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Colour Memory

by io.github.DigbyO

Generate an Archive-Grounded Brand Colour Standard

brand_guideline_specify
Read-only

Generates the case for a brand's colours, not just the colours themselves: three genuinely different, archive-grounded candidate palettes from a brand brief, each scored for distinctiveness against named competitors, checked for accessibility, and labelled with exactly what each colour can and cannot legitimately claim (documented archive anchor vs analogue vs original brand colour). Returns a brand_ref (valid 24h) plus a claim_id per colour -- resolve those into full source/permitted-claim/do_not_say text with brand_guideline_claims (the response's own claim_detail_available_via field always names it explicitly). Follow with brand_guideline_select to record which candidate was chosen. CREATE ONCE, THEN VERSION: the response returns project_id and current_version. When you refine or update a Brand Standard you already created in this conversation, pass that project_id back as continue_project_id rather than creating a second project. TIMING (2026-08-07): real generation cost ranges roughly 60-280 seconds depending on retrieval/generation path. This call races generation against a safe ~55s window: a fast generation returns the full result exactly as described above, unchanged. A slower generation instead returns a compact {"status": "processing", "brand_job_ref": ..., "poll_after_seconds": ...} -- generation keeps running server-side regardless, and is never lost. Call brand_guideline_status with that brand_job_ref to retrieve the completed result (brand_ref, project_id, candidate summary) once ready; poll no more often than poll_after_seconds suggests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_nameYesThe brand's name.
brand_briefNoCategory, positioning, audience, personality, values, channels, markets, and named competitors with their hex colours.
constraintsNoStructured negative/positive retrieval constraints, checked before archive-diversity capping. avoid_concepts takes precedence over any sentiment inferred from brand_brief prose.
preferencesNo
palette_inputYesExactly how to source the candidate colours.
identity_assetsNo
output_preferencesNo
continue_project_idNoThe project_id returned by an earlier call, when this is a REFINEMENT of that same Brand Standard. Reuse it and the work joins that project as a new version; omit it and a second project is created. 'Make it warmer', 'change the secondary', 'render the PDF again' and 'show another option' are all continuations. Start a new project only when the customer asks for a genuinely separate brand.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.5/5.0
Behavior1/5

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

The description transparently discloses async generation (the ~55s race, the {"status":"processing"} fallback, poll_after_seconds, 'generation keeps running server-side... never lost') and creation semantics (projects, versions, 24h brand_ref). However, annotations declare readOnlyHint=true, which asserts the tool does not modify state — directly contradicted by a tool that creates projects and versions server-side. Flagged as an annotation contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is an unbroken wall of dense run-on sentences packing async behavior, versioning, polling, and sibling routing together ('Returns a brand_ref (valid 24h) plus a claim_id per colour -- resolve those into full source/permitted-claim/do_not_say text with brand_guideline_claims...'). The purpose is front-loaded, but scanability is poor and the text contains typos ('CREATE ONCE'), so it is comprehensive rather than concise.

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?

For an 8-parameter, nested-object tool with async generation, the description covers the full call lifecycle: what is generated, what is returned, how to poll, what to call next, and how to version refinements. An output schema exists, so return values need not be spelled out. The remaining gaps are the annotation contradiction and unstated prerequisites for input modes such as image, which keep it just shy of fully complete.

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 63%, so the schema already carries most parameter documentation, and it is notably rich where it matters (minimum_claim_strength's evidence-vs-design rule, continue_project_id's continuation examples, constraints' precedence). The description itself adds nothing about parameters, so the uncovered ~37% (e.g., output_preferences, identity_assets semantics) is left to the agent to infer.

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 opening sentence names a specific verb and resource: 'Generates the case for a brand's colours... three genuinely different, archive-grounded candidate palettes... scored for distinctiveness against named competitors, checked for accessibility'. It lists concrete deliverables (brand_ref, claim_id per colour, project_id, current_version) and names sibling tools (brand_guideline_claims/select/status) so an agent can tell this tool apart without opening any schema.

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?

The description gives explicit sequencing and alternatives: resolve claims with brand_guideline_claims, 'Follow with brand_guideline_select to record which candidate was chosen', and 'Call brand_guideline_status with that brand_job_ref to retrieve the completed result'. The CREATE ONCE/THEN VERSION rule states when to pass continue_project_id rather than create a second project, and the schema even contrasts this tool with palette_specify on evidence-floor behavior.

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

A3.8/5.0
Disambiguation2/5

With 88 tools, there is substantial overlap: colour_passport vs colour_dna vs colour_metrics vs colour_cultural_risk are explicit components of the same object; palette_concept vs palette_strict vs palette_generate vs palette_heritage overlap heavily; and four image extraction tools exist (extract_image_colours, image_palette, palette_extact, ingest_image). Although descriptions are detailed and tool_guide exists, an agent will frequently struggle to select the correct tool unambiguously.

Naming Consistency5/5

Nearly all tools follow a consistent snake_case noun_verb or domain-prefixed pattern (colour_*, palette_*, brand_*, archive_*, project_*, accessibility_*). The naming is uniform and predictable, with no mixing of styles or verb conventions across the set.

Tool Count1/5

88 tools is an extreme count for an MCP server. Even honoring the broad domain, the rubric places 50+ at the extreme end, and the high overlap between compound and individual tools suggests many could be consolidated or exposed as sub-resources rather than top-level tools.

Completeness5/5

The tool surface covers the full colour lifecycle: lookup, analysis, palettes, brand systems, accessibility, image extraction, interior design, archival research, reports, PDF generation, and project management. Workflows have clear entry points and few dead ends, and the presence of compound tools further closes integration gaps.

Resources