Skip to main content
Glama

list_projects

View all project spaces to see memory distribution, recent activity, and key tags for managing knowledge organization across your workspace.

Instructions

List all project spaces with memory counts, latest activity, and top tags. Shows how knowledge is distributed across projects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it describes what information is returned, it doesn't address important behavioral aspects like whether this is a read-only operation, if there are rate limits, how results are sorted or paginated, or what permissions might be required. The description only covers output content, not operational behavior.

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?

The description is perfectly concise with two sentences that each add value. The first sentence specifies exactly what the tool returns, and the second provides higher-level context about knowledge distribution. There's no wasted language or redundancy.

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?

Given that the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description provides good contextual completeness. It explains what information is returned and the purpose of that information. The main gap is lack of behavioral context, but with an output schema handling return values, the description focuses appropriately on the 'why' rather than the 'what' of outputs.

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?

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on what the tool returns, which is valuable context for a parameterless operation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and resource 'project spaces' with specific details about what information is included (memory counts, latest activity, top tags). It distinguishes the tool's purpose well, though it doesn't explicitly differentiate from potential sibling tools like 'project_status' or 'knowledge_stats' that might provide related information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'project_status', 'knowledge_stats', and 'list_sources' available, there's no indication of when this specific listing tool is appropriate versus other project or knowledge-related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/besslframework-stack/project-tessera'

If you have feedback or need assistance with the MCP directory API, please join our Discord server