agent-automation-smart-agent
Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent
35
0%
Does it follow best practices?
Impact
99%
1.07xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-automation-smart-agent/SKILL.mdQuality
Discovery
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.
This is an extremely weak description that provides essentially no useful information for skill selection. It only contains the skill's internal name and invocation command, with no description of capabilities, use cases, or trigger conditions. It would be nearly impossible for Claude to correctly select this skill from a pool of available skills.
Suggestions
Add a clear statement of what the skill does with specific concrete actions (e.g., 'Automates browser interactions, runs scheduled tasks, and orchestrates multi-step workflows').
Add an explicit 'Use when...' clause with natural trigger terms that describe scenarios where this skill should be selected (e.g., 'Use when the user asks to automate repetitive tasks, schedule jobs, or create workflow pipelines').
Replace the generic 'automation-smart-agent' label with a meaningful description of the skill's unique niche to distinguish it from other automation-related skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions whatsoever. 'Agent skill for automation-smart-agent' is entirely vague and abstract, providing no information about what the skill actually does. | 1 / 3 |
Completeness | Neither 'what does this do' nor 'when should Claude use it' is answered. The description only states the invocation command, providing no functional or contextual information. | 1 / 3 |
Trigger Term Quality | There are no natural keywords a user would say. 'automation-smart-agent' is an internal identifier, not a term users would naturally use in requests. The only instruction is how to invoke it, not when. | 1 / 3 |
Distinctiveness Conflict Risk | The term 'automation' is extremely generic and could overlap with virtually any automation-related skill. There is nothing distinctive about this description to differentiate it from other skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%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 high-level product specification or marketing document rather than an actionable skill file. It describes aspirational capabilities (predictive spawning, ML integration, multi-objective optimization) without providing any concrete implementation, commands, or executable guidance. Claude would gain almost no actionable knowledge from this content.
Suggestions
Replace abstract descriptions with concrete, executable commands or code that Claude can actually run to spawn/coordinate agents (e.g., specific CLI commands, API calls, or function invocations).
Define a clear step-by-step workflow: 1) Analyze task → 2) Select agent type → 3) Spawn with specific command → 4) Validate spawning succeeded → 5) Monitor, with explicit validation checkpoints.
Remove aspirational features that aren't implemented (ML integration, predictive spawning, workload forecasting) or move them to a separate roadmap file — they waste tokens without adding actionable value.
Cut the content by at least 60% — remove sections like 'Best Practices', 'Common Pitfalls', and conceptual diagrams, keeping only what Claude needs to execute the coordination task.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~150+ lines, mostly describing abstract concepts and aspirational features rather than providing actionable instructions. Explains things like 'Natural language understanding of requirements' and 'Complexity assessment' which are vague filler. The content reads like a product brochure, not a skill file. | 1 / 3 |
Actionability | No executable code or concrete commands anywhere. The code blocks are pseudocode/diagrams showing conceptual flows (e.g., 'Task Requirements → Capability Analysis → Agent Selection'). The Python and JavaScript blocks are abstract schemas, not runnable code. Claude would not know what specific commands to run or what tools to invoke. | 1 / 3 |
Workflow Clarity | No clear step-by-step workflow for how to actually coordinate agents. The 'Automation Patterns' section describes desired outcomes but not how to achieve them. No validation checkpoints, no error handling steps, no concrete sequencing of operations. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files. All content is inline with no clear hierarchy for discovery. Sections like 'Machine Learning Integration' and 'Advanced Features' add bulk without being actionable or pointing to detailed resources. | 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- ruvnet/ruflo
- Commit
398f7c2
- 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.