APICK Vision

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

The readOnlyHint annotation already indicates a safe read operation, and the description adds valuable context: it returns a ZIP file, extracts at regular intervals, and costs 10 points per call. This goes beyond the annotation and helps the agent understand side effects and cost. No contradiction detected.

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 concise, with a single English sentence and a Korean duplicate alongside the cost note. It front-loads the core action and output format with no unnecessary filler. The bilingual repetition is acceptable and the cost disclosure is important, so every part earns its place.

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?

Given the tool's moderate complexity, the description covers the essential purpose, output format, and cost. The schema fully documents parameters and limits (e.g., max 200MB). It does not explain processing time or failure behavior, but for a read-only extraction tool with strong schema coverage, this is reasonably complete.

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 descriptions cover all parameters 100%, so the baseline is 3. The description does not add further semantic detail about the parameters beyond what the schema already provides. It mentions 'regular intervals' but does not clarify count or width behavior beyond their schema descriptions.

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 a specific action ('Extract preview thumbnail images') on a specific resource ('from a video'), and specifies the output format ('return them as a ZIP file'). This distinguishes it from sibling tools like face_detection or video_to_mp3, which serve different purposes.

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 implies when to use it (when you need preview images from a video) but does not explicitly mention alternatives or exclusion criteria. It would benefit from stating that it is not for audio extraction or detection tasks. Usage is implied rather than explicitly guided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations declare readOnlyHint=true, covering safety. The description adds the cost per call (3 points) and notes that use_feature=1 returns face feature info, which is useful beyond annotations. However, it does not describe other behaviors like error handling or limitations, so it adds only moderate context.

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 concise and front-loaded with the primary purpose. It includes both English and Korean versions of the same content, which is slightly redundant but acceptable. The cost note is placed at the end, keeping the main action clear.

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 read-only tool with all parameters documented and no output schema, the description covers the essentials: what it detects, the optional feature, and cost. It could optionally describe the format of the returned coordinates (e.g., bounding boxes), but that is not critical for invocation.

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 description coverage is 100%, with each parameter already documented (e.g., threshold sensitivity, use_feature flag). The description mentions the effect of use_feature but essentially restates the schema, so it adds little new meaning to the 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 the tool detects faces and returns their coordinates, which is a specific verb and resource. It distinguishes from siblings like nsfw_detection or image_similarity by its unique focus on face detection, though it does not explicitly name alternatives.

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?

No guidance is given on when to use this tool versus the sibling tools (e.g., nsfw_detection for inappropriate content, image_similarity for image matching). There are no conditions, prerequisites, or exclusions provided, leaving the context of use implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true, so the description doesn't need to state non-mutating behavior. The description adds a practical detail — the per-call cost of 10 points — and mentions use cases, which is helpful context beyond the annotations. It does not describe the nature of the similarity score (e.g., range, interpretation), but this is not a conflict. Given annotations cover the safety profile and the description adds a bit of operational context, a 3 is fair.

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 concise — three short sentences plus a cost note in brackets. The primary action and purpose are front-loaded, and every sentence adds value: what it does, use cases, and cost. There is no filler or redundancy.

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 two-parameter tool with no output schema, the description is mostly complete: it states inputs, outputs (a score), and use cases. The significant gap is the lack of any indication about the score's format or scale (e.g., 0–1, percentage), which an agent would need to interpret results correctly. Since the description carries the responsibility for explaining return values when no output schema exists, this omission makes it incomplete enough for a 3.

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% — both parameters (image_url, compare_image_url) are fully described with format restrictions and size limits. The description does not add semantic meaning beyond the schema; it merely restates roles (base vs. comparison) that are already evident from parameter names and the schema descriptions. With full schema coverage, the baseline of 3 applies.

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 verb 'Compare' with two distinct resources (base image and comparison image) and the outcome (similarity score). It further specifies use cases (origin verification, duplicate detection), which distinguishes it from all sibling tools that handle video, face, NSFW, audio, and text — none relate to image similarity. This is a specific and unambiguous definition.

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?

It provides clear usage context by listing typical scenarios ('원본 검증, 중복 이미지 탐지 등' – origin verification, duplicate detection), which guides an agent on when to invoke it. However, it does not explicitly state when NOT to use it or mention alternative tools, though no sibling tool is directly comparable. Since context is given but exclusions are absent, a 4 is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true, so the description need not restate that. It adds useful context about the detail parameter returning detailed results and the per-call cost of 10 points. These are beyond the annotations, but no additional behavioral traits like failure modes or rate limits are disclosed.

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 contains redundant bilingual repetition: the same English and Korean sentence say the same thing. While overall length is short, the duplication wastes space and could be consolidated. The core purpose is front-loaded, but the structure is not tight.

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 description explains the output (nsfw_score) and the detail option, but does not clarify the score's scale, interpretation thresholds, or any failure behavior. Given there is no output schema, this leaves the agent uncertain about how to act on the result. Cost is mentioned, which helps, but overall completeness is only 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 description coverage is 100%, so both `detail` and `image_url` are already documented (including formats and size limits). The description merely repeats the detail behavior ('detail=1 입력 시 세부 판정 결과를 함께 반환') without adding new meaning beyond the schema, so it sits at the baseline.

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 detects NSFW content in an image and returns a score, using a specific verb and resource. It distinguishes from siblings like face_detection and image_similarity by the domain, but does not explicitly name them or contrast, so it misses the top mark.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention scenarios like content moderation or say to prefer image_similarity for similarity tasks, leaving the selection burden entirely on the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true, which the description does not contradict. The description adds a cost note (30 points per call), which is a useful behavioral detail. However, no other behavior such as output format details (beyond MP3) or failure modes is disclosed.

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 concise, front-loaded with the key action, and includes a bilingual translation and cost note. Each part serves a purpose, and there is no unnecessary fluff.

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 single-parameter tool with no output schema, the description covers the core function and output (MP3 file) plus cost. It lacks details on response format or error handling, but remains adequate for a simple conversion tool.

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 provides 100% coverage for the video_url parameter, including allowed formats and size limit. The description adds no additional parameter-specific information, leaving the schema to carry the full burden.

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 uses a specific verb ('Extract') and resource ('audio track of a video file') and specifies the output format (MP3). It clearly differentiates from sibling tools like extract_video_thumbnail, which handles thumbnails rather than audio.

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 implies usage when an MP3 audio file is needed from a video, but does not explicitly state when to use it vs alternatives or mention any exclusions. Sibling tools are distinct, so selection is straightforward.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and openWorldHint. The description adds valuable details: the output format (JPEG), the frequency-based sizing behavior, and a per-call point cost. It does not contradict the annotations, though it omits return transport details like URL vs base64.

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 English sentence is concise and front-loaded. The Korean repetition adds minor redundancy but includes the cost note. Overall the description is well-sized, though it could be tightened by removing the duplicate.

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 read-only tool, the description is mostly complete. However, it lacks an output schema and does not specify the return format (URL, binary, etc.) or any input limitations/error behaviors. It is minimally viable but not fully transparent.

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 documents the single 'text' parameter with 100% coverage, so the description does not need to add parameter details. It only explains tool behavior, not parameter constraints, aligning with the baseline 3 for high schema 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?

The description clearly states the tool generates a JPEG word cloud image from input text, with word sizing based on frequency. It uses a specific verb-resource pairing and distinguishes itself from sibling media analysis tools (e.g., face_detection, video_to_mp3).

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 explains what the tool does, but does not explicitly state when to use it or mention alternatives. Usage is implied by the tool name and purpose; siblings are clearly different, but no direct 'use this when...' guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.