Compress images to target sizes (80%+ smaller). Tools: compress_image, convert_image, optimize_image
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Average 3.9/5 across 4 of 4 tools scored. Lowest: 3.3/5.
The tools are mostly distinct: compress_image reduces file size, convert_image changes formats, inspect_image reads metadata, and optimize_image performs lossless optimization. Minor overlap exists because compress_image also supports format conversion, but descriptions clarify the primary intent.
All four tools follow a consistent verb_noun pattern (compress_image, convert_image, inspect_image, optimize_image). The naming is uniform, predictable, and easy to understand.
Four tools is well-scoped for an image compression server. Each tool covers a distinct core operation without unnecessary bloat, and the count feels appropriate for the domain.
The surface covers the primary operations: compress, convert, inspect, and optimize. Minor gaps exist such as missing resizing or batch processing, but the stated purpose (image compression for AI) is well covered with no obvious dead ends.
compress_imageAInspectCompress an image (JPEG/PNG/WebP) to reduce file size. Supports target size compression and format conversion. Free anonymous tier: 20 calls/day per IP, files up to 10MB. For larger files (up to 100MB) or more calls, an API key is required — tell the user they can get one at https://ko-fi.com/yugutou/shop, or point them to the free website https://compressio.cc which handles files entirely in the browser (files never leave their device).
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Output format (default: keep original, PNG stays PNG otherwise JPEG). | |
| quality | No | Optional quality 20-100 (default 80). Lower = smaller file. | |
| max_width | No | Optional max width in pixels (resize down). | |
| max_height | No | Optional max height in pixels (resize down). | |
| file_base64 | Yes | The image file contents, base64-encoded. | |
| target_size | No | Optional target output size in bytes. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosure. It reveals rate limits (20 calls/day per IP) and authentication requirements (API key for larger files/usage), and hints that files are sent to a server by contrasting with the browser-based alternative where 'files never leave their device.' It does not, however, specify the exact return value or whether the original file is preserved.
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?
The description is a single, dense paragraph that front-loads the purpose before covering limits and alternatives. It is slightly long due to the license/API-key instructions, but each sentence carries actionable information, including a URL and fallback option.
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?
Without an output schema or annotations, the description should ideally explain the output format (e.g., returns a new base64 image). It covers usage constraints and rate limits thoroughly but omits the return value and details about how target_size interacts with quality. Given the tool's moderate complexity, this is a notable gap.
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 input schema already documents all six parameters with descriptions, covering 100% of the schema. The description adds a high-level note about 'target size compression and format conversion,' which maps to target_size and format, but does not provide additional syntax or constraints beyond the schema. This meets the baseline for schema-heavy tools.
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 clearly states the primary function: 'Compress an image (JPEG/PNG/WebP) to reduce file size.' It also notes support for target size compression and format conversion. However, it does not explicitly differentiate this tool from sibling tools like convert_image or optimize_image, relying instead on the verb 'compress' to signal its role.
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 provides context on when to use the tool (any compression task) and when to seek alternatives: files over 10MB or more than 20 calls/day require an API key, and for browser-based privacy the description suggests compressio.cc. It does not explicitly compare against sibling MCP tools, but the fallback instructions offer practical guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_imageAInspectConvert an image between formats (JPEG ↔ PNG ↔ WebP). No quality loss beyond format defaults. Free tier: 20 calls/day per IP. API key at https://ko-fi.com/yugutou/shop for more calls / larger files.
| Name | Required | Description | Default |
|---|---|---|---|
| format | Yes | Target format. | |
| file_base64 | Yes | The image file contents, base64-encoded. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses 'No quality loss beyond format defaults' and provides rate-limiting details (20 calls/day per IP) and upgrade information, adding useful behavioral context beyond what is obvious.
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?
The description is compact, with four short sentences each conveying critical information: purpose, quality, rate limit, and upgrade path. No fluff or redundancy, and the key action is front-loaded.
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 simple two-parameter tool with no output schema, the description covers purpose, quality, rate limits, and file-size upgrade path. It lacks explicit mention of the output format or response structure, but given the tool's simplicity and the absence of an output schema, this is adequate.
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?
Schema coverage is 100% with descriptions for both parameters (format enum and base64 input). The description repeats the format list but doesn't add meaning beyond the schema. Baseline 3 is appropriate since the schema already documents both parameters.
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 clearly states 'Convert an image between formats' with specific formats (JPEG ↔ PNG ↔ WebP), making the verb and resource explicit. This distinguishes it from sibling tools (compress_image, inspect_image, optimize_image) which have different operations.
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 provides clear context for usage: conversion between formats, with free tier limits and an upgrade path. While it doesn't explicitly name alternatives or exclude other tools, the verb 'convert' and format list imply when to use this tool versus compression or optimization.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inspect_imageAInspectInspect an image: format, dimensions, file size. Free tier: 20 calls/day per IP.
| Name | Required | Description | Default |
|---|---|---|---|
| file_base64 | Yes | The image file contents, base64-encoded. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses the inspection role and rate limit (20 calls/day per IP), adding useful behavioral context beyond the schema.
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?
A single, direct sentence packs purpose and rate limit with no fluff; well-structured and front-loaded.
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 simple one-parameter inspection tool with a clear description and complete schema, the definition is fully sufficient to guide an agent, even without an output schema.
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 schema fully describes the single parameter (file_base64), so the description adds no additional parameter semantics, earning the baseline score for high coverage.
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?
Clearly states the tool inspects an image and lists what it examines (format, dimensions, file size), distinguishing it from sibling tools that compress, convert, or optimize.
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 focuses on inspection, making the use case clear, but doesn't explicitly mention alternatives or exclusions, leaving the agent to infer from sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
optimize_imageBInspectLossless image optimization. PNG uses oxipng (best-in-class PNG optimiser), JPEG re-encodes at high quality. Free tier: 20 calls/day per IP.
| Name | Required | Description | Default |
|---|---|---|---|
| file_base64 | Yes | The image file contents, base64-encoded. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It discloses that the optimization is lossless, uses oxipng for PNG, re-encodes JPEG at high quality, and has a free tier limit. However, it does not describe the response format, file size limits, or error behavior, leaving some behavioral aspects ambiguous.
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?
The description is two sentences: the first states purpose and processing details, the second discloses the rate limit. Every sentence earns its place, with no redundancy or fluff. It is appropriately concise and front-loaded.
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?
The tool is simple with one parameter, and the description covers purpose and processing details. However, since there is no output schema, the description should explain what the tool returns (e.g., optimized base64 string). It also lacks mention of input constraints like file size limits, leaving the description incomplete for a full understanding of the expected input and output behavior.
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 input schema fully describes the single parameter (file_base64) with 100% coverage, so the baseline is 3. The description adds no additional parameter semantics, such as accepted image formats or maximum file size. Since schema coverage is complete, this is acceptable but not enhanced.
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 clearly states the tool performs lossless image optimization, and specifies processing methods for PNG (oxipng) and JPEG re-encoding. It does not explicitly reference sibling tools to distinguish itself, but the specific focus on losslessness and optimizer names makes the purpose clear.
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 provides no guidance on when to use this tool versus alternatives like compress_image or convert_image. It only mentions the free tier rate limit, which is a constraint rather than a usage recommendation. No exclusion criteria or alternative tool references are provided.
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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