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Designesy

by io.github.LE-VAI

designesy_agent_json

Get the Designesy agent discovery document (/.well-known/agent.json) — the org identity, authority, ingest protocol, package index, machine-export list, permission policy, and citation templates. Use this when you are integrating with or enumerating Designesy as a machine agent and need the canonical discovery/manifest endpoint rather than one specific contract. When NOT to use: for the package list, use designesy_catalog (lighter); for the contract, use designesy_contract. Read-only — no side effects. Returns the /.well-known/agent.json object: { identity, authority, ingest_protocol, package_index, permission_policy, citation_templates }. 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?

No annotations are provided, so the description carries the full burden. It explicitly states 'Read-only — no side effects' and describes the returned object structure, which is more than sufficient for a simple discovery endpoint.

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?

Although slightly long, every sentence adds value: purpose, usage scenario, exclusions, read-only note, return shape, and parameter confirmation. The core action is front-loaded, making the structure effective.

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?

With no output schema, the description compensates by detailing the return object fields. It also covers usage context, exclusions, and behavior, making it complete for a zero-parameter discovery tool.

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, and the description confirms 'No parameters.' Per the baseline rule for zero-parameter tools, a score of 4 is appropriate since there is nothing else to document.

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 clearly states the tool's purpose: 'Get the Designesy agent discovery document' and enumerates its contents (identity, authority, ingest protocol, etc.). It distinguishes this tool from siblings by positioning it as the canonical discovery/manifest endpoint rather than a specific contract.

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?

Explicit usage guidance is provided: 'Use this when you are integrating with or enumerating Designesy as a machine agent and need the canonical discovery/manifest endpoint.' It also gives clear exclusions: 'for the package list, use designesy_catalog (lighter); for the contract, use designesy_contract.'

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