Skip to main content
Glama

create_taste_profile

Destructive

Create a portable design-judgment ruleset by defining explicit rules or ingesting a DESIGN.md document. Rules are categorized and stored locally for consistent design audits.

Instructions

Create (or overwrite) a named taste profile — a portable design-judgment ruleset + precedent corpus persisted locally under ~/.raven/taste/.json (override dir with RAVEN_TASTE_HOME). Pass explicit rules[] (rule_id, clause_text, category, severity_default block|warn|nit, negative_prompt, owner taste|raven, delegate_to), and/or a DESIGN.md-style markdown doc to ingest (## headings = categories; '- ' bullets = rules; '(block)'/'(warn)'/'(nit)' severity markers; '(raven:)' delegates a rule to an existing Raven audit tool; '(scope:)' scopes a rule to one surface; 'Do NOT …' sentences become the rule's negative prompt). Ingest RULES-SHAPED docs only (actionable design constraints under category headings) — brand-story/mythology docs produce noise rules, not judgment. Local-first: nothing leaves the machine. Pass template:'portfolio'|'saas-marketing'|'app' for a cold start — seeds a small starter ruleset (color restraint, typography floor, spacing, voice, tap targets) BEFORE any calibration interview has run; template rules are added first, then any explicit rules/markdown you also pass are merged in on top. Still run get_taste_interview afterward — the template is a floor, not a substitute for calibrating to the actual person's taste.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesProfile name (becomes <name>.json; lowercase alnum/dash/underscore).
rulesNoExplicit rule objects.
corpusNoSeed precedent records.
markdownNoDESIGN.md-style markdown to ingest as rules.
templateNoSeed a small cold-start ruleset for this surface family before any explicit rules/markdown are merged in. Omit for a blank profile.
Behavior4/5

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

Annotations indicate destructiveHint=true; description adds detail: local file persistence, merge behavior (template first, then explicit/markdown), and the 'overwrite' semantics. Warns about noise from inappropriate docs. No contradictions with annotations.

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

Conciseness3/5

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

Description is lengthy with multiple paragraphs covering edge cases and warnings. While information-dense, it could be more concise. Front-loaded with primary purpose but drifts into detailed markdown parsing rules that might overwhelm.

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?

Covers file location, merge logic, template behavior, and post-invocation step. Missing return value or error handling (e.g., invalid name, duplicate rule_id). Given no output schema, some behavioral context is absent.

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

Parameters5/5

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

Schema coverage is 100%, but description adds substantial meaning: explains rules object fields in detail, markdown ingestion format with syntax examples, template enum semantics, and order of merging. Goes far beyond 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?

Clearly states it creates/overwrites a named taste profile with specific components (ruleset + precedent corpus). Distinguishes from sibling tools like get_taste_profile (read) and audit_taste (evaluate).

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

Usage Guidelines4/5

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

Provides explicit when-to-use guidance for passing rules, markdown, or template. Warns against using non-RULES-SHAPED docs. Recommends subsequent get_taste_interview call. Could explicitly contrast with get_taste_profile for when to read only.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rhinocap/raven-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server