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ndjson-local-log-triage-mcp

ndjson-local-log-triage-mcp

by vola-trebla
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

discover_log_schema

Infer log format and type schemas from file samples, including key polymorphism and timestamp regex patterns.

Instructions

Analyze a log file to infer format and type schemas, including key type polymorphism and regex patterns for timestamps.

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": {
      "file_path": "<file_path>"
    },
    "name": "discover_log_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathYesAbsolute path to the log file
sample_sizeNoNumber of lines to sample for schema detection

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.4/5.0
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. It reveals the tool analyzes a file and produces schema info, but does not disclose whether it modifies anything, what the return format is, or any limitations. This is a significant gap for a tool that reads files and infers structures.

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, well-structured sentence with no fluff or repetition. Every phrase contributes useful information about the tool's function.

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 there is no output schema and no annotations, the description should explain what the result looks like, how sample_size affects behavior, or any other operational details. It only states the high-level purpose, leaving a knowledgeable agent uncertain about the tool's output and constraints.

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 description coverage is 100%, and the input schema already documents both file_path and sample_size. The description adds no additional parameter-specific meaning beyond what the schema provides, so the baseline of 3 applies.

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 verb 'Analyze' and the resource 'log file', with specific output details: infer format and type schemas, key type polymorphism, and regex patterns for timestamps. This distinguishes it from sibling tools like query_log_pattern or detect_error_anomalies.

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 purpose implies this should be used when you need to understand the structure of a log file, but there is no explicit when-to-use guidance or mention of alternatives. Siblings exist but are not referenced, so usage context is implied rather than stated.

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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