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List Project Files

list_files
Read-only

List a Floot project's virtual file tree with sizes, plus its dependencies, current version (pass the version to write tools as expected_version), and current project metadata — title, description, app icon (iconUrl), splash screen, mobile app id, SSR, iOS Info.plist overrides, Android share target. This is where to look up those settings; update_project_metadata changes them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYes

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds value by detailing the exact return contents (file tree, sizes, dependencies, version, metadata fields), which is more than the annotations alone provide. No contradictions.

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?

The description is a single, well-structured sentence that front-loads the primary action (list file tree) and then concisely lists additional returned data and usage pointers. It is dense but not bloated, with useful detail in a compact form.

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 tool with one parameter and no output schema, the description covers what is returned in detail and even includes a usage note about the version for write tools. It clearly states the relationship with update_project_metadata. Minor missing point: no mention of error conditions or pagination, but these are not critical given the tool's simplicity.

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 0%, so the description must explain the single parameter projectId. It implicitly does so by stating the tool lists a Floot project's tree and metadata, making it clear projectId identifies that project. While not explicit, the context is sufficient for the simple parameter.

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 clearly states the verb 'List' and the resource (a Floot project's virtual file tree), and enumerates the included data: file sizes, dependencies, current version, and detailed project metadata. It differentiates from siblings by explicitly naming update_project_metadata as the tool that changes these settings and notes that the version should be passed to write tools.

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 provides explicit when-to-use guidance: 'This is where to look up those settings' and contrasts with update_project_metadata which changes them. It also instructs the user to pass the version to write tools as expected_version, giving a concrete usage pattern.

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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TDQS

A3.6/5.0
Disambiguation4/5

Tools are mostly distinct, but there is some overlap among file-modifying tools (edit_file, write_file, apply_patch) and between run_code_in_vm and run_code_in_browser. Detailed descriptions and clearly scoped use cases help agents select correctly.

Naming Consistency4/5

Most tools follow a verb_noun snake_case pattern (create_project, list_files, execute_sql), but a few deviate (apply_patch, card_upload_asset, run_code_in_vm). Overall readable and predictable, with only minor inconsistencies.

Tool Count2/5

With 46 tools, the server exceeds the typical well-scoped range and approaches the extreme threshold. While the broad scope of a full development platform justifies many tools, this count may overwhelm agents and increase misselection risk.

Completeness4/5

The tool surface covers the full development lifecycle: project creation, file operations, database management, resource provisioning, deployment, testing, and debugging. Minor gaps exist (e.g., no delete_project or checkpoint management), but core workflows are well-supported.

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