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by agentkitai

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Python

Remote

review_connection

Approve or reject pending knowledge graph connections. Rejected patterns are tracked to prevent re-suggestion.

Instructions

Approve or reject a pending knowledge graph connection. USE THIS AFTER: getting a review_digest and the user has decided which connections to keep or discard. Rejected patterns are tracked so the same connection won't be re-suggested.

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": {
      "relationship_id": "<relationship_id>",
      "action": "<action>"
    },
    "name": "review_connection"
  }
}

Input Schema

Name	Required	Description	Default
`action`	Yes
`reason`	No
`relationship_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jun 24, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description must carry the behavioral burden. It discloses that rejected patterns are tracked to avoid re-suggestion, but does not detail whether it is read-only or destructive, authentication needs, rate limits, or error conditions. The description is partially informative but not comprehensive.

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 concise with two sentences, no redundancy, and front-loads the purpose. However, it could benefit from a slightly more structured format, such as listing parameters or providing an example.

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?

Given the lack of parameter descriptions, no annotations, and an output schema that is not described, the description leaves gaps. It relies on familiarity with the workflow involving review_digest and does not fully explain the inputs or outputs for autonomous agent use.

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%, yet the description does not explain the 'action' values or the 'reason' parameter explicitly. While 'approve or reject' implies possible actions, it does not specify valid values or the role of 'reason'. This is insufficient for an agent to construct correct invocations.

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 the tool approves or rejects a pending knowledge graph connection, using specific verbs and identifying the resource. It distinguishes from sibling tools like review_digest, which generates the list of connections.

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

Usage Guidelines5/5

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

The description explicitly directs to use this tool after getting a review_digest and when the user has decided, providing clear when-to-use guidance. It also mentions that rejected patterns are tracked, indicating a learning mechanism.

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