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agent-gantt

agent-gantt

by TobiasCoding
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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add_dependency

Adds a predecessor dependency between two tasks in a project plan, rejecting cycles and cross-project edges to keep schedules valid.

Instructions

Add predecessor; rejects cycles and cross-project edges.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>",
      "depends_on_id": "<depends_on_id>"
    },
    "name": "add_dependency"
  }
}

Input Schema

NameRequiredDescriptionDefault
actorNo
reasonNo
task_idYes
depends_on_idYes
idempotency_keyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses important rejection rules (cycles and cross-project edges), but omits mutation side effects, permissions, idempotency behavior, and return semantics for a five-parameter write 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?

The description is a single front-loaded sentence with no wasted words. Its brevity is partly under-specification, but from a conciseness perspective it is efficient and easy to parse.

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 mutation tool with five parameters, no annotations, and no output schema, the description is too thin. It confirms validation behavior but leaves parameter semantics, usage context, and mutation effects incomplete.

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

Parameters1/5

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

Schema description coverage is 0% across five parameters, and the description does not explain the roles of task_id, depends_on_id, actor, reason, or idempotency_key. It leaves the direction of the dependency and the purpose of supporting parameters entirely undocumented.

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 states a specific verb ('Add') and resource ('predecessor'), making the tool's core action clear. It does not explicitly differentiate from sibling tools, but no sibling appears to handle dependency creation, so the purpose is still highly identifiable.

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?

The description implies when the tool is valid by stating it rejects cycles and cross-project edges, which tells the agent when the operation will fail. However, it gives no guidance on prerequisites, alternatives, or when to prefer this tool over others.

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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