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ard-registry-builder

Build, validate, test, and update registries and catalogs that follow the Agentic Resource Discovery (ARD) specification. Use this whenever the user works with an ai-catalog.json, a capability manifest, an ARD/AIR catalog or Agent Registry, urn:air: identifiers, trustManifest/attestations, representativeQueries, or an Agent Finder / discovery service — including authoring a new manifest, scaffolding one, fixing schema or URN errors, running conformance/validation, probing a registry's /search, /explore, or /agents REST endpoints, reviewing trust and federation metadata, or preparing to publish at /.well-known/ai-catalog.json. Trigger it even when the user only says "ARD", "agentic resource discovery", "AI catalog manifest", "agent registry", or "make agents discoverable" without naming the file.

76

Quality

94%

Does it follow best practices?

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered skill body: copy-paste-ready commands, error-code-to-fix mappings, and four workflows with explicit validate-and-retry loops. The only defects are minor trimmable prose in the golden-rules section and a dangling reference to a non-existent evals/evals.json file.

Suggestions

Remove or fix the dangling "evals/evals.json" reference (Section: Evals) — the evals/ directory is absent from the bundle, so the pointer currently dead-ends.

Tighten the "Golden rules" section: fold the URN/url and FQDN rules into the workflows that enforce them, keeping only the checks not already stated inline.

The "Two artifacts, one mental model" prose paragraph can be condensed to the two bullets plus the one-line URN/URL rule without losing the identity-vs-location insight.

DimensionReasoningScore

Conciseness

The body is dense and task-oriented ("Run the validator first, before reading the file by hand — it pinpoints issues fast"), and its ARD explanations are niche domain knowledge Claude does not already have, so they earn their tokens. It is not a 5 because the "Golden rules (the why behind the checks)" section and the identity-vs-location prose partially restate rules the workflows already enforce and could be trimmed; it is above 3 because padding is minor and there is no generic-concept explanation.

4 / 5

Actionability

Fully executable, copy-paste-ready commands cover the common cases: "python scripts/new_catalog.py --template enterprise --publisher mycorp.com --host 'MyCorp AI' --out ./ard.json", "python scripts/validate_catalog.py <path-or-url>", "python scripts/test_registry.py https://registry.example.com/api/v1", plus a concrete error-code-to-fix mapping ("urn-wrong-nid → change urn:ai: to urn:air:"). Score 4 would require minor gaps in the commands or examples, and none are evident.

5 / 5

Workflow Clarity

Four workflows are clearly sequenced with explicit validation checkpoints and feedback loops: "Validate: python scripts/validate_catalog.py ./ard.json. Fix until it passes", "Re-run until clean", and "Re-validate the file; if it is already published, also validate the live URL and re-probe any registry. Treat 'passes validation' as the definition of done." This matches the top anchor's validate→fix→retry pattern; no checkpoint is missing or only implicit.

5 / 5

Progressive Disclosure

The body is a clean overview with four one-level-deep, clearly signaled references (references/data-model.md, registry-api.md, validation-rules.md, publishing.md), all verified to exist with the promised table of contents, plus bundled scripts and templates. It is not a 5 because the "Evals" section points to "evals/evals.json", which does not exist in the bundle — a dangling reference that breaks navigation; it is above 3 because all other structure and signaling is excellent.

4 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: concrete capabilities, an explicit "Use this whenever…" trigger clause with additional colloquial trigger phrases, and highly distinctive spec-specific terminology. It is comprehensive without padding.

DimensionReasoningScore

Specificity

Multiple concrete actions are listed — "Build, validate, test, and update registries and catalogs", "authoring a new manifest, scaffolding one, fixing schema or URN errors, running conformance/validation, probing a registry's /search, /explore, or /agents REST endpoints" — with comprehensive coverage and no vague filler. Score 4 would require minor coverage gaps, but every listed capability is a specific concrete action.

5 / 5

Completeness

Explicitly answers both what ("Build, validate, test, and update registries and catalogs that follow the Agentic Resource Discovery (ARD) specification") and when ("Use this whenever the user works with…" and "Trigger it even when the user only says 'ARD'…"). Both are present with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Comprehensive natural-term coverage including synonyms and literal file/spec tokens: "ai-catalog.json", "urn:air: identifiers", "trustManifest/attestations", "Agent Finder / discovery service", plus colloquial triggers like "make agents discoverable". This matches the anchor's bar of synonyms and file extensions; score 4 would mean a few natural terms are missing, and none are obviously absent.

5 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (the ARD specification) with spec-specific triggers (URNs, trust manifests, /.well-known/ai-catalog.json) that no generic skill would claim, so conflict risk is minimal. Score 4 would require overlap with closely related skills, which the spec-bound terminology precludes.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
webmaxru/ai-native-dev
Reviewed

Table of Contents

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