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Morpha

by ai.morphareels

list_projects

List projects as { id, name, editorUrl } entries. The id is what every other tool's projectId argument takes. name is the human-readable label shown in the editor's project picker ("Untitled" when no name has been set — ids are opaque and never shown to the user, so always refer to a project by its name). editorUrl is a tappable link that opens that project in the editor — offer it to the user (by name) when they want to look at one. By default lists the user's OWN personal projects (those not in any workspace). Pass workspaceId (from list_workspaces) to instead list the projects that live in that workspace — including teammates' — each with the owner's ownerEmail. Call this when the user asks "what projects do I have?" or hasn't named a project but you need to operate on one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdNoOptional workspace id (from list_workspaces). When given, lists that workspace's projects instead of the caller's personal ones; requires membership. Omit for personal projects.

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so thoroughly. It discloses the default personal-only scope, the workspace variant with ownerEmail, membership requirements, that ids are opaque and should not be shown, and that editorUrl is a tappable link to offer the user. This is rich, non-obvious behavioral context.

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?

All four sentences earn their place: the output shape, field semantics, default vs workspace behavior, and an explicit usage trigger. The most decision-relevant details are front-loaded, and there is no 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 one optional parameter and no output schema, the description is complete. It covers the return entries, field meanings, default behavior, workspace behavior, and the right moment to invoke the tool. Nothing critical is missing.

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 for the single parameter is 100%, so the baseline is 3. The description adds value by explaining that workspaceId comes from list_workspaces, that membership is required, and what happens when omitted. This goes slightly beyond the schema's own 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 states a specific verb ('List') and resource ('projects'), and precisely defines the output shape as { id, name, editorUrl } entries. It clearly distinguishes this tool from siblings like list_workspaces and list_versions by focusing on project listing, and further clarifies the role of each output field.

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?

The description gives explicit when-to-use guidance: call it when the user asks 'what projects do I have?' or when the user hasn't named a project but you need to operate on one. It also explains the workspaceId alternative and references list_workspaces as the source for workspace IDs, making the decision path clear.

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
Disambiguation3/5

The tool set has several clusters that overlap conceptually: add_keyframe/add_keyframes/set_keyframes_batch, move_band/move_layer/shift_group/set_group_window, and fade_layer/set_layer_transition/set_layer_visible all target similar actions. However, each tool's description is distinct and detailed enough for an agent to disambiguate after careful reading. The sheer volume of 95 tools still creates meaningful selection risk.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (add_, remove_, set_, list_, rename_, create_, delete_), which is predictable and readable. Minor inconsistencies exist: plural variants like add_keyframes vs add_keyframe, mixed specificity like remove_keyframe vs remove_color_keyframe, and a few oddballs like reid_project and clip_processing_status. Overall the pattern is strong and helps navigation.

Tool Count2/5

95 tools is far beyond the well-scoped range and will overwhelm agents; even a comprehensive video editor could consolidate keyframe batch operations, overlay/track manipulations, and page/group window controls. Many tools are highly specific (reid_project, safe_zones, move_band) and place burden on the agent to pick among near-synonym verbs. While the broad domain justifies many operations, this count is excessive for a coherent tool surface.

Completeness3/5

The surface covers a broad editing lifecycle: layers, keyframes, text, captions, audio, pages, groups, versions, projects, workspaces, and collections, including batch operations. However, there is no MCP tool to render/export the final MP4 (explicitly delegated to an SDK) and no upload_video tool for bringing in a clip file, leaving major end-to-end gaps. For the stated purpose of building and editing videos, these are significant omissions that force agents to stop short of delivery.

Resources