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agent-gantt

agent-gantt

by TobiasCoding
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_projects

Retrieve all project IDs and names from your agent-gantt workspace. Use limit and cursor to page through results, then request full project details when needed.

Instructions

List project IDs/names; detail on demand.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_projects"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
cursorNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.9/5.0
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 behavioral burden. It discloses that only IDs/names are returned and that details are fetched elsewhere, but says nothing about read-only status, pagination, default result size, or authentication, leaving significant gaps for a cursor-paginated list operation.

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?

One short sentence, front-loaded with the core action and followed immediately by the routing hint. It is efficient, though arguably too terse given the undocumented pagination parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list tool with two optional parameters including a pagination cursor and no annotations or output schema, the description is too thin. It omits how to page through results, what the default limit is, and what the returned ID/name objects look like, so an agent lacks enough context to call it robustly.

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 never mentions 'limit' or 'cursor'. The parameter names are somewhat self-explanatory, but the description adds no semantics about result-size caps or cursor-based pagination, failing to compensate for the undocumented schema.

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?

States a specific verb ('List') and resource ('project IDs/names'), and the 'detail on demand' clause hints that fuller project information lives in another tool. It is clear enough to distinguish from create_project, though it does not explicitly name project_view or get_detail as the detail alternatives.

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

Usage Guidelines3/5

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

'detail on demand' implies this tool is for lightweight discovery and that a different tool should be used when details are needed, giving implicit usage context. However, no alternative is named and no when-not condition is stated, so the agent must infer the routing.

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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