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io.github.flujo-app/mcp-virtual-computer

io.github.flujo-app/mcp-virtual-computer

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by flujo-app
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edit_file

Replace exact text in UTF-8 files and visually verify the selection, overwrite, and save.

Instructions

Replace exact UTF-8 text and show it being selected, overwritten, and saved.

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": {
      "path": "<path>",
      "old_text": "<old_text>",
      "new_text": "<new_text>"
    },
    "name": "edit_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesUTF-8 text file path, absolute or relative to /workspace.
new_textYesReplacement UTF-8 text.
old_textYesExact text to select and replace; include context if ambiguous.
replace_allNoReplace every exact match instead of requiring one match.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.4

TDQS

B3.3/5.0
Behavior2/5

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 reveals that the replacement will be visually shown, but it does not explain matching failure behavior, whether changes are reversible, permission requirements, or what happens when old_text is ambiguous or absent. 'Replace' is essentially the operation implied by the tool name.

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 efficient sentence that front-loads the core action ('Replace exact UTF-8 text') and adds a concise behavioral detail about the visual selection and save process. No unnecessary padding is present.

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 tool is moderately simple and the schema thoroughly documents parameters, but there is no output schema and no annotation context. The description does not cover failure modes, return values, or how the tool behaves when old_text is not found, leaving some important operational context unstated.

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 the schema already documents all parameters including path, old_text, new_text, and replace_all. The description adds no additional parameter semantics beyond the schema, so the baseline score of 3 applies.

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 identifies the action ('Replace exact UTF-8 text') and the resource (a UTF-8 text file). It distinguishes this from more general file writing by emphasizing exact text replacement, though it does not explicitly name sibling alternatives.

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 the tool is for targeted in-place text replacement, which suggests when to use it over write_file, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. The guidance is implicit rather than direct.

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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