Take a screenshot of the current screen and show the image in the user interface.
Capture the current screen with flameshot to ~/Pictures and return it to the client as base64 image data (compressed for relay delivery when large). The AI model only receives a success confirmation — the image is delivered to the user interface separately.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the operation is read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail: it uses flameshot, saves to ~/Pictures, compresses for relay, and informs the AI model only of success while delivering image data separately. This goes beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no filler. The core action and delivery model are front-loaded, and every clause adds useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with no output schema, the description covers what is captured, how it is delivered, and what the AI model will perceive. Nothing essential is missing for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the input schema is empty, so there is no parameter ambiguity to resolve. The description correctly implies no inputs are required, meeting the baseline for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb (capture), resource (current screen), and mechanism (flameshot to ~/Pictures), plus a clear delivery channel (base64 to client, separate from model confirmation). It is clearly distinct from sibling operations like webcam_snapshot or display_record.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool is for capturing the current screen, but it does not explicitly state when to choose this over alternatives such as get_snapshot or display_record. It provides functional context rather than explicit routing or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.