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Multi-Room House Colour Scheme — Provenance-Grouped Where Documented

house_specify
Read-only

Generate a complete multi-room house colour scheme from a single archive. Where the retrieved evidence supports it, rooms are grouped by documented provenance (same object, same pattern colourway, same source citation, same designer, same period+institution); where it does not, they are grouped by perceptual similarity and the response says so -- grouping_basis reports which, and provenance_credit reports how many delivered colours are individually evidenced versus documented as a GROUP (often zero). Every colour is a real archive record either way. Each room gets a full colour card set (dominant/secondary/joinery/textile/accent roles) with paint matches, LRV, illuminant behaviour, and WCAG data. A documentary grouping states exactly which documented fact ties its colours together (e.g. 'documented on the same Fitzwilliam Museum record for the Artichoke hanging, accession T.1-1979') and its weighted grouping_strength score -- historical claims are templated only from fields the archive record actually states; room/surface assignment is disclosed as editorial, never as historical fact. Orientation (north/south/east/west) is recorded as room context and surfaced in each room's light_context; in the current model it does not alter palette selection. Example: concept='Arts and Crafts movement family house', archive='ArtsAndCrafts', rooms=[{label:'Entrance Hall', room_type:'hallway', orientation:'north'}, {label:'Living Room', room_type:'living', orientation:'south'}]. Use interior_specify instead for a single room without cross-room grouping. The response includes house_ref -- pass that (not the full response) to palette_pdf's house_ref input to render the flagship document; the full response is often 60-100KB+, too large to safely resend as another tool call's input. 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
avoidNoTerms to exclude from retrieval.
roomsYesOne entry per room, e.g. [{label:'Entrance Hall', room_type:'hallway', orientation:'north'}]
archiveYesSingle archive to draw every room's colours from, e.g. 'ArtsAndCrafts'. Required -- invalid names return a clear error listing valid archives.
conceptYesHouse-level concept or brief, e.g. 'Arts and Crafts movement family house'
narrative_modeNoDefault 'evidence_only'.evidence_only
colours_per_roomNoDefault 5.
shared_house_coloursNoDefault 2.
minimum_claim_strengthNoEvidence-grade floor, default 'B'. Explicitly supplied: a hard admission filter, never relaxed -- too few qualifying records fails closed with a per-grade availability map (ARCHIVE_EVIDENCE_POOL_DEPLETED). Left at the implicit default: if the archive's best relevant records sit below it, the design-admissibility floor is relaxed to the archive's best achievable grade and disclosed in the response's evidence_floor block. Colours always keep their true evidence grade either way -- claims are never upgraded.B
strict_semantic_colourNoDefault true -- excludes entries whose quoted colour language contradicts their stored hex.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior5/5

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

The description discloses substantial behavioral nuance far beyond the readOnlyHint annotation: how grouping is determined, what grouping_basis and provenance_credit report, that room/surface assignment is editorial, that orientation does not affect palette selection, that the full response is large, and that the response already carries downloadable artifacts. It also warns agents never to present derivation anchors as recommended colours.

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 nearly every sentence adds decision-relevant behavior or workflow guidance for a complex tool. It is front-loaded with the core purpose and example, then organized around grouping, outputs, and cross-tool handoffs, making the length justifiable despite some density.

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?

For a complex tool with no output schema, the description fully covers what the agent needs: input shape, grouping semantics, evidence disclosure, output artifacts, size concerns, and sibling-tool handoffs. It also explains how to pass house_ref to palette_pdf and when to call palette_finalize, leaving little ambiguity about how to invoke and use the result.

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?

The input schema already provides detailed descriptions for most parameters, including concept, archive, rooms, orientation, minimum_claim_strength, and strict_semantic_colour. The tool description adds little parameter-specific meaning beyond an example and the requirement that a single archive supply all room colours, so the schema carries the bulk of the semantic load.

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 specific verb and resource: 'Generate a complete multi-room house colour scheme from a single archive.' It clearly distinguishes itself from sibling tools, especially interior_specify, and includes a concrete example of the expected input shape.

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 explicitly says 'Use interior_specify instead for a single room without cross-room grouping,' giving a clear exclusion condition. It also provides downstream routing guidance for palette_finalize and palette_pdf, so an agent knows exactly when and how to chain follow-up tool calls.

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