agent-worker-specialist
Agent skill for worker-specialist - invoke with $agent-worker-specialist
44
13%
Does it follow best practices?
Impact
98%
10.88xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-worker-specialist/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 fails on every dimension. It provides no information about what the skill does, when it should be used, or what domain it operates in. It reads as a placeholder or auto-generated stub rather than a functional skill description.
Suggestions
Replace the entire description with concrete actions the skill performs, e.g., 'Delegates complex tasks to specialized worker agents for parallel processing' or whatever the actual functionality is.
Add an explicit 'Use when...' clause that describes the scenarios and trigger terms that should cause Claude to select this skill.
Include natural language keywords that users would actually say when they need this skill's functionality, rather than internal naming conventions like 'worker-specialist'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions whatsoever. 'Agent skill for worker-specialist' is entirely abstract with no indication of 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 how to invoke it, not what it does or when it should be selected. | 1 / 3 |
Trigger Term Quality | There are no natural keywords a user would say. 'Worker-specialist' is internal jargon, and 'invoke with $agent-worker-specialist' is a technical invocation command, not a trigger term. | 1 / 3 |
Distinctiveness Conflict Risk | The description is so vague that it provides no distinguishing characteristics. 'Worker-specialist' could refer to virtually anything, making it impossible to differentiate from other skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is excessively verbose, repeating the same memory coordination pattern across multiple nearly-identical code blocks that differ only in their JSON payload keys. The hybrid JavaScript/MCP tool call syntax is inconsistent and potentially confusing. While the overall structure (task execution, specialized types, dependency management, result delivery) is logical, the content would be far more effective at ~1/3 the length with a single pattern example and a table of key schemas.
Suggestions
Consolidate the repetitive memory store examples into one canonical pattern, then use a concise table or list to show the different key names and JSON schema fields for each worker type and status update.
Fix the code syntax to be consistently either MCP tool call format or JavaScript - the current hybrid (e.g., `const deps = await mcp__claude-flow__memory_usage { ... }`) is neither valid JS nor clear MCP invocation.
Split specialized worker types and integration points into a separate reference file, keeping SKILL.md as a concise overview with the core execution protocol.
Add explicit validation/verification steps after task completion (e.g., verify deliverables exist, confirm results stored successfully) to strengthen the workflow.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with repetitive JSON blocks that all follow the same pattern (store to memory with slightly different keys/values). The skill could be condensed to ~30% of its size by showing one example of the memory store pattern and listing the different key schemas. Much of the content is redundant template variations. | 1 / 3 |
Actionability | The code examples show specific MCP tool calls with concrete JSON structures, which is somewhat actionable. However, the JavaScript syntax is inconsistent (mixing await with non-function MCP calls, using const with MCP tool syntax), making the examples not truly executable. The placeholders like [ID] and [feature] are reasonable but the hybrid JS/MCP syntax is confusing. | 2 / 3 |
Workflow Clarity | The sequential execution pattern lists clear steps, and the dependency management section shows a check-before-proceed pattern. However, there are no explicit validation checkpoints after task execution, no error recovery feedback loops for failed tasks, and the 'Emergency Response' and 'Parallel Collaboration' sections are vague without concrete steps. | 2 / 3 |
Progressive Disclosure | The entire skill is a monolithic wall of text with no references to external files. All specialized worker types, work patterns, quality standards, integration points, and metrics are inlined despite being clearly separable concerns. The content would benefit greatly from splitting worker type templates and integration details into separate reference files. | 1 / 3 |
Total | 6 / 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
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