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Designesy

by io.github.LE-VAI

designesy_llms_txt

Get the Designesy /llms.txt — a short agent-facing brief with the canonical reference, topic index, ingest steps, package list, and contact. Use this first when you don't know what Designesy is — it's the cheapest orientation path before pulling heavier artifacts. When NOT to use: for the full expanded brief, use designesy_llms_full_txt; for the contract itself, use designesy_contract. Read-only — no side effects. Returns text/plain (~500 tokens). No parameters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

Even though no annotations are present, the description explicitly states 'Read-only — no side effects' and discloses the return format ('Returns text/plain (~500 tokens)'). It also describes what content the response includes, giving the agent a clear behavioral model despite having no structured safety hints.

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

Conciseness5/5

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

The description is well-structured: it opens with the action and resource, provides a concise content list, then delivers usage guidance, exclusions, safety, and return format in a compact sequence. Every sentence contributes critical information without redundancy, making it efficiently scannable.

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 zero-parameter tool that returns a simple text artifact, this description is fully complete. It covers the tool's purpose, what the output contains, when to use it vs alternatives, safety behavior, and output format. No additional context is needed for an agent to select and invoke it 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?

The tool has zero parameters, so the schema fully covers parameter semantics by having none. The description reinforces this with 'No parameters,' and the baseline for 0-param tools is 4. There are no undocumented parameters to explain, so it meets the expected standard.

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 starts with a specific verb 'Get' and names the exact resource '/llms.txt', then lists its key contents (canonical reference, topic index, ingest steps, package list, contact). It explicitly distinguishes this tool from siblings by naming designesy_llms_full_txt and designesy_contract, making its purpose unmistakable.

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?

Provides clear when-to-use guidance: 'Use this first when you don't know what Designesy is' and frames it as the 'cheapest orientation path before pulling heavier artifacts.' It also gives explicit when-not-to-use instructions with named alternatives (designesy_llms_full_txt for full brief, designesy_contract for the contract), which is exemplary.

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

All Designesy toolsInspect
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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly scoped purpose, and the extensive 'When NOT to use' notices cleanly separate the many scoring variants (e.g., score, drift, readiness, monitor, tokens, motion, a11y). Even similar informational endpoints (contract, skill, llms) are differentiated by format and use case. No two tools appear to do the same thing.

Naming Consistency5/5

All tools follow a consistent 'designesy_' prefix, and scoring tools uniformly append '_score' (e.g., drift_score, tokens_score, monitor_score). Non-score tools use descriptive noun suffixes (catalog, contract, report, guardrails). The pattern is predictable and uniform throughout.

Tool Count4/5

At 17 tools, the set is slightly above the ideal 3-15 range, but the breadth of the design-system intelligence domain justifies the count. Each scoring variant targets a different artifact (live URL, token file, Lottie, temporal drift) and the informational endpoints serve distinct formats. The tool count is heavy but not bloated.

Completeness5/5

The toolset covers the full assessment lifecycle: full audit (score), drift and temporal governance (drift_score, monitor_score), AI readiness (readiness_score), token and motion validation (tokens_score, motion_score), accessibility framework (a11y_score), diff (compare), composite report (report), guardrails generation, and multiple discovery formats (catalog, contract, skill_md, llms). No obvious dead ends exist; each tool leads to a usable artifact or clear next step.

Resources