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 across multiple worker types without meaningful variation. The JavaScript/MCP syntax is inconsistent and not truly executable, reducing actionability. The content would benefit enormously from condensing the repeated patterns into a single template with a schema reference, and splitting specialized worker details into separate files.
Suggestions
Consolidate the repetitive MCP memory_usage examples into a single template pattern, then use a compact table or list to show the different key/value schemas for each worker type (code, analysis, testing, metrics).
Fix the JavaScript syntax to be either valid JS or clearly marked as pseudo-invocations—currently mixing `await` with non-function MCP tool calls creates confusion about how to actually use these tools.
Extract specialized worker types (Code, Analysis, Testing) into a separate WORKER_TYPES.md reference file, keeping only the core execution protocol and work patterns in the main skill.
Add explicit error recovery steps for task failures—e.g., what to store in memory when a task fails, how to retry, and when to escalate to the queen-coordinator.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with repetitive JSON blocks that follow the same pattern. The skill could be condensed to a fraction of its size by showing one memory coordination example and listing the different key/value schemas in a table. Much of the content is boilerplate that Claude could infer from a single example. | 1 / 3 |
Actionability | The code examples show specific MCP tool calls with concrete JSON schemas, 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 patterns are illustrative but not copy-paste ready. | 2 / 3 |
Workflow Clarity | The sequential execution pattern lists clear steps, and there's a dependency check workflow with a blocking report. However, validation checkpoints are weak—there's no explicit error recovery loop for failed tasks, and the 'Emergency Response' and 'Parallel Collaboration' sections are vague bullet points without concrete validation 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, and integration points are inlined despite the content being over 150 lines. The different worker types and detailed schemas could easily be split 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/claude-flow
- Commit
01070ed
- Reviewed
Table of Contents
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