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by rnd-pro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

ai-tools__edit_code

Apply specified editing instructions to the given code. Provide the code and the modifications to get the corrected version.

Instructions

[AI Code Analysis] Edits the given code based on instructions

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": {
      "code": "<code>",
      "instructions": "<instructions>"
    },
    "name": "ai-tools__edit_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesCode to edit
instructionsYesEditing instructions

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full responsibility for disclosing behavior. It only states that code is edited based on instructions, but does not clarify whether the tool returns updated code, modifies files, applies side effects, or handles partial edits. This is a minimal disclosure rather than a transparent one.

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

Conciseness4/5

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

The description is a single concise sentence with no obvious filler, and it front-loads the core operation. However, it is so terse that it provides limited practical guidance, which keeps it from a 5.

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

Completeness2/5

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

For a simple two-parameter tool, the description is minimal but leaves out return-value behavior and sibling differentiation. No output schema or annotations exist to fill those gaps, so the description is incomplete for selecting and using the tool confidently.

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 both code and instructions are already documented in the input schema. The description adds no additional parameter meaning beyond restating the schema. Baseline 3 is appropriate because the schema carries the semantic weight.

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 clearly states a specific action—editing code based on instructions—using a definite verb and target resource. It does not explicitly differentiate from the sibling tool ai-tools__fix_code, which also involves modifying code, so it stops short of a 5.

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 offers no guidance on when to use this tool versus alternatives like fix_code, explain_code, or review_code. It does not mention any exclusions, prerequisites, or preferred contexts, leaving the agent to infer appropriate usage.

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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