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pedra-ai

Pedra MCP Server

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Edit via prompt

pedra_edit_via_prompt

Edit images with natural-language prompts. Provide a photo and a description like 'paint walls green' to receive the edited image.

Instructions

Edit an image from a natural-language instruction (e.g. "paint the walls sage green"). Returns the edited image URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesNatural-language description of the edit to apply.
imageUrlYesSource image: a public https:// URL, a data: URI, or an absolute path to a local image file (the file is read and inlined automatically).
Behavior3/5

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

The description notes the return value (edited image URL) and implies a mutation (edit). Annotations already indicate readOnlyHint=false and destructiveHint=false, so the description adds minimal behavioral context. No contradictions.

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?

A single, well-structured sentence that includes an example. Every word serves a purpose; no fluff.

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

Completeness4/5

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

For a simple two-parameter tool with no output schema, the description adequately explains input and output. It could mention constraints (e.g., supported edits or image format) but is sufficient for the tool's complexity.

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 coverage is 100%, so parameters are already well described in the schema. The description repeats some info (prompt example) but does not add meaning beyond the schema.

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 states a specific verb ('Edit'), a resource ('image'), and a mechanism ('natural-language instruction'), with a concrete example. It clearly distinguishes from sibling tools like pedra_remove_object (targeted removal) and pedra_blur (specific effect) by conveying a general-purpose editing capability.

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?

No guidance on when to use this tool versus alternatives. Siblings like pedra_enhance, pedra_remove_object, or pedra_sky_blue offer more specific operations, but the description does not mention these or provide exclusion criteria.

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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