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designesy_catalog

List the 23 published Designesy packages with versions, URLs, and statuses. Use this to discover what Designesy publishes before fetching a specific contract. When NOT to use: if you already know which package you need, skip this and call designesy_contract directly. Read-only — no side effects. Returns JSON: { package_count, packages[{id, kind, title, version, status, human_url, machine_url}], standing_rules[], machine_exports[] }. No parameters — accepts empty input.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states 'Read-only — no side effects' and discloses the exact JSON return shape, which is especially valuable given there is no output schema.

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 compact and front-loaded with the core purpose. Every sentence adds value: purpose, usage guidance, side-effect disclosure, return format, and parameter confirmation. No filler or repetition.

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 read-only catalog tool with no annotations and no output schema, the description covers everything an agent needs: what it lists, what it returns, whether it has side effects, and how to choose between this and designesy_contract. It is complete for correct invocation and interpretation.

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 schema already shows an empty properties object, so the baseline is 4. The description reinforces with 'No parameters — accepts empty input,' which is helpful but adds little semantic meaning beyond the schema.

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 states a specific verb ('List') and resource ('the 23 published Designesy packages') with the exact fields returned. It also distinguishes itself from the sibling designesy_contract by framing itself as the discovery step before fetching 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?

It explicitly tells the agent when to use the tool ('Use this to discover what Designesy publishes before fetching a specific contract') and when not to use it ('if you already know which package you need, skip this and call designesy_contract directly'). This gives clear routing guidance relative to a relevant sibling.

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

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.