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sdc-mapper-mcp

sdc-mapper-mcp

Official
by SemanticDataCharter
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

log_summary

Summarize audit log activity over a chosen day window, showing calls, outcomes, value classes, per-target exceptional values, and active models and mapping files.

Instructions

Read the log back over a window: calls, outcomes, value classes and Exceptional Value classes per target, and the models and mapping files in use.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "log_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.1

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. "Read the log back" implies a non-destructive read and it lists the summary content, but it omits permissions, rate limits, return format, and other operational details.

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 front-loaded sentence with no wasted words. The colon-delimited list efficiently enumerates the summary dimensions.

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?

For a simple one-parameter read tool, the description covers the purpose and the categories returned. However, with no output schema, no annotations, and 0% schema description coverage, it should do more to explain the days parameter and the return structure.

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?

The sole parameter is days, and the schema provides no description for it. The description mentions "over a window" but does not explain that days controls the window, nor does it mention the default of 7 or the minimum of 0.

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 gives a specific verb and resource: "Read the log back over a window," then lists the summary dimensions returned. It is clear what the tool does, but it does not explicitly distinguish itself from siblings such as verify_log or list_targets.

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?

There is no explicit guidance on when to use this tool versus alternatives. The description implies it summarizes a log window, but it does not name when-not-to-use cases or point to sibling tools.

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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