memory-systems
Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph for agents", "track entities over time", "add long-term memory", "choose a memory framework", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory or memory benchmarks (LoCoMo, LongMemEval).
94
92%
Does it follow best practices?
Impact
Pending
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 with named frameworks, comprehensive trigger terms covering both natural language and technical terminology, explicit 'Use when...' guidance, and a clearly defined niche that distinguishes it from related skills. The description uses proper third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple concrete actions: 'guides implementation', 'compares production frameworks' (with specific names: Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and 'designs persistence architectures'. The framework names add significant specificity. | 3 / 3 |
Completeness | Clearly answers both what (guides implementation, compares frameworks, designs architectures) AND when with an explicit 'Use when...' clause containing multiple specific trigger phrases and scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'implement agent memory', 'persist state across sessions', 'build knowledge graph', 'add long-term memory', 'choose a memory framework', plus technical terms like 'temporal knowledge graphs', 'vector stores', 'entity memory', and benchmark names. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche focused specifically on agent memory systems with named frameworks and specific concepts (temporal knowledge graphs, LoCoMo, LongMemEval benchmarks). Unlikely to conflict with general coding or database 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 strong, comprehensive skill that provides actionable framework selection guidance backed by benchmark data. The code examples are executable and the workflow for choosing memory architectures is clear. Minor verbosity in the opening sections and some redundancy in framework descriptions prevent a perfect conciseness score, but overall the skill effectively balances depth with usability.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is generally efficient but includes some unnecessary explanation (e.g., the opening paragraph explaining what memory is, some redundant framework descriptions). The benchmark tables and comparison content earn their place, but sections like 'Core Concepts' could be tighter. | 2 / 3 |
Actionability | Provides concrete, executable code examples for Mem0, temporal queries, and Cognee. The framework comparison table gives specific selection criteria, and the escalation path (prototype → scale → complex reasoning → full control) is actionable guidance. | 3 / 3 |
Workflow Clarity | Clear escalation path for choosing memory architecture with explicit decision points. Error recovery section provides ordered strategies with specific conditions. The 'Choosing a Memory Architecture' section gives a clear 4-step workflow with validation criteria for when to escalate. | 3 / 3 |
Progressive Disclosure | Well-structured with clear sections (Core Concepts → Detailed Topics → Practical Guidance → Examples → Guidelines → Gotchas). References external files appropriately (implementation.md) and links to related skills. Content is appropriately split between overview and detailed reference material. | 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
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