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Glama

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, share target (iOS + Android), native system bars. This is where to look up those settings; update_project_metadata changes them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, lowering the burden on the description. The description adds useful behavioral context by specifying it returns a virtual file tree with sizes, dependencies, version, and metadata fields, and clarifies that update_project_metadata performs mutations. No contradiction with annotations.

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 long single paragraph but information-dense; every clause contributes value, and the second sentence provides operational guidance. A bulleted list would improve scannability, but there is no filler or 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?

For a read-only listing tool with no output schema, the description thoroughly enumerates what the response contains: file tree, dependencies, expected_version, and detailed metadata fields. It even tells agents how to use the version value with write tools, making the definition effectively complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain projectId beyond implying a project is selected. The property name is self-explanatory, so the gap is minor, but the description still adds no parameter-level meaning and does not compensate for the missing schema description.

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 uses a specific verb ('List') and clearly identifies the resource: a Floot project's virtual file tree, dependencies, version, and project metadata. It also distinguishes itself from update_project_metadata by stating that this is the lookup tool while update_project_metadata changes those settings.

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 explicitly says 'This is where to look up those settings' and names update_project_metadata as the sibling that changes them, giving agents a clear when-to-use signal. It does not enumerate all exclusions, but the primary usage context is unambiguous.

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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