projection-patterns
Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
Install with Tessl CLI
npx tessl i github:Dicklesworthstone/pi_agent_rust --skill projection-patterns82
Quality
73%
Does it follow best practices?
Impact
94%
1.77xAverage score across 3 eval scenarios
Optimize this skill with Tessl
npx tessl skill review --optimize ./tests/ext_conformance/artifacts/agents-wshobson/backend-development/skills/projection-patterns/SKILL.mdDiscovery
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 well-crafted description that clearly defines its niche in event-sourced architecture patterns. It excels at completeness with explicit 'Use when' guidance and includes strong domain-specific trigger terms. The main weakness is that the 'what' portion could be more specific about concrete actions beyond 'build'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (event streams, CQRS) and some actions ('build read models and projections'), but doesn't list multiple concrete actions like specific operations or techniques involved. | 2 / 3 |
Completeness | Clearly answers both what ('Build read models and projections from event streams') and when ('Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'read models', 'projections', 'event streams', 'CQRS', 'read sides', 'materialized views', 'query performance', 'event-sourced systems' - good coverage of domain terminology. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting CQRS/event-sourcing patterns with distinct triggers like 'read models', 'projections', 'event streams' - unlikely to conflict with general database or coding skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides excellent, actionable code templates for building event-sourced projections with real-world patterns. However, it suffers from being a monolithic document that should be split into an overview with linked template files. The workflow guidance for rebuilding and error recovery could be strengthened with explicit validation steps.
Suggestions
Split the 5 code templates into separate files (e.g., TEMPLATES/basic_projector.py, TEMPLATES/elasticsearch_projection.py) and reference them from the main skill
Add explicit validation workflow for projection rebuilds: how to verify data consistency, handle partial failures, and confirm successful completion
Add a 'Troubleshooting' section covering common projection issues: lag detection, checkpoint corruption recovery, and idempotency verification
Trim the 'When to Use This Skill' section - Claude can infer these use cases from the content
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is comprehensive but includes some unnecessary verbosity. The 'Core Concepts' section with the ASCII diagram and projection types table adds value, but the extensive code templates (5 full implementations) could be trimmed or moved to separate files. Some explanatory text like 'Comprehensive guide to building projections' is filler. | 2 / 3 |
Actionability | Excellent actionability with fully executable Python code templates. Each template is complete with imports, class definitions, and SQL queries that are copy-paste ready. The code covers real-world scenarios (Elasticsearch, PostgreSQL, multi-table updates) with concrete implementations. | 3 / 3 |
Workflow Clarity | While the templates show individual operations clearly, the skill lacks explicit validation checkpoints for the rebuild process and error recovery workflows. The 'rebuild' method exists but there's no guidance on verifying projection correctness after rebuild, handling partial failures, or validating data consistency. | 2 / 3 |
Progressive Disclosure | This is a monolithic 400+ line file with all content inline. The five detailed templates should be in separate files with the main SKILL.md providing an overview and links. The external resources at the end are good but the internal structure lacks progressive disclosure. | 1 / 3 |
Total | 8 / 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
Table of Contents
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