CtrlK
BlogDocsLog inGet started
Tessl Logo

update-llm-model-list

Audit and update the supported LLM model list in assets.py against litellm's registry (models.litellm.ai). Use when adding new models, pruning outdated ones, or verifying the list is correct.

80

Quality

100%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

A well-structured, action-oriented skill body with executable code, a clear sequenced workflow including validation checkpoints, and clean organization. It assumes Claude's competence and avoids redundant concept explanations.

DimensionReasoningScore

Conciseness

Prose is lean and assumes competence (no explanation of what litellm or providers are); the embedded scripts are complete executable code that earns its tokens rather than padded concept exposition, matching the level-3 anchor.

3 / 3

Actionability

Provides fully executable, copy-paste-ready guidance — `uvx` invocations, complete Python heredoc scripts, and pytest commands with exact paths — rather than pseudocode or abstract direction, matching the level-3 anchor.

3 / 3

Workflow Clarity

A clear 4-step sequence (check outdated → find missing → edit → run ruff then test) with explicit validation: the check script exits non-zero on failure and "All checks must pass before committing" provides a feedback checkpoint, matching the level-3 anchor.

3 / 3

Progressive Disclosure

No bundle files exist, so disclosure is a single self-contained file with well-organized sections and headers; scripts are intentionally inlined via /tmp heredocs for portability with no nested references, avoiding the monolithic/nested level-1 anchors.

3 / 3

Total

12

/

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.

A tight, specific description that clearly states both the capability and the explicit "Use when" trigger conditions, with concrete actions rather than vague language. It is distinct and unlikely to conflict with other skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Audit and update the supported LLM model list", "adding new models, pruning outdated ones, or verifying the list is correct" — tied to a specific file (assets.py) and external registry, matching the level-3 anchor.

3 / 3

Completeness

Explicitly answers both what ("Audit and update the supported LLM model list... against litellm's registry") and when (an explicit "Use when..." trigger clause), satisfying the level-3 anchor rather than the implied-when level-2 anchor.

3 / 3

Trigger Term Quality

The "Use when adding new models, pruning outdated ones, or verifying the list is correct" clause covers natural phrases a developer would say, giving good coverage of common variations; it is not jargon-only (which would cap at 1) nor partial (level 2).

3 / 3

Distinctiveness Conflict Risk

The scope (the LLM model list in a specific assets.py file vs litellm's registry) is a clear niche with distinct triggers, making accidental triggering for unrelated skills unlikely; it is far more specific than the level-2 "Works with document files" overlap example.

3 / 3

Total

12

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Agenta-AI/agenta
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.