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smart-coding-mcp

smart-coding-mcp

by cbuntingde
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

set_convention

Append a new coding convention to the AGENTS.md file and receive the line number where it was added.

Instructions

Append a new convention to AGENTS.md and return its line number.

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": {
      "text": "<text>"
    },
    "name": "set_convention"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesA new convention to append. Plain English, ~1-3 sentences. Don't repeat existing conventions; cite the lesson id if relevant.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It states that the tool appends (non-destructive write) to AGENTS.md and returns a line number. However, it does not explain side effects (e.g., whether duplicate conventions are allowed), permission requirements, or potential failures, which limits transparency to a basic level.

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, short sentence that front-loads the key action ('Append a new convention to AGENTS.md') and immediate result ('return its line number'). Every word is necessary, with no filler or repetition.

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?

Given a simple tool with one parameter and an existing output schema, the description adequately covers the action, affected resource, and return value. It specifies that the operation is an append and provides the output type (line number), which is sufficient for context.

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?

The input schema for 'text' is well-described with length constraints and usage guidance (plain English, 1-3 sentences, cite lesson id). The tool description adds no additional meaning beyond 'new convention', so it does not improve parameter understanding. Baseline 3 applies because schema coverage is 100%.

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 uses the specific verb 'Append' and clearly identifies the resource as 'AGENTS.md' and the action of adding a 'new convention'. It also immediately states the return value (line number), making the tool's purpose distinct from siblings like get_conventions (read) or record_lesson (different action).

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives such as get_conventions or record_lesson. No context is given for appropriate use cases or when to avoid using it, leaving the agent to infer usage solely from the tool name and siblings.

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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