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agent-sona-learning-optimizer

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

27

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

35%

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

The body is padded with unverifiable benchmark claims and first-person marketing language rather than lean instruction, though it does provide some executable hook commands and a single-level reference. It would benefit from stripping performance numbers and adding concrete, copy-paste-ready guidance with validation steps.

Suggestions

Remove the benchmark tables and percentage-based performance claims, or move them to the referenced integration guide, to respect the token budget.

Replace abstract capability bullets ('Learn from every task execution') with concrete, executable steps showing exactly how to invoke and verify each capability.

Add validation checkpoints after the pre-task/post-task hooks (e.g. confirm the trajectory was recorded and check the task-id exists) to create a proper feedback loop.

DimensionReasoningScore

Conciseness

The body is padded with marketing-style claims and benchmark numbers ('+55% quality improvement', 'sub-millisecond learning overhead', throughput tables) that compete with the context window without adding actionable instruction.

1 / 3

Actionability

It provides concrete, executable hook commands, but the core capability instructions ('Learn from every task execution', 'Apply learned strategies to new tasks') remain abstract rather than executable.

2 / 3

Workflow Clarity

Pre-task and post-task hooks are sequenced, but there are no validation checkpoints or feedback loops confirming the learning trajectory was recorded successfully before proceeding.

2 / 3

Progressive Disclosure

The body is organized into sections and references one external doc (docs/RUVECTOR_SONA_INTEGRATION.md) at a single level, but the integration guide is mentioned without confirming it exists, and detail that could be split out remains inline.

2 / 3

Total

7

/

12

Passed

Description

0%

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 boilerplate template text that names no concrete actions, lacks any natural trigger terms, and omits any 'use when' guidance. It fails to communicate what the skill does or when Claude should invoke it.

Suggestions

Replace the template phrase with concrete actions the skill performs, e.g. 'Fine-tunes agent behavior via LoRA and preserves learned patterns with EWC++ memory.'

Add an explicit 'Use when...' clause with natural trigger terms users would actually say, such as 'continuous learning', 'fine-tuning', or 'avoiding catastrophic forgetting'.

Remove the internal invocation syntax '$agent-sona-learning-optimizer' from the user-facing description since it is not a natural trigger term.

DimensionReasoningScore

Specificity

The description 'Agent skill for sona-learning-optimizer - invoke with $agent-sona-learning-optimizer' names no concrete actions, only stating what the skill is for, matching the vague/abstract anchor.

1 / 3

Completeness

It weakly implies 'what' but provides no 'when to use it' trigger guidance, so it is missing the when clause entirely.

1 / 3

Trigger Term Quality

Terms like 'sona-learning-optimizer' and '$agent-sona-learning-optimizer' are internal jargon a user would never naturally say, with no natural trigger keywords present.

1 / 3

Distinctiveness Conflict Risk

The generic template phrasing 'Agent skill for ...' is not a distinctive, behavior-based description and reads as boilerplate that could apply to many skills.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
ruvnet/claude-flow
Reviewed

Table of Contents

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