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superpos-mcp

superpos-mcp

Official
by Superpos-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

superpos_get_issue

Retrieve a single issue including its type, linked tasks, dependencies, approvals, and allowed state transitions for workflow management.

Instructions

Get a single issue with its type, linked tasks, dependencies, approvals, and allowed_transitions (the states it can move to next).

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": {
      "issue_id": "<issue_id>"
    },
    "name": "superpos_get_issue"
  }
}

Input Schema

NameRequiredDescriptionDefault
hive_idNo
issue_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It indicates a read operation and lists returned fields, but lacks details on error handling, authentication requirements, or behavior in edge cases. For a simple get tool, this is minimally adequate.

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 a single sentence that is front-loaded and efficient. It clearly states the action and lists key outputs without wasted words.

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

Completeness3/5

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

The description lists the returned data, and an output schema exists to define the return structure. However, it lacks parameter documentation and usage context. For a simple tool, it is adequate but not fully complete.

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 does not explain the parameters (hive_id, issue_id). It mentions 'single issue' but does not clarify which parameter identifies it or the role of hive_id. This leaves the agent with insufficient guidance on parameter usage.

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

Purpose5/5

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

The description clearly states 'Get a single issue' and enumerates the returned data (type, linked tasks, dependencies, approvals, allowed_transitions). This specific verb and resource distinguishes it from sibling tools like superpos_list_issues.

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 usage when a single issue's details are needed, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., list_issues for multiple issues) or when not to use it.

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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