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compress_image_webp

Convert images to WebP, optimize alpha channels, strip EXIF tags, and cut file weight by up to 80%.

Instructions

Serverless WebP image compressor: optimizes alpha channels, strips privacy-invasive EXIF tags, and cuts image weight by 80%. (0.025 USDC on Base L2)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesInput parameters or JSON string payload for the tool execution
paymentSignatureNoBase L2 USDC micropayment signature or transaction hash for x402 settlement

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden and does it well: it discloses the payment requirement (0.025 USDC on Base L2) — critical for the agent to know before invoking — plus the privacy behavior (EXIF stripping) and expected performance (80% weight reduction). It does not state the return format or whether the input image is preserved, but the disclosed traits substantially exceed what the schema alone conveys.

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?

A single, front-loaded sentence with the core function stated first, followed by concrete outcomes and a parenthetical cost note. No fluff or repetition of the tool name. The parenthetical about cost slightly interrupts the flow but earns its place by disclosing a mandatory payment. Efficient and well-ordered.

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?

Core purpose, cost, and privacy behavior are covered, but with no output schema, the return value format is undocumented — an agent doesn't know if it receives a URL, base64 data, or a file reference. Input format expectations for the payload are also unspecified. For a paid image-processing tool, these gaps are meaningful but not fatal given the strong purpose statement.

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 parameters (payload and paymentSignature) are documented in the schema. The description adds no parameter-level detail — it doesn't clarify what the payload should contain (encoded image data? a URL?) or the expected format of the payment signature. At full schema coverage, baseline 3 is appropriate; the description neither helps nor hurts parameter understanding.

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?

States a specific verb (compress) + resource (image to WebP) with three concrete outcomes: alpha channel optimization, EXIF stripping, and 80% weight reduction. This distinguishes it from siblings like resize_image_preserve_aspect (resizing, not compressing) and extract_exif_geolocation (extracts rather than strips EXIF). The purpose is immediately unambiguous.

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 purpose implies usage context (compress images to WebP while stripping EXIF), but there is no explicit when-to-use/when-not-to-use guidance and no mention of alternatives. An agent facing siblings like resize_image_preserve_aspect or multimodal_image_exif_redactor gets no routing hints from the description itself, though the function's specificity makes the primary use case inferable.

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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