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Ikalus1988

MisakaNet

by Ikalus1988
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Python

misakanet_get_lesson

Fetch a specific debugging lesson by ID or repository path to get its markdown content for failure triage and release auditing.

Instructions

Fetch one public MisakaNet lesson by repository path or lesson ID. Use after misakanet_search returns a promising result, or when a lesson is explicitly referenced; do not use it for broad discovery. Input semantics: provide either path or id. Output schema: JSON with path and markdown content, truncated to 5000 characters for MCP context. Error cases: missing path/id or lesson not found. Side effects: none. Auth: none. Rate limits: local stdio process only; fetch one lesson per call when possible.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoLesson ID, usually the filename without .md, for example auto-merge-ci-pipeline.
pathNoLesson path relative to the repository, for example lessons/core/auto-merge-ci-pipeline.md.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.14.0
    • changedInput schema / properties / id / description
      Previous value: -"Lesson ID (filename without .md, e.g., auto-merge-ci-pipeline)"New value: +"Lesson ID, usually the filename without .md, for example auto-merge-ci-pipeline."
    • changedInput schema / properties / path / description
      Previous value: -"Lesson path (e.g., lessons/core/auto-merge-ci-pipeline.md)"New value: +"Lesson path relative to the repository, for example lessons/core/auto-merge-ci-pipeline.md."
  2. Changed1 schema field changedv2.12.4
    • changedInput schema / properties / id / description
      Previous value: -"Lesson ID (filename without .md)"New value: +"Lesson ID (filename without .md, e.g., auto-merge-ci-pipeline)"
  3. First observedv2.12.3

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It covers side effects ('none'), authentication ('none'), rate limits, error cases, and output truncation to 5000 characters, giving the agent a complete behavioral picture.

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 front-loaded with the core purpose, followed by compact, information-dense sections for usage, input, output, errors, side effects, auth, and rate limits. Every sentence earns its place without unnecessary filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without an output schema, the description explains the return value format and truncation behavior. It also covers error cases, side effects, auth, and rate limits, making it fully actionable for an agent selecting and invoking the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful relational semantics by stating 'provide either path or id,' which clarifies that the parameters are alternatives rather than independent optional fields. This is valuable beyond the individual parameter descriptions.

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 states a specific verb and resource: 'Fetch one public MisakaNet lesson by repository path or lesson ID.' It clearly distinguishes from siblings like misakanet_search, which is for discovery, and misakanet_write_lesson, which is for writing.

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 tells the agent when to use this tool: after misakanet_search returns a promising result, or when a lesson is explicitly referenced. It also states a clear exclusion: 'do not use it for broad discovery,' which prevents confusion with search 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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