Create a new project with sensible templates. Sets up project + initial elements, tasks, and agent instructions based on the chosen category.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | ||
| title | Yes | Project title | |
| template | Yes | Template: software=Software project, research=Research/Analysis, creative=Creative project, learning=Learning project, business=Business idea, general=General purpose | |
| description | No | Project description |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 transparency. It discloses that calling this tool creates not just the project but also initial elements, tasks, and agent instructions, which is useful side-effect information beyond what the name alone implies. It does not mention permissions, error behavior, or whether the operation is idempotent, but the core side effects are clearly surfaced.
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 compact and front-loaded: the primary action 'Create a new project' appears first, followed by the key side effects in a second sentence. 'sensible templates' is slightly vague, but the overall structure is efficient with no redundant filler.
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 moderate complexity with four parameters and no output schema, and the description conveys the essential creation and scaffolding behavior. However, it does not explain what the function returns, how duplicate titles or conflicts are handled, or how to choose between this and the sibling create_project. For an agent to invoke it correctly in context, some of that guidance would be helpful.
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 75%, so the schema already documents title, template, and description. The description adds little parameter-level meaning; 'chosen category' loosely references the template enum but does not enumerate values or explain tags. This meets the baseline for high schema coverage but does not compensate beyond 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 clearly states the tool creates a new project, and goes further by explaining it also sets up initial elements, tasks, and agent instructions from a chosen category. This distinguishes it from the sibling create_project tool, which presumably creates a plain project without scaffolding.
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 implies this tool is for creating a project with template-based scaffolding, but it does not explicitly state when to use it versus create_project or when not to use it. No alternative tools or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources (elements, knowledge, tasks, datasets, snapshots), but a few pairs blur boundaries: create_project/init_project both create projects, and pin_knowledge/set_knowledge_relevance both mark importance for future agents. The descriptions help separate them, but misselection is possible without careful reading.
Tool names consistently use snake_case verb_noun and have solid list_/get_/search_ conventions. However creation verbs are inconsistent (add_element vs create_entry vs save_dataset vs init_project), and deletion mixes delete_entry/delete_file with remove_element, making the naming pattern less predictable than it could be.
48 tools is well above the typical well-scoped range, and the set includes many lifecycle variants (create/init/save/add, delete/remove, update/set) that inflate the count. While the server covers a broad domain, the sheer number makes it heavy and harder for an agent to navigate.
The core surfaces (projects, elements, knowledge, timeline, tasks, chats, datasets, snapshots, files) have solid create/read/update coverage, with search and session-handoff tools. Notable gaps exist: read_file references a download path for binary files that no tool provides, and there is no get_entry or delete/archive for projects, datasets, snapshots, or chat sessions.