agent-sona-learning-optimizer

Agent skill for sona-learning-optimizer - invoke with $agent-sona-learning-optimizer

Quality

11%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-sona-learning-optimizer/SKILL.md

Quality

Discovery

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

This description is critically deficient across all dimensions. It provides only a technical invocation command without any explanation of capabilities, use cases, or trigger conditions. Claude would have no basis for selecting this skill appropriately from a list of available skills.

Suggestions

Add a clear statement of what the skill does with specific actions (e.g., 'Optimizes learning schedules, creates spaced repetition plans, tracks study progress').

Include an explicit 'Use when...' clause with natural trigger terms users would say (e.g., 'Use when the user asks about study optimization, learning strategies, or spaced repetition').

Remove or relocate the invocation command to focus the description on capabilities and selection criteria rather than technical implementation details.

Dimension	Reasoning	Score
Specificity	The description contains no concrete actions whatsoever. It only states it's an 'Agent skill' with an invocation command, providing no information about what the skill actually does.	1 / 3
Completeness	The description fails to answer both 'what does this do' and 'when should Claude use it'. It only provides an invocation command with no functional description or usage guidance.	1 / 3
Trigger Term Quality	No natural keywords users would say are present. 'sona-learning-optimizer' is technical jargon that wouldn't appear in natural user requests. There are no terms like 'learning', 'optimize', 'study', or any domain-specific vocabulary.	1 / 3
Distinctiveness Conflict Risk	The description is so vague that it's impossible to distinguish from other skills. Without knowing what it does, there's no way to determine when it should or shouldn't be selected.	1 / 3
	Total	4 / 12 Passed

Implementation

22%

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

This skill reads more like a marketing document or README than actionable guidance for Claude. It heavily emphasizes performance claims and benchmarks but fails to explain how to actually use the SONA learning optimizer in practice. The hooks section is the only actionable content but lacks context on integration into workflows.

Suggestions

Replace capability descriptions with a concrete workflow showing how to integrate SONA learning into a task (e.g., 1. Initialize before task, 2. Execute task, 3. Record outcome, 4. Verify learning)

Add executable code examples showing actual usage patterns, not just CLI invocations with placeholder variables

Remove or drastically reduce the performance benchmarks section - move to the referenced integration guide if needed

Explain when and why to use pre-task/post-task hooks with a concrete example task

Dimension	Reasoning	Score
Conciseness	Contains some unnecessary self-description ('I am a self-optimizing agent') and marketing-style claims (+55% quality improvement) that don't add actionable value. The performance statistics section is verbose for a skill file.	2 / 3
Actionability	Extremely vague - describes capabilities and benchmarks but provides almost no executable guidance. The only concrete commands are two hook invocations with placeholder variables and no context on when/how to use them.	1 / 3
Workflow Clarity	No clear workflow for how to actually use this agent. Lists capabilities and performance metrics but never explains the sequence of operations, when to invoke hooks, or how the learning loop works in practice.	1 / 3
Progressive Disclosure	References an integration guide (docs/RUVECTOR_SONA_INTEGRATION.md) which is appropriate, but the main content is poorly organized - mixes marketing claims, benchmarks, and sparse usage info without clear structure for discovery.	2 / 3
	Total	6 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: ruvnet/claude-flow
Commit: b2618f9

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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