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Generate Creative Brief from Image

image_brief
Read-only

Compound endpoint: one image in, full creative brief out. Extracts dominant colours, matches them to the Colour Memory archive with coherent cultural naming, understands the scene, identifies the style period, suggests product directions by category (textiles, interiors, fashion), generates an image generation prompt, and returns a swatch URL. Use instead of chaining palette_extract + palette_analyse + agent_brief separately. Pass style_context for coherent archive matching e.g. 'English cottage garden', 'Victorian', 'MarsColour'. The result already carries the rendered palette and its PNG, PDF, ASE, JSON and CSS downloads -- show them to the customer. Never present the archive anchors a colour was derived from as the colours you are recommending. If you go on to choose a final palette OF YOUR OWN from this evidence, call palette_finalize once with those exact colours so the customer can see and download what you actually recommended.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoNumber of colours to extract (3-12, default 6)
modelNoImage model: midjourney | flux | dalle | stable_diffusion (default midjourney)
archiveNoExplicit archive name override e.g. 'MarsColour', 'Japan'
image_urlNoPublic URL of the image
image_base64NoBase64-encoded image data
product_typeNoProduct focus e.g. 'tea towel', 'wallpaper', 'ceramic', 'textile'
grey_card_hexNoHex value from a grey/white card for white balance correction
style_contextNoPlain English style e.g. 'English cottage garden', 'Victorian', 'Japanese', 'MarsColour'. Restricts archive matching to coherent cultural set.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare readOnyHint=true, and the description goes far beyond that: it reveals the compound nature of the endpoint, states that the result carries rendered palette downloads (PNG, PDF, ASE, JSON, CSS), and adds two hard behavioral rules — never present archive anchor colours as recommendations, and call palette_finalize when recommending a palette of your own. These are exactly the non-obvious traps an agent needs disclosed.

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?

The description is long but each sentence carries functional content — purpose, scope, alternative routing, param guidance, output contents, two caveats. Slight redundancy exists between 'returns a swatch URL' and 'carries the rendered palette and its ... downloads', and the palette_finalize sentence is a bit wordy, but for a compound endpoint of this complexity the density is justified.

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 an output schema present and readOny annotations covering safety, the description covers the essentials: full capability list, alternative routing, key param guidance, output artifacts, and two critical behavioral rules. The remaining gaps are minor but real for a tool with 8 optional params and no required ones — no precedence rule for image_url vs image_base64 when both are supplied, and no error/failure conditions.

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 baseline is 3. The description adds real meaning for style_contex ('pass style_contex for coherent archive matching e.g. English cottage garden, Victorian, MarsColour') and ties product_type to the cited catagories (textiles, interiors, fashion). For the remaining params (k, model, archive, image_url, grey_card_hex) it adds nothing beyond the schema, which limits it to a 4.

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 opens with a precise compound-endpoint statement ('one image in, full creative brief out') and enumerates the full pipeline: colour extraction, archive matching, scene understanding, style-period identification, product directions, prompt generation, and swatch URL. It explicitly names the siblings it replaces (palette_extract + palette_analyse + agent_brief), so an agent can distinguish it without inspecting other schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit alternative-and-condition: 'Use instead of chaining palette_extract + palette_analyse + agent_brief separately'. Also instructs when to pass style_contex for coherent archive matching and when to hand off to palette_finalize ('If you go on to choose a final palette OF YOUR OWN... call palette_finalize'), which routes the agent cleady.

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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TDQS

A3.7/5.0
Disambiguation2/5

Multiple tool clusters have unclear boundaries: colour_passport, colour_dna, colour_metrics, and colour_cultural_risk overlap heavily; palette_extract, extract_image_colours, image_palette, and ingest_image cover similar image-colour extraction territory; and compound tools like design_session, image_brief, session_brief, and archive_report_brief duplicate chains of component tools. The descriptions are detailed and occasionally state 'use this instead of X', but an agent still faces many near-duplicate choices.

Naming Consistency3/5

Names are consistently snake_case and often use domain prefixes (colour_, palette_, archive_, brand_, accessibility_), but verb placement is mixed: some are verb_noun (extract_image_colours, query_hex, style_match), others are noun_verb (colour_dna, palette_generate, brand_audit), and a few standalone names (ui_states, tool_guide, meta_capabilities) don't fit either pattern. The convention is readable but not uniform.

Tool Count1/5

At 88 tools, this is far beyond the reasonable well-scoped range and exceeds the 50+ extreme mismatch threshold. Many tools are compound wrappers that consolidate chains of simpler tools, adding redundancy and cognitive load rather than genuine coverage.

Completeness5/5

For the apparent domain, the tool surface is extremely comprehensive: colour extraction, analysis, naming, accessibility, cultural/provenance research, palette generation, brand systems, interior design, ecommerce copy, image briefs, project lifecycle, exports, and diagnostic tools are all present. Persistent objects have list/get/versions/delete/export support, so there are no obvious dead ends.

Resources