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agent-sona-learning-optimizer

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

18

Quality

3%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./.agents/skills/agent-sona-learning-optimizer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

7%Scale 1-3

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

This skill reads like a marketing document or README for a product rather than an actionable skill for Claude. It is dominated by benchmark statistics, capability bullet points, and performance claims, but provides virtually no concrete instructions on how to actually perform tasks. The only actionable content is two bash commands for hooks, buried without context or workflow integration.

Suggestions

Replace the capability lists and benchmark tables with a concrete step-by-step workflow showing how Claude should use SONA learning in a task (e.g., 1. Initialize trajectory, 2. Execute task, 3. Record outcome, 4. Verify learning improvement).

Add executable code examples showing actual usage patterns — how to invoke LoRA fine-tuning, how to query the pattern library, how to select an LLM route — not just the hook commands.

Remove all marketing-style performance claims and benchmark statistics; if benchmarks are needed for decision-making (e.g., choosing between routing options), put them in a referenced file.

Add validation and error handling steps: what happens if a hook fails, how to verify learning was recorded, what to do if quality degrades.

DimensionReasoningScore

Conciseness

The content is padded with marketing-style claims (+55% quality improvement, 761 decisions/sec, 2211 ops/sec) and benchmark statistics that don't help Claude execute any task. It explains what the system is rather than what to do, and includes capability lists that read like a product brochure rather than actionable instructions.

1 / 3

Actionability

The skill provides almost no executable guidance. The only concrete commands are two bash hook invocations, but there's no context for when/how to use them, what the output looks like, or how to handle errors. The rest is descriptive claims about performance characteristics with no actionable steps.

1 / 3

Workflow Clarity

There is no clear workflow or sequence of steps. The skill lists capabilities and benchmarks but never describes a process for actually using the system. There are no validation checkpoints, no error handling, and no feedback loops despite the system involving fine-tuning and continual learning operations.

1 / 3

Progressive Disclosure

The skill references an integration guide (docs/RUVECTOR_SONA_INTEGRATION.md) and a package, which is appropriate progressive disclosure. However, no bundle files are provided to support these references, and the main content that is inline is mostly fluff that could be removed rather than content that should be split into separate files.

2 / 3

Total

5

/

12

Passed

Description

0%Scale 1-3

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 essentially a placeholder that provides no useful information about the skill's purpose, capabilities, or appropriate usage context. It fails on every dimension because it only states an agent name and invocation command without describing any functionality or trigger conditions.

Suggestions

Add concrete actions describing what the skill does (e.g., 'Optimizes learning schedules, recommends study strategies, tracks knowledge retention').

Add an explicit 'Use when...' clause with natural trigger terms that users would actually say (e.g., 'Use when the user asks about learning plans, study optimization, or improving retention').

Replace the generic 'Agent skill for...' pattern with a substantive description that clearly distinguishes this skill from others in a multi-skill environment.

DimensionReasoningScore

Specificity

The description contains no concrete actions whatsoever. It only names an agent and an invocation command, with no indication of what the skill actually does.

1 / 3

Completeness

Neither 'what does this do' nor 'when should Claude use it' is answered. The description only provides an invocation command with no functional or contextual information.

1 / 3

Trigger Term Quality

There are no natural keywords a user would say. 'sona-learning-optimizer' is an opaque internal name that provides no semantic trigger terms related to any task or domain.

1 / 3

Distinctiveness Conflict Risk

The description is so vague that it provides no distinguishing characteristics. Without knowing what the skill does, it cannot be reliably differentiated from any other skill.

1 / 3

Total

4

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
ruvnet/claude-flow
Reviewed

Table of Contents

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