spawn
Generate PhD-level expert agent prompts for Claude Code. Creates comprehensive 500-1000 line agents with detailed patterns, code examples, and best practices. Triggers on: spawn agent, create agent, generate expert, new agent, agent genesis.
74
62%
Does it follow best practices?
Impact
94%
1.84xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./data/skills-md/0xdarkmatter/claude-mods/spawn/SKILL.mdQuality
Discovery
89%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 a solid description that clearly communicates its purpose and includes explicit trigger terms. The main weakness is that the capability description relies on somewhat vague qualifiers ('PhD-level', 'comprehensive', 'best practices') rather than listing more concrete actions. Overall it performs well for skill selection purposes.
Suggestions
Replace vague qualifiers like 'PhD-level' and 'best practices' with more concrete actions, e.g., 'Generates agent prompts with tool-use patterns, error handling strategies, multi-step reasoning flows, and domain-specific code examples.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (agent prompt generation) and some actions ('Creates comprehensive 500-1000 line agents with detailed patterns, code examples, and best practices'), but the actions are somewhat vague — 'detailed patterns' and 'best practices' are not concrete enough to fully qualify as specific actions. | 2 / 3 |
Completeness | Clearly answers both 'what' (generates PhD-level expert agent prompts with detailed patterns, code examples, and best practices) and 'when' (explicit 'Triggers on:' clause with specific trigger phrases). | 3 / 3 |
Trigger Term Quality | Includes explicit trigger terms ('spawn agent', 'create agent', 'generate expert', 'new agent', 'agent genesis') that are natural phrases a user would say when needing this skill. Good coverage of variations. | 3 / 3 |
Distinctiveness Conflict Risk | The niche is very specific — generating expert agent prompts for Claude Code — with distinct trigger terms like 'agent genesis' and 'spawn agent' that are unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is highly verbose and repetitive, explaining the same concepts (scope, file paths, YAML frontmatter) multiple times throughout. While it provides a structured 10-part template and clear mode distinctions, the actual actionable content is diluted by excessive documentation of concepts Claude already understands. The skill would benefit enormously from being cut to ~40% of its current length with detailed references moved to separate files.
Suggestions
Eliminate repeated explanations of project vs global scope, file paths, and YAML frontmatter - mention each concept once and reference it thereafter
Move the Claude Code Agent Documentation links section and YAML frontmatter field documentation to a separate reference file (e.g., AGENT-FORMAT-REFERENCE.md)
Replace the hypothetical UI interaction examples with a concrete example of actual generated agent content (showing input platform + abbreviated output)
Add an explicit validation step in the workflow: after generation, verify the agent meets minimum thresholds (line count, URL count, code block count) before saving
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~300+ lines. Extensively explains concepts Claude already knows (what YAML frontmatter is, how file paths work, what markdown is). The documentation links section, repeated scope explanations, and lengthy examples with mock UI interactions add significant bloat. The same information about project vs global scope is repeated 5+ times. | 1 / 3 |
Actionability | Provides a concrete 10-part template structure and specific file paths, which is useful. However, the actual code examples are minimal - mostly showing file path patterns rather than executable generation logic. The 'examples' section shows hypothetical UI interactions rather than concrete input/output of generated agent content. | 2 / 3 |
Workflow Clarity | The Implementation Steps section provides a clear sequence for the three modes, and the Quality Checklist serves as a validation checkpoint. However, there are no explicit validation/feedback loops for the generation process itself - no steps for verifying generated content quality, no error recovery if generation fails or produces subpar output, and the checklist is a post-hoc review rather than an integrated validation step. | 2 / 3 |
Progressive Disclosure | References benchmark agents (python-expert.md, react-expert.md) and external documentation links, which is good. However, the skill itself is monolithic - the 10-part template, YAML frontmatter documentation, Claude Code agent documentation, and implementation steps could all be split into referenced files. The inline documentation links section is essentially a reference dump that belongs in a separate file. | 2 / 3 |
Total | 7 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- NeverSight/skills_feed
- Commit
f772de4
- Reviewed
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