Generate eval scenarios from repo commits, configure multi-agent runs, execute baseline + with-context evals, and compare results — the full setup pipeline before improvement begins
94
94%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
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 a strong skill description that clearly articulates specific capabilities around evaluation pipeline management and multi-agent benchmarking. It uses third person voice correctly, provides concrete actions, and includes an explicit 'Use when...' clause with natural trigger terms. The combination of git-based scenario generation with agent evaluation creates a distinctive niche.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Generate eval scenarios from repo commits', 'configure multi-agent runs', 'execute baseline + with-context evals', and 'compare results'. These are distinct, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what (generate eval scenarios, configure runs, execute evals, compare results) AND when with explicit 'Use when...' clause covering evaluation pipelines, benchmarks, agent performance comparison, and test scenario generation. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'evaluation pipelines', 'benchmarks', 'agent performance', 'models', 'test scenarios', 'git history'. Good coverage of terms across evaluation and testing domains. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining evaluation/benchmarking with multi-agent systems and git-based scenario generation. The combination of 'eval scenarios from repo commits' and 'multi-agent runs' creates a distinct trigger profile unlikely to conflict with general testing or git skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%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 orchestration skill with excellent progressive disclosure and workflow clarity. The phase-based approach with clear decision tables and stopping conditions is strong. The main weakness is that actionability depends entirely on the referenced files - the main skill file contains no executable commands or concrete examples.
Suggestions
Add at least one concrete command example in the main file (e.g., the `tessl scenario generate` or `tessl eval run` command syntax) so the skill is partially actionable without loading references
Include a minimal quick-start example showing the most common single-command flow for users who want to skip the interactive scope selection
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is lean and efficient, providing just enough context to understand each phase without explaining concepts Claude already knows. Time expectations are practical additions, not padding. | 3 / 3 |
Actionability | The skill provides clear phase structure and decision tables, but all concrete implementation details are deferred to reference files. The main file lacks executable commands or code examples. | 2 / 3 |
Workflow Clarity | Excellent multi-step workflow with clear phase sequencing, a decision table mapping user choices to phases, explicit stopping conditions, and quality-check gates (Phase 4 rubric anti-patterns) before proceeding. | 3 / 3 |
Progressive Disclosure | Exemplary structure with a clear overview, well-signaled one-level-deep references to phase-specific files, and appropriate content splitting. Each phase links to exactly one reference file. | 3 / 3 |
Total | 11 / 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.
Reviewed
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