agent-safla-neural

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

3.03x

Quality

Does it follow best practices?

Impact

100%

3.03x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-safla-neural/SKILL.md

Quality

Content

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 brochure than actionable technical guidance. It is filled with vague capability claims, unexplained metrics, and conceptual descriptions that Claude already understands. The code examples are not executable, use non-standard syntax, and reference undefined variables, making them useless as practical guidance.

Suggestions

Replace the capability bullet list and four-tier memory model description with concrete, executable code examples showing how to actually initialize, store, retrieve, and update memory using the MCP tools.

Provide a clear step-by-step workflow for a common task (e.g., 'Creating a persistent learning agent') with numbered steps, specific MCP commands, and validation checkpoints.

Fix the MCP integration examples to use correct, executable syntax with properly defined parameters and realistic placeholder values.

Remove marketing-style claims (172,000+ ops/sec, 60% compression) and conceptual explanations that don't contribute to actionable guidance.

Dimension	Reasoning	Score
Conciseness	Extremely verbose with extensive explanations of concepts Claude already knows (what vector memory is, what episodic memory is, what working memory is). The capability bullet list is padded with marketing-style claims ('172,000+ operations per second', '60% compression') that are not actionable. The four-tier memory model description is purely conceptual with no executable value.	1 / 3
Actionability	The MCP integration examples use non-standard JavaScript-like syntax that is not executable (missing quotes on keys, using template literals without backticks properly, referencing undefined variables like `interaction_context`, `result_metrics`). Most of the content describes capabilities rather than providing concrete, copy-paste-ready instructions for accomplishing tasks.	1 / 3
Workflow Clarity	There is no clear multi-step workflow, no sequencing of operations, and no validation checkpoints. The skill describes what the agent supposedly does but never explains how to actually accomplish any task step by step. The two code snippets are isolated examples with no connection to a coherent workflow.	1 / 3
Progressive Disclosure	The content is a monolithic wall of text with no references to supporting files, no clear navigation structure, and no separation between overview and detailed content. There are no bundle files to support progressive disclosure, and the inline content mixes high-level description with incomplete code examples without clear organization.	1 / 3
	Total	4 / 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 an extremely weak description that provides virtually no useful information. It only states it is an 'agent skill' with a name and invocation command, but fails to describe any capabilities, actions, use cases, or trigger conditions. This description would be essentially useless for Claude when selecting among multiple available skills.

Suggestions

Add concrete actions describing what safla-neural actually does (e.g., 'Performs neural network analysis, trains models, evaluates embeddings' or whatever its actual capabilities are).

Add an explicit 'Use when...' clause with natural trigger terms that describe the situations and user requests where this skill should be selected.

Replace the generic 'Agent skill for safla-neural' framing with a domain-specific summary that distinguishes this skill from others (e.g., 'Manages neural memory indexing and semantic search for the SAFLA framework').

Dimension	Reasoning	Score
Specificity	The description contains no concrete actions whatsoever. 'Agent skill for safla-neural' is entirely vague and abstract, 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 ('$agent-safla-neural') with no explanation of purpose or trigger conditions.	1 / 3
Trigger Term Quality	The only keyword is 'safla-neural', which is technical jargon that no user would naturally say. There are no natural language trigger terms that would help Claude match user requests to this skill.	1 / 3
Distinctiveness Conflict Risk	While 'safla-neural' is a unique term, the description is so vague ('Agent skill') that it provides no meaningful differentiation. Claude would have no basis to distinguish when to use this skill versus any other agent skill.	1 / 3
	Total	4 / 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/ruflo
Commit: 28c81c0

Reviewed: about 19 hours ago

Table of Contents

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