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g-hyeong

Logging Advisor MCP

by g-hyeong

suggest_improvements

Generate a logging improvement roadmap with actionable, prioritized code suggestions to fix issues like console.log overuse and missing error context.

Instructions

Generate logging improvement roadmap and specific modification suggestions

When used: Automatically executed after analyze_logging completion or when direct improvement suggestions are needed

What it provides:

  • Immediately applicable Quick Wins (1-2 hours)

  • Phased migration plan (prevents Big Bang approach)

  • Line-by-line precise modification code

  • ROI-based prioritization (cost vs. benefit)

  • Implementation difficulty and estimated time required

  • Required library/configuration guidance

Improvement patterns:

  • console.log → structured logger (winston, pino)

  • Error ignoring → complete context preservation

  • Synchronous logging → asynchronous performance optimization

  • Sensitive data exposure → complete removal/masking

  • Untraceable → correlation ID addition

Operational safety: Preserve existing logic, incremental application, rollback plan

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoImprovement focus areaall
languageYesProgramming language - provides language-specific improvement patterns
complexityNoImprovement complexity - quick: 1-2 hours, standard: half day, comprehensive: full migrationstandard
currentIssuesNoCurrent logging issues identified (optional) - e.g., ["console.log overuse", "missing error context", "sensitive data exposure"]

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.1

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does describe operational safety ('Preserve existing logic, incremental application, rollback plan'), which is useful context about the generated output. However, it doesn't disclose whether this is a read-only operation, whether it modifies files, or its execution model. The safety notes are about the suggestions, not the tool's own behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is heavily formatted with headers and bullet lists, making it longer than necessary. The front-loaded purpose is clear, but the extensive enumeration of improvement patterns and benefits could be distilled. It's structured but somewhat bloated.

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?

Given no annotations and no output schema, the description needs to compensate. It describes what the tool provides but omits critical behavioral details like whether it's read-only, how it interacts with the analysis session, or error handling. It covers the 'what' well but leaves gaps in the 'how'.

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%, so the baseline is 3. The description mentions 'language-specific improvement patterns' and the focus/complexity concepts loosely map to the schema, but adds no syntax or format details beyond what the structured schema already provides.

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 states a specific verb+resource ('Generate logging improvement roadmap and specific modification suggestions'), which is clear enough. However, it doesn't differentiate itself from the sibling 'analyze_logging' beyond saying it's 'automatically executed after analyze_logging completion'. A stronger description would directly contrast the two tools' scopes.

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

Usage Guidelines4/5

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

Provides clear context for when to use: 'Automatically executed after analyze_logging completion or when direct improvement suggestions are needed.' It names the prerequisite sibling tool, which helps routing. It lacks explicit when-not-to-use guidance or a direct alternative, but the trigger conditions are adequately specified.

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