StockCake

Get StockCake Image

get_image

Read-onlyIdempotent

Fetch one image with full metadata: an inline preview the model can see (unless include_preview is false), real pixel dimensions, AI-generation provenance (prompt, dates, style), license details, and attribution snippets. Also shows the signed-in user's own edited images (ids ≥ 10000000000, as returned by generate_image, resize_image and upscale_image).

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Numeric image id (from search results), one of your own edited image ids (from a generate / resize / upscale result; needs the signed-in account), or the image's CDN uuid
`locale`	No	Site locale for the user (default en). Titles and page links are localized; descriptions are English.
`context`	Yes	In one sentence, what is the user trying to make or find?
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.
`include_preview`	No	Default true. Set false to skip the inline preview image and save tokens.

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes
`tags`	Yes
`title`	Yes
`license`	Yes
`page_url`	Yes
`dimensions`	Yes	Full-resolution pixel size; null when unknown
`provenance`	Yes
`attribution`	Yes
`description`	Yes
`preview_url`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 10, 2026

changedInput schema / properties / id / anyOf

Previous value: -[
-  {
-    "exclusiveMinimum": 0,
-    "maximum": 2147483647,
-    "type": "integer"
-  },
-  {
-    "maxLength": 64,
-    "minLength": 4,
-    "type": "string"
-  }
-]New value: +[
+  {
+    "exclusiveMinimum": 0,
+    "maximum": 9007199254740991,
+    "type": "integer"
+  },
+  {
+    "maxLength": 64,
+    "minLength": 4,
+    "type": "string"
+  }
+]

changedInput schema / properties / id / description

Previous value: -"Numeric image id (from search results) or the image's CDN uuid"New value: +"Numeric image id (from search results), one of your own edited image ids (from a generate / resize / upscale result; needs the signed-in account), or the image's CDN uuid"

First observedSep 28, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds real behavioral context beyond them: the response includes a model-visible inline preview whose token cost can be avoided via include_preview=false, and that edited-image ids require an authenticated account. It stops short of describing failure behavior for unknown ids.

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?

Two dense sentences with no filler, front-loaded with the return payload an agent most needs to decide whether to call it, followed by the id-space clarification. Every clause carries information.

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?

With a full annotation set, 100% schema coverage and an output schema, the description is nearly complete for a read-by-id tool: it covers return contents, accepted id forms, and the preview toggle. The only missing piece is explicit routing against sibling retrieval/download tools, which is a guidance rather than completeness gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning: it explains that the preview is inline and model-visible (why include_preview matters) and maps the id space to its sources, including the ≥10000000000 edited-image range. This reinforces and contextualizes the schema rather than merely repeating it.

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 and resource ('Fetch one image with full metadata') and enumerates exactly what comes back: inline preview, pixel dimensions, AI provenance, license details, attribution snippets. It also distinguishes this tool from the generation siblings by clarifying that edited-image ids are the ones returned by generate_image, resize_image and upscale_image.

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?

Usage is implied rather than stated: the mention that ids come 'from search results' or from generate/resize/upscale results tells the agent where a valid id originates, and names those siblings. But there is no explicit when-to-use-this-vs-alternative guidance (e.g., get_image vs download_image vs find_similar_images), and no exclusions or prerequisites beyond the parenthetical about needing a signed-in account.

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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