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sync-model-catalog

Regenerate and refresh the curated agent model catalog (the label/description/pricing/ratings behind the agent model picker). Use when the pinned @earendil-works/pi-ai version bumps, when a Claude Code build changes its accepted alias set, or before a release when the curated Claude/Pi facts (lineup, pricing, ratings) need refreshing from current public sources. Owns the data files under sdks/python/agenta/sdk/agents/data/; never edits capabilities.py logic.

74

Quality

92%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

The body is a lean, actionable, well-sequenced operational guide with explicit validation and one-level-deep references; its only weakness is an inline time-sensitive date that the rubric penalizes for conciseness. Otherwise it is strong across actionability, workflow clarity, and progressive disclosure.

Suggestions

Move or remove the inline time-sensitive phrase "as of mid-2026" (and the Fable-5-above-Opus assertion) into a clearly labeled "current as of" / deprecated-style note, or replace it with an instruction to always look up the current frontier, so conciseness is not dinged for a hardcoded date.

Add a per-job validation callout (e.g., re-run the pytest loader after Job 1's regeneration and after Job 3's metadata edits) so each workflow step has its own checkpoint rather than relying on a single centralized Validate section.

Consider linking the design docs as markdown references (e.g., See [design.md](...)) in addition to the bare path so the one-level-deep references are even more clearly signaled for navigation.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's competence with no padded concept explanations, but it embeds an inline time-sensitive phrase — "the Anthropic frontier is Fable 5, above Opus, as of mid-2026" — which the guideline says should penalize conciseness unless placed in a deprecated/old-patterns section; it is not level 3 because of that date, and not level 1 because there is no verbose explanation of concepts Claude already knows.

2 / 3

Actionability

Job 1 provides a fully executable bash command with glob resolution and the node invocation, and the Validate section gives a copy-paste pytest command; Jobs 2 and 3 give concrete, actionable guidance (publish claude-fable-5, avoid fable/fable[1m], validate the 1-5 range) with the absence of code explicitly justified by the live-session requirement — matching the fully executable/specific anchor; not level 2 because the guidance is complete rather than pseudocode or missing key details.

3 / 3

Workflow Clarity

The three jobs are clearly numbered and sequenced, with a dedicated Validate section that includes an explicit command and a feedback loop ("fails loud there... publishes an empty catalog rather than crashing /inspect") plus a "When to run" checklist; validation is present for the data-file rewrite so there is no cap at 2, and it is not level 2 because checkpoints and error recovery are explicit rather than implicit.

3 / 3

Progressive Disclosure

No bundle directories are provided, so this is scored on body organization: the content is well sectioned (~85 lines) with one-level-deep, clearly signaled references (design.md/plan.md in the rationale line, generate_pi_models.mjs for the generator); matches the clear-overview-with-well-signaled-references anchor and is not level 2 because references are not nested or poorly signaled.

3 / 3

Total

11

/

12

Passed

Description

100%

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

The description is specific, third-person, and clearly states both what the skill does and exactly when to invoke it, with concrete trigger conditions tied to repo events. It is unlikely to conflict with other skills given its narrow scope.

DimensionReasoningScore

Specificity

Lists multiple concrete actions tied to concrete artifacts — "Regenerate and refresh the curated agent model catalog (the label/description/pricing/ratings...)", "Owns the data files under sdks/python/agenta/sdk/agents/data/", "never edits capabilities.py logic" — matching the anchor for listing multiple specific concrete actions; it is not the level below because it names more than a domain plus a few actions incompletely.

3 / 3

Completeness

Explicitly answers what ("Regenerate and refresh the curated agent model catalog...") and when via an explicit "Use when..." clause listing three concrete triggers; matches the anchor that clearly answers both what AND when, and is not level 2 because the trigger guidance is explicit rather than implied.

3 / 3

Trigger Term Quality

Natural trigger terms the intended audience would say — "model catalog", "model picker", "pi-ai version bumps", "Claude Code build changes its accepted alias set", "before a release", "lineup, pricing, ratings" — give good coverage of multiple distinct triggers; not level 2 because common variations are well represented rather than partially missing.

3 / 3

Distinctiveness Conflict Risk

Occupies a narrow, well-scoped niche (this SDK's curated agent model catalog) with distinct triggers (pi-ai bump, alias-set change, pre-release refresh) that are unlikely to fire for any other skill; not level 2 because it is far more specific than "works with document files"-style overlap.

3 / 3

Total

12

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

Total

15

/

16

Passed

Repository
Agenta-AI/agenta
Reviewed

Table of Contents

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