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 generic that it provides no distinguishing information. '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 (mcp__claude-flow__memory_usage store) six or seven times with minor variations in the JSON payload. The core concept—report status via memory store before/during/after tasks—could be conveyed in a fraction of the space. The pseudo-JavaScript syntax is neither valid JS nor clear MCP tool invocation syntax, reducing actionability.
Suggestions
Consolidate the repetitive memory store examples into one canonical pattern, then provide a concise table or list of the different key patterns and their expected JSON schemas for each worker type.
Fix the code syntax to be either valid MCP tool call format or valid JavaScript—the current hybrid (e.g., `const deps = await mcp__claude-flow__memory_usage { ... }`) is confusing and not executable.
Extract specialized worker type details (Code, Analysis, Testing) into a separate reference file and link to it from the main skill, keeping only the common execution protocol inline.
Add explicit validation/verification steps for task outputs (e.g., 'verify deliverables exist before marking complete') to strengthen the workflow for destructive or batch operations.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with repetitive JSON blocks that follow the same pattern (store to memory with slightly different payloads). The skill could be condensed to ~30% of its size by showing one memory store pattern and listing the different key/value schemas. Much of the content is redundant template code. | 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 for the actual work being done—no verify-output steps, no error recovery loops for failed task execution. The 'Emergency Response' and 'Parallel Collaboration' sections are vague with no concrete validation. | 2 / 3 |
Progressive Disclosure | The entire skill is a monolithic wall of text with no references to external files. All specialized worker types (code, analysis, testing) are inlined with full JSON examples when they could be split into separate reference files. The Integration Points section references other agents but provides no links or further documentation. | 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
ccb062f
- Reviewed
Table of Contents
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