CtrlK
BlogDocsLog inGet started
Tessl Logo

agent-safla-neural

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

36

3.03x
Quality

0%

Does it follow best practices?

Impact

100%

3.03x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

0%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 as a marketing description or persona prompt rather than an actionable skill document. It spends most of its tokens describing abstract capabilities and architectural concepts that Claude already understands, while providing no concrete, executable workflows. The code examples are non-functional pseudocode with undefined variables and non-standard syntax.

Suggestions

Replace the abstract capability list and four-tier memory description with concrete, executable MCP tool invocations showing real workflows (e.g., 'To create a persistent memory pattern: 1. Initialize with mcp__claude-flow__neural_train(...) 2. Validate with... 3. Store results with...')

Provide actual executable code examples with proper syntax and defined variables instead of pseudocode with placeholders like `interaction_context` and `result_metrics`

Add a clear multi-step workflow with validation checkpoints for at least one core task (e.g., setting up a feedback loop, training a neural pattern, or configuring persistent memory)

Remove the persona description and marketing-style capability bullets ('172,000+ operations per second', '60% compression') and replace with concise, actionable instructions that assume Claude's competence

DimensionReasoningScore

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 reads like marketing copy ('172,000+ operations per second', '60% compression') rather than actionable instructions. The four-tier memory model description is purely conceptual padding.

1 / 3

Actionability

The MCP integration examples use non-standard JavaScript-like syntax that isn't executable (no proper function call syntax, uses undefined variables like `interaction_context`, `result_metrics`, `timestamp`). The bulk of the content describes capabilities and architecture abstractly rather than providing concrete, copy-paste-ready instructions for accomplishing tasks.

1 / 3

Workflow Clarity

There is no clear workflow or sequenced process. The skill describes what the agent supposedly can do but never explains how to actually accomplish any task step by step. No validation checkpoints, no error recovery, no feedback loops despite claiming to be about feedback loops.

1 / 3

Progressive Disclosure

Monolithic wall of text with no references to external files, no clear navigation structure, and no separation of overview from detailed content. Everything is dumped into a single file with no bundle files to support it.

1 / 3

Total

4

/

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 is an extremely weak description that fails on every dimension. It provides no information about what the skill does, when it should be used, or what user requests should trigger it. It reads more like a label or invocation instruction than a functional description.

Suggestions

Add concrete actions describing what safla-neural actually does (e.g., 'Performs neural network analysis', 'Processes embeddings', etc.).

Add a 'Use when...' clause with explicit trigger conditions and natural language terms users would say when they need this skill.

Include domain-specific keywords and common variations that would help Claude distinguish this skill from others in a large skill library.

DimensionReasoningScore

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 states it's an 'agent skill' and how to invoke it, which is neither a capability description nor a trigger condition.

1 / 3

Trigger Term Quality

The only keyword is 'safla-neural', which is technical jargon that a user would not naturally say. There are no natural language trigger terms that would help Claude match user requests to this skill.

1 / 3

Distinctiveness Conflict Risk

The description is so generic ('Agent skill') that it provides no distinguishing characteristics. Without knowing what the skill does, it could conflict with any other agent skill or be entirely ignored.

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

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.