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Systemonomic

Systemonomic

by TonyC23
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_suggestions

View AI-generated task proposals awaiting approval for a specific project. This tool helps review pending suggestions before implementation.

Instructions

List all pending task suggestions for a project.

Suggestions are AI-generated task proposals that haven't been accepted yet.

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": {
      "project_id": "<project_id>"
    },
    "name": "list_suggestions"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.2/5.0
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 burden of behavioral disclosure. It states this is a listing operation for 'pending' suggestions, implying it's read-only and non-destructive, but doesn't address permissions, rate limits, pagination, or what 'pending' means operationally. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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 appropriately sized and front-loaded. The first sentence directly states the tool's purpose, and the second sentence adds necessary clarification without redundancy. Every sentence earns its place, making it efficient and well-structured.

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 the tool's low complexity (one parameter, no nested objects) and the presence of an output schema (which handles return values), the description is mostly complete. It covers the core purpose and clarifies what 'suggestions' are, but lacks usage guidelines and behavioral details that would be helpful despite the output schema.

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

Parameters3/5

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

The description adds minimal semantic context beyond the input schema. It mentions 'for a project,' which aligns with the 'project_id' parameter, but with 0% schema description coverage and only one parameter, the baseline is 4. However, it doesn't explain what a 'project_id' is, its format, or where to find it, so it doesn't fully compensate for the schema gap, warranting a score of 3.

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 tool's purpose: 'List all pending task suggestions for a project' with the clarifying sentence 'Suggestions are AI-generated task proposals that haven't been accepted yet.' This provides a specific verb ('List'), resource ('pending task suggestions'), and scope ('for a project'), though it doesn't explicitly differentiate from sibling tools like 'list_tasks' or 'list_atss_runs'.

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. It doesn't mention sibling tools like 'list_tasks' (for accepted tasks) or 'derive_task_suggestions' (for generating new suggestions), nor does it specify prerequisites or exclusions. The context is implied but not explicit.

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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