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smart-coding-mcp

smart-coding-mcp

by cbuntingde
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

record_lesson

Save coding lessons with category, summary, evidence, and tags. Persist learned insights to avoid repeating mistakes and maintain conventions.

Instructions

Record a lesson into the persistent store. Returns the new lesson.

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": {
      "category": "<category>",
      "summary": "<summary>"
    },
    "name": "record_lesson"
  }
}

Input Schema

NameRequiredDescriptionDefault
tagsNoComma-separated tags (no spaces within tags). e.g. 'python,async,timeout'.
summaryYesOne-line atomic takeaway. Prefers the form 'In <context>, do/avoid X because Y'. Target: ~80 chars.
categoryYesLesson category: bug, style, perf, convention, debt, risky, win.
evidenceNoOptional file:line or short quote that triggered the lesson.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions persistence and return value but does not disclose side effects (e.g., overwrite behavior, permissions, rate limits) or what happens with duplicate keys.

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 extremely concise with two sentences, front-loaded with the purpose. No unnecessary words.

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?

The description mentions the return value (implied output schema) and covers the basic action. However, given the tool has 4 parameters and no annotations, it lacks details on error handling, uniqueness, or concurrency. Could be more complete.

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 baseline is 3. The description does not add additional meaning beyond the schema; it only restates the tool's purpose. Parameter details are adequately covered in the schema.

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 ('Record a lesson') and the return value ('Returns the new lesson'). It distinguishes from sibling tools like 'recall_lessons' (retrieve) and 'recent_lessons' (list).

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 description implies usage when saving a new lesson, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or when not to use it.

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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