agent-safla-neural

Agent skill for safla-neural - invoke with $agent-safla-neural

3.03x

Quality

15%

Does it follow best practices?

Impact

100%

3.03x

Average score across 3 eval scenarios

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.agents/skills/agent-safla-neural/SKILL.md

Quality

Content

22%

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

The content reads as a persona/manifesto with concept explanations and pseudocode examples rather than actionable, sequenced guidance. It assumes little of Claude's knowledge and provides no workflow or validation steps for the complex operations it claims to support.

Suggestions

Cut the conceptual memory-tier explanations and buzzword capability list; assume Claude knows what vector/episodic memory is and keep only the non-obvious specifics.

Replace the pseudocode MCP blocks with real, executable invocation syntax and show the concrete sequence a user would follow.

Add a numbered workflow with validation checkpoints for the core task (e.g. train -> store -> verify persistence) so Claude knows exactly what to do.

Dimension	Reasoning	Score
Conciseness	The body explains concepts Claude already knows (the four-tier memory model with definitions of vector/episodic/semantic/working memory), is padded with buzzword capabilities ('quantum, and chaotic neural patterns'), and even contains a stray duplicate YAML frontmatter block as noise.	1 / 3
Actionability	The MCP examples give concrete-ish invocation patterns, but they are pseudocode (invalid JS/MCP syntax like 'mcp__claude-flow__neural_train { ... }') rather than executable code, and the capability list describes rather than instructs.	2 / 3
Workflow Clarity	There is no sequenced workflow, no steps, and no validation checkpoints for any of the many claimed capabilities; the content is a persona statement plus reference material rather than a process.	1 / 3
Progressive Disclosure	The body has recognizable sections (capabilities, memory architecture, MCP examples) and needs no external references, but it is a monolithic single-file wall with the stray frontmatter block and no clear navigation to deeper material.	2 / 3
	Total	6 / 12 Passed

Description

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 is a placeholder-style description that identifies the skill by name but does not explain what it does or when to use it. It fails to give Claude any basis for deciding to invoke it.

Suggestions

Replace the description with concrete actions the skill performs (e.g. 'designs multi-tier memory systems, orchestrates distributed neural training, implements feedback loops').

Add an explicit 'Use when...' clause with natural trigger terms a user would actually say, such as 'self-learning agents', 'persistent memory', or 'feedback-loop training'.

State the value/outcome in third person and drop the 'invoke with $agent-safla-neural' invocation hint, which is not a trigger.

Dimension	Reasoning	Score
Specificity	The description 'Agent skill for safla-neural - invoke with $agent-safla-neural' names a domain but lists no concrete actions, matching the 'vague or no actions' anchor rather than the score-2 anchor which requires 'some actions'.	1 / 3
Completeness	It barely states what the skill is (just 'agent skill for safla-neural') and has no 'Use when...' or equivalent trigger guidance, so both what and when are weak.	1 / 3
Trigger Term Quality	'safla-neural' is an internal skill identifier and 'invoke with $agent-safla-neural' is an invocation instruction, not natural language a user would say when they need this skill.	1 / 3
Distinctiveness Conflict Risk	The named 'safla-neural' niche gives it some specificity, but with no capability or trigger description it could still overlap with other neural/AI skills.	2 / 3
	Total	5 / 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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: ruvnet/ruflo
Path: .agents/skills/agent-safla-neural/SKILL.md
Commit: 26c35b5

Reviewed: about 6 hours ago

Table of Contents

Discovery Implementation Validation

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.