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agy_computer_use.mcp_server

agy_computer_use.mcp_server

by orakulzero
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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cu_replay_macro

Replay recorded desktop automation trajectories with self-healing UIA selector fallback to restore workflows when UI elements change; optionally run dry-run without OS dispatch.

Instructions

Replay recorded trajectory with self-healing UIA selector fallback.

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": {
      "trajectory": "<trajectory>"
    },
    "name": "cu_replay_macro"
  }
}

Input Schema

NameRequiredDescriptionDefault
dry_runNoDry-run execution without OS dispatch.
trajectoryYesExported trajectory dictionary.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It discloses one important trait, self-healing selector fallback, but does not say whether replay dispatches real OS actions, what happens on selector failure, whether operations are reversible, or what permissions are needed.

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 definition is a single front-loaded sentence with no wasted words. The core action and fallback behavior are stated immediately.

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 macro-replay tool with a nested trajectory object, no annotations, and no output schema, the description is too thin. It should explain side effects, failure behavior, and the significance of dry_run beyond what the schema briefly notes.

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 the trajectory and dry_run parameters are already documented. The description reinforces that trajectory is replayed but adds no syntax, structure, or constraints beyond the schema. Baseline 3 is appropriate.

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 gives a specific verb and resource: replaying a recorded trajectory. It adds a distinctive behavioral detail, self-healing UIA selector fallback, which separates it from low-level siblings like cu_click and cu_type. It does not explicitly name alternatives, so it falls 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?

There is no guidance on when to use this tool versus capture, dispatch, or lower-level action tools. The description does not state prerequisites, when-not conditions, or how dry_run changes usage decisions.

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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