flutter-mcp-toolkit-guide

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Author repo skills-registry

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Entry point for inspecting or driving a running Flutter app from your AI assistant — routes to the right task skill (inspect / c…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “When to use”, “Step 1: Preflight”, “Step 2: Pick the right skill for the user's intent”, “Step 3: Execute”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name flutter-mcp-toolkit-guide directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “When to use / Step 1: Preflight / Step 2: Pick the right skill for the user's intent” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / shell-exec; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

When to use

Use this skill when the user wants to inspect or drive a running Flutter app from this conversation. Examples:

"Tap the login button in my app"
"Why is the home screen blank?"
"Take a screenshot and tell me what's broken"
"Expose my cart / flags / internal state to the agent via MCP"

If the user is asking about Flutter concepts unrelated to a running app (architecture questions, package selection), this skill does not apply.

Step 1: Preflight

Always run flutter-mcp-toolkit doctor --json first. Parse the output:

status: "ok" — proceed to Step 2.
status: "error" and error.code: "binary_not_found" — load flutter-mcp-toolkit-setup and follow its install instructions.
status: "error" and error.code: "vm_not_connected" — load flutter-mcp-toolkit-setup and follow its troubleshooting section.
Any other error — load flutter-mcp-toolkit-debug and read the error envelope playbook.

Step 2: Pick the right skill for the user's intent

User intent	Load skill
Read state ("what's on screen?", "show me errors", "screenshot")	`flutter-mcp-toolkit-inspect`
Drive UI ("tap X", "type into Y", "scroll to Z", "hot reload")	`flutter-mcp-toolkit-control`
Diagnose ("why is X failing?", "show recent logs", "evaluate expression")	`flutter-mcp-toolkit-debug`
Register app-specific MCP tools/resources (`MCPCallEntry`, `bootstrapFlutter` `additionalEntries`)	`flutter-mcp-toolkit-custom-tools`

If the task spans more than one (e.g. "tap the button and show me what changed"), load inspect AND control. Skills are additive.

Step 3: Execute

Each task skill has the tool list, parameter shapes, and example calls. Follow the prelude at the top of the skill — it tells you whether you're calling MCP tools or shelling out to the CLI.

Tool taxonomy reference

The core toolkit tools fall into these categories. The full list with parameter shapes lives in the task skills.

Inspection (read-only): discover_debug_apps, get_app_errors, get_screenshots, get_view_details, get_vm, get_extension_rpcs, semantic_snapshot, inspect_widget_at_point, capture_ui_snapshot, connect_debug_app. → flutter-mcp-toolkit-inspect.
Interaction (mutating): tap_widget, long_press, enter_text, fill_form, scroll, swipe, drag, hover, press_key, wait_for, navigate, handle_dialog, hot_reload_flutter, hot_restart_flutter, hot_reload_and_capture. → flutter-mcp-toolkit-control.
Debug: get_recent_logs, evaluate_dart_expression. → flutter-mcp-toolkit-debug.
Dynamic registry (app-defined): after registration in the Flutter app, list with list_client_tools_and_resources, then client_tool / client_resource — wire names as fmt_* when calling MCP. → flutter-mcp-toolkit-custom-tools.

When in doubt

If doctor is green but a tool call fails, read the returned error.code and error.recovery fields. The full code → recovery table is in flutter-mcp-toolkit-debug.

Source: Arenukvern/mcp_flutter — distributed by TomeVault.

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: AI
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @tomevault-io · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Guided setup
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Unspecified
Detected file/system behavior: Read-only
Shell exec
Detected network behavior: Local-only
Install commands: None (reference only)

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview flutter-mcp-toolkit-guide.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

<!-- @FMT_MODE_PRELUDE -->

## When to use

Use this skill when the user wants to inspect or drive a running Flutter app
from this conversation. Examples:
- "Tap the login button in my app"
- "Why is the home screen blank?"
- "Take a screenshot and tell me what's broken"
- "Expose my cart / flags / internal state to the agent via MCP"

If the user is asking about Flutter concepts unrelated to a running app
(architecture questions, package selection), this skill does not apply.

## Step 1: Preflight

Always run `flutter-mcp-toolkit doctor --json` first. Parse the output:

- `status: "ok"` — proceed to Step 2.
- `status: "error"` and `error.code: "binary_not_found"` — load
  `flutter-mcp-toolkit-setup` and follow its install instructions.
- `status: "error"` and `error.code: "vm_not_connected"` — load
  `flutter-mcp-toolkit-setup` and follow its troubleshooting section.
- Any other error — load `flutter-mcp-toolkit-debug` and read the error
  envelope playbook.

## Step 2: Pick the right skill for the user's intent

| User intent | Load skill |
|---|---|
| Read state ("what's on screen?", "show me errors", "screenshot") | `flutter-mcp-toolkit-inspect` |
| Drive UI ("tap X", "type into Y", "scroll to Z", "hot reload") | `flutter-mcp-toolkit-control` |
| Diagnose ("why is X failing?", "show recent logs", "evaluate expression") | `flutter-mcp-toolkit-debug` |
| Register app-specific MCP tools/resources (`MCPCallEntry`, `bootstrapFlutter` `additionalEntries`) | `flutter-mcp-toolkit-custom-tools` |

If the task spans more than one (e.g. "tap the button and show me what
changed"), load `inspect` AND `control`. Skills are additive.

## Step 3: Execute

Each task skill has the tool list, parameter shapes, and example calls. Follow

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> When to use → Step 1: Preflight → Step 2: Pick the right skill for the user's intent → Step 3: Execute → Tool taxonomy reference → When in doubt
terms    -> Inspection (read-only) · Interaction (mutating) · Debug · Dynamic registry (app-defined)
files/cmd -> flutter-mcp-toolkit doctor --json · status: "ok" · status: "error" · error.code: "binarynotfound" · flutter-mcp-toolkit-setup · error.code: "vmnotconnected" · flutter-mcp-toolkit-debug · flutter-mcp-toolkit-inspect
body sha256 -> ae6f2fbca72a