git repository. Combined with paths when both are given.", + "type": "boolean" +} - added
Input schema / properties / pathsAdded value: +{ + "description": "Report only components declared in these files or directories, relative to the project directory. The whole project is still scanned.", + "items": { + "type": "string" + }, + "type": "array" +}
- Changed
run_generate2 fields changed- added
Input schema / properties / changedAdded value: +{ + "description": "Render only previews declared in files with uncommitted git changes. Ignored outside a git repository.", + "type": "boolean" +} - added
Input schema / properties / filesAdded value: +{ + "description": "Render only previews declared in these files, relative to the project directory.", + "items": { + "type": "string" + }, + "type": "array" +}
5 tool updates
v0.1.2- First observed
analyze_coverage - First observed
check_setup - First observed
get_preview_guidance - First observed
run_build - First observed
run_generate
TDQS
Scored across 5 tools
Each tool addresses a distinct step in the preview workflow: guidance, setup, coverage analysis, generation, and building. The only adjacent pair (run_generate and run_build) is clearly separated by bundle output versus static-site output.
Most names are imperative snake_case with a clear object (get_preview_guidance, analyze_coverage, check_setup). run_build and run_generate are a minor deviation because they use a run_ prefix around CLI command names rather than a pure verb_noun structure.
Five tools is well-scoped for a focused preview-generation workflow. Each tool earns its place by covering a separate phase from setup to final build, with no redundant or padding tools.
The tool set covers the full core loop: check setup, get authoring guidance, analyze coverage gaps, generate previews, and build the gallery site. The absence of a write-preview tool is fine because editing code happens outside the server, and the guidance plus coverage tools support that workflow.
Maintenance
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