Colour Memory

Complete Brand Colour Audit

brand_audit

Read-only

Fast, fully deterministic brand colour audit. Accepts a palette array plus market, use_case, medium and brand_category. COMPUTED SYNCHRONOUSLY, no model call of any kind: colour roles with archive names, the full WCAG accessibility matrix, cultural risk per colour, CSS variables, Tailwind config, design tokens and production notes. NOT COMPUTED HERE: palette interpretation -- the verdict, its score and the written narrative copy. Those require an LLM call and used to be made inside this tool without saying so, which put a normal five-colour audit at 43-45s. The palette_verdict and verdict_copy keys are still returned, carrying interpretation_status='not_computed' plus a ready-to-send palette_verdict.continuation.arguments -- forward those verbatim to the palette_verdict tool to get the interpretation. Replaces chaining accessibility_matrix + cultural_risk_assessment; palette_verdict is now an explicit, optional second call rather than a hidden one. FOR A LIVE-SITE BRAND AUDIT ('audit this website'): inspect representative rendered pages FIRST (homepage, about, one deep page) and pass what you observed as site_evidence -- a CSS scrape alone is not an audit of what a visitor sees, and the response's audit_evidence.audit_status will say PARTIAL until real multi-page rendered evidence is supplied. 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

Name	Required	Description	Default
`market`	No	Target market e.g. 'UK luxury', 'global', 'Japan'	global
`medium`	No	digital \| print \| both	digital
`palette`	Yes	Array of hex values e.g. ['#D4A829', '#1A5C6E', '#0F2D6B', '#0A0A0B']
`use_case`	No	Use case e.g. 'brand identity', 'packaging', 'app UI'	brand identity
`site_evidence`	No	Evidence for a LIVE-SITE audit, supplied by the host (Colour Memory does not browse). {pages: [{url, role: 'homepage'\|'about'\|'work'\|'services'\|'product'\|..., screenshot: bool, tokens: bool, observations: [{hex, evidence_type: 'canonical_token'\|'rendered_observation'\|'source_verified_external'\|'model_interpretation', prominence?: 'dominant'\|'primary'\|...}]}], competitors: [{name, colours: [hex], colour_provenance: 'verified_brand_guideline'\|'verified_current_site'\|'verified_identity_source'\|'estimated'\|'unverified', source?}]}. A FULL live-site audit needs a homepage, an about/company page and one meaningful deep page (work/approach/services/product/case study), with rendered evidence from at least two of them. Supply less and the response's audit_evidence.audit_status comes back PARTIAL or INSUFFICIENT with the specific gaps named -- it will not present as a completed multi-page audit. A competitor colour that is not verified is kept as a QUALITATIVE comparison and never enters a CIEDE2000 or distinctiveness number; do not invent a hex to fill the gap.
`brand_category`	No	Optional brand category e.g. 'developer tool', 'food', 'fashion'

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.8/5.0

Behavior5/5

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

The description discloses that the tool is deterministic and synchronous with no model call, and transparently reveals that verdict generation was previously hidden inside the tool and is now delegated. It also states that audit_status will be PARTIAL or INSUFFICIENT without proper rendered evidence. The readOnlyHint annotation is consistent; no contradiction.

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 and heavily capitalized, but every section carries decision-relevant information: deterministic compute, hidden model call removal, live-site evidence requirements, and follow-up tool routing. It's dense rather than bloated, though a more structured layout would improve scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers input semantics, return-key behavior (palette_verdict, verdict_copy, audit_evidence.audit_status), downloadable artifacts, and required follow-up calls (palette_verdict, palette_finalize). Given an output schema exists, it doesn't need to detail return structure, but it provides enough for an agent to call and interpret results correctly.

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 met by the schema. The description goes beyond the schema for site_evidence by explaining what counts as a full live-site audit (homepage, about, deep page; rendered evidence from at least two) and that CSS scrapes are insufficient. Other parameters (market, medium, use_case) are merely listed in the description without adding beyond their schema descriptions.

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 'Fast, fully deterministic brand colour audit,' naming a specific verb and resource. It differentiates itself from siblings by stating what it replaces (chaining accessibility_matrix + cultural_risk_assessment) and what it does not compute (palette_verdict). This makes the tool distinguishable from palette_audit and related colour tools.

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?

It explicitly says to use palette_verdict as an optional second call for interpretation, and to call palette_finalize when choosing a final palette from the evidence. For live-site audits, it instructs to inspect rendered pages first and pass site_evidence, with a warning that a CSS scrape alone is insufficient. This is explicit when-to-use / when-not-to-use guidance.

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

A3.6/5.0

Disambiguation2/5

Several tool clusters perform near-identical functions: extract_image_colours, image_palette and palette_extract all extract dominant colours from images; colour_passport, colour_dna, colour_metrics and colour_cultural_risk all profile a single hex; and at least six compound 'complete package' tools (agent_brief, archive_report_brief, brand_report, design_session, image_brief, session_brief) overlap heavily in scope. The descriptions try to differentiate -- some even point to tool_guide for routing -- but the volume and similarity of clusters makes misselection likely.

Naming Consistency4/5

The vast majority of tools follow a clear domain_prefix_suffix pattern (colour_, palette_, archive_, brand_, accessibility_, project_) and within families naming is very disciplined (brand_guideline_specify/select/pdf/claims/status, project_get/list/versions/delete). However, a handful of outliers invert the order (extract_image_colours, ingest_image, render_colour_result, query_hex) and some descriptions reference tools that don't exist as endpoints (palette_from_concept, match_paint_system, get_colour_metrics).

Tool Count1/5

88 tools is far beyond any reasonable single-server surface, even for a platform spanning archives, branding, interiors and accessibility. The sheer number forces agents into a massive decision space, and many tools exist purely as convenience wrappers that replace chains of 3-6 other tools, suggesting aggressive consolidation was needed.

Completeness4/5

The surface covers an unusually broad domain -- archive search, colour science, palettes, branding, interiors, accessibility, image extraction, projects, and PDF/Word/Excel exports -- with very few dead ends for end-user workflows. Minor gaps: several compound-tool descriptions reference tools that no longer exist, and valid archive names are only discoverable via error messages rather than a dedicated listing endpoint.

Resources

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