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smart-coding-mcp

smart-coding-mcp

by cbuntingde
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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mark_lesson_used

Increments the usage count of a lesson when you apply it in practice, tracking how often each lesson is used.

Instructions

Bump times_used on a lesson — call when you actually applied it.

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": {
      "lesson_id": "<lesson_id>"
    },
    "name": "mark_lesson_used"
  }
}

Input Schema

NameRequiredDescriptionDefault
lesson_idYesID of the lesson the orchestrator applied.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions the action (bump field) but does not disclose return values, error conditions, or permissions. For a simple increment operation, this is adequate but lacks some detail.

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 sentence, front-loaded with the action. No extraneous words; every part serves a purpose.

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

Completeness4/5

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

For a simple tool with one parameter and an output schema, the description is largely complete. It covers the purpose and usage. Minor gap: no mention of what the response contains.

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% with one well-described parameter. The description repeats the schema's meaning ('ID of the lesson') without adding significant new information. Baseline 3 is appropriate.

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 action (bump times_used) and the resource (a lesson), with a specific verb and resource. It distinguishes itself from siblings like record_lesson by specifying the condition 'when you actually applied it.'

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?

The description explicitly says 'call when you actually applied it,' providing clear context for use. It does not mention when not to use or alternatives, but the directive is sufficient for the intended use case.

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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