endor-troubleshoot
Troubleshoot Endor Labs scan errors and failures. Use when the user says "scan failed", "why did the scan fail", "endor troubleshoot", "fix scan error", "diagnose error", or pastes an error message from a failed scan. Matches errors against known patterns across NPM, Maven, PyPI, Go, Cargo, NuGet, RubyGems, and Packagist. Do NOT use for setup issues (/endor-setup) or general scanning (/endor-scan).
72
88%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%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 excellent skill description that hits all the marks. It provides specific capabilities, comprehensive natural trigger terms, explicit 'Use when' guidance, and clear negative boundaries to distinguish it from related skills. The inclusion of supported ecosystems and explicit exclusions makes it particularly strong for skill selection in a multi-skill environment.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists concrete actions: troubleshoot scan errors, match errors against known patterns, and specifies supported ecosystems (NPM, Maven, PyPI, Go, Cargo, NuGet, RubyGems, Packagist). Also explicitly states what it does NOT handle. | 3 / 3 |
Completeness | Clearly answers both 'what' (troubleshoot Endor Labs scan errors, match against known patterns across multiple ecosystems) and 'when' (explicit 'Use when...' clause with specific trigger phrases). Also includes negative boundaries for disambiguation. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms: 'scan failed', 'why did the scan fail', 'endor troubleshoot', 'fix scan error', 'diagnose error', and 'pastes an error message from a failed scan' — these are phrases users would naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with explicit negative boundaries ('Do NOT use for setup issues (/endor-setup) or general scanning (/endor-scan)'), clearly carving out its niche from related Endor Labs skills and minimizing conflict risk. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured troubleshooting skill with clear workflow steps, concrete resolution patterns, and good actionability. The ecosystem detection table and structured diagnosis output template make it immediately usable. Minor weaknesses include some inline content that could be offloaded to reference files and the inability to verify referenced bundle files exist.
Suggestions
Verify that references/error-knowledge-base.md and references/data-sources.md exist in the bundle, or include them — the skill's core matching logic (Step 3) depends entirely on the knowledge base file.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient with good use of tables and structured formatting, but some sections like the ecosystem detection table and common resolution patterns could be tighter. The output template includes template variables and conditional blocks that add bulk but serve a purpose. | 2 / 3 |
Actionability | Provides concrete, specific guidance throughout: exact MCP tool invocations with parameters, specific file paths to check (~/.endorctl/config.yaml), specific env var names, exact commands (rm -rf ~/.endorctl), links to relevant docs, and clear resolution patterns per category. The diagnosis output template is copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear 5-step sequential workflow (detect ecosystem → classify → match patterns → present diagnosis → handle multiple errors) with explicit priority ordering for multiple errors, a feedback loop via re-scan after fix, and an error handling table covering edge cases. The auth conflict resolution provides a clear decision tree. | 3 / 3 |
Progressive Disclosure | References external files (references/error-knowledge-base.md, references/data-sources.md) and other skills (/endor-setup, /endor-scan) appropriately, but no bundle files were provided to verify these exist. The main SKILL.md contains a good amount of inline content that could potentially be split out (e.g., the full ecosystem detection table, common resolution patterns), though it's not egregiously long. | 2 / 3 |
Total | 10 / 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
- endorlabs/skills-ideas
- Commit
b958adc
- 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.