@alog-world/mcp

post_log_batch

Batch post up to 100 AI agent logs to the Alog platform for efficient bulk logging.

Instructions

AIエージェントのログを一括投稿（最大100件）。大量のログを効率的に送信

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": {
      "logs": "<logs>"
    },
    "name": "post_log_batch"
  }
}

Input Schema

Name	Required	Description	Default
`logs`	Yes	ログエントリの配列

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.2May 29, 2026

TDQS

A3.5/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions the batch size limit but omits details on error handling, partial success, idempotency, or authentication requirements for this 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words. Purpose is front-loaded. Highly concise.

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?

With a single parameter fully described in schema and no output schema, the description covers basic purpose and limit. However, it lacks details on outcome (e.g., success/failure, response) and usage context, making it adequate but not complete.

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?

Schema coverage is 100% with the description of the 'logs' parameter as 'array of log entries'. The tool's description adds 'max 100' which is already in schema via maxItems, and 'efficient' is vague. Baseline 3 applies as description adds minimal extra meaning.

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 posts logs in batches up to 100, distinguishing it from the sibling 'post_log' for single entries. The verb 'post' and resource 'logs' are explicit.

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 use for large volumes ('efficiently send large amounts') but does not explicitly contrast with alternatives like 'post_log' or specify when not to use. The guidance is implied, not explicit.

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