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kiln-check-deprecation

Check Kiln's model list for deprecated or sunset models across all providers. Use when the user wants to find deprecated models, check model availability, audit the model list for stale entries, or mentions model deprecation/sunset/end-of-life.

76

Quality

95%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

96%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-crafted operational skill: lean, information-dense, fully executable, with a clearly sequenced five-phase workflow that includes confirmation gates and post-edit verification. Bundle scripts are real, correctly referenced, and carry the implementation weight; the only structural refinement left is moving some inline provider-quirk detail into a reference file.

Suggestions

Move the per-provider API-quirk bullet list and the 'Providers NOT covered' / 'Providers to skip' detail into a one-level-deep references file (e.g. references/providers.md) so SKILL.md stays a leaner overview of the five phases.

The Phase 2 quirk notes duplicate docstring content in scripts/check_provider.py; consider keeping only the interpretation-relevant quirks (what 'missing' means per provider) inline and linking to the script for the rest.

DimensionReasoningScore

Conciseness

Every section carries non-obvious, task-critical information: API quirks ("Together AI returns a flat JSON array", "OpenRouter `:exacto` is a virtual routing suffix... never appears in model listings"), env-var requirements, and provider skip rationales. No padding, no explanations of concepts Claude already knows. Not a 4 because I found no over-explained passages that could be trimmed without losing actionable content.

5 / 5

Actionability

Every phase gives copy-paste-ready commands: "python3 .agents/skills/kiln-check-deprecation/scripts/extract_models.py > /tmp/kiln_extracted.json", "grep -n 'model_id="<model_id>"' libs/core/kiln_ai/adapters/ml_model_list.py", plus executable jq pipelines for Bedrock and LiteLLM and a concrete output format template for the report. Fully executable guidance covering the common cases.

5 / 5

Workflow Clarity

Five clearly sequenced phases with explicit checkpoints: the pre-check rules ("Only check providers where `deprecated=False`"), a user-confirmation gate ("Ask the user to confirm before making changes"), and a verification step ("grep -c \"deprecated=True\"... Ensure the count matches what you expect"), ending in a checklist. The destructive/batch-operation cap does not apply because validation and confirmation are present, and there are error-recovery notes ("If `gcloud auth print-access-token` fails, prompt the user to authenticate").

5 / 5

Progressive Disclosure

Structure is good: heavy lifting is properly offloaded to real bundle scripts (both `scripts/extract_models.py` and `scripts/check_provider.py` exist and are referenced by exact path), sections are clearly labeled by phase, and there is a provider table and a checklist. Not a 5 because the ~15-line provider-quirk bullet list and the "Providers NOT covered" detail could live in a one-level-deep reference file, keeping SKILL.md as a leaner overview; not a 3 because what is inlined is directly needed to interpret results and nothing is buried or nested.

4 / 5

Total

19

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20

Passed

Description

95%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.

A strong description that clearly states what the skill does and when to use it, with excellent natural-language trigger coverage including synonyms (deprecated, sunset, end-of-life, stale). The only minor gap is that the capability statement is a single action, which slightly limits the breadth of specificity compared to multi-action examples.

DimensionReasoningScore

Specificity

"Check Kiln's model list for deprecated or sunset models across all providers" names a concrete, domain-specific action, and the trigger clause enumerates specific variants ("find deprecated models, check model availability, audit the model list for stale entries"). Not a 5 because the core capability is a single action rather than multiple distinct concrete actions; not a 3 because the scope (Kiln's model list, all providers, deprecated/sunset) is precisely delimited with no vagueness.

4 / 5

Completeness

Explicitly answers both questions: what it does ("Check Kiln's model list for deprecated or sunset models across all providers") and when to use it ("Use when the user wants to find deprecated models... or mentions model deprecation/sunset/end-of-life"). Mirrors the anchor-5 example structure with concrete trigger phrases, so no lower anchor fits.

5 / 5

Trigger Term Quality

Covers natural terms and their synonyms users would actually say: "deprecated models", "model availability", "stale entries", "audit the model list", and explicitly "model deprecation/sunset/end-of-life". This matches the anchor-5 pattern of comprehensive synonym coverage (deprecation, sunset, end-of-life, stale).

5 / 5

Distinctiveness Conflict Risk

The proper noun "Kiln" and the narrow task (model-list deprecation audit) carve out a clear niche with triggers that would not fire for any other skill. Minimal conflict risk, matching the anchor-5 example.

5 / 5

Total

19

/

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
Kiln-AI/Kiln
Reviewed

Table of Contents

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