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memory-systems

This skill should be used for persistent semantic memory in agent systems: cross-session knowledge retention, entity tracking, temporal validity, graph or vector retrieval, memory consolidation, and memory benchmark selection. Route file-backed scratchpads to filesystem-context, handoff summaries to context-compression, and token-efficiency tactics to context-optimization.

64

Quality

76%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/memory-systems/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Well-structured and largely actionable content with strong comparison tables and example code, weakened by some conceptual padding, undefined variables in examples, and missing validation checkpoints in the consolidation workflow.

Suggestions

Trim the intro paragraph and Core Concepts section to remove general memory concepts Claude already knows, keeping only the skill-specific decision rules.

Add explicit validate→fix→retry checkpoints to the Memory Consolidation workflow, since merging/invalidating memories is a destructive batch operation.

Link scripts/memory_store.py from the body (e.g., in Memory Consolidation or References) and make code examples copy-paste-ready by defining the 'graph' variable or noting it comes from the bundled script.

DimensionReasoningScore

Conciseness

The body is mostly efficient with high-signal tables and guidance, but the opening paragraph and Core Concepts section explain general memory concepts Claude already knows, and table commentary could be tightened.

3 / 5

Actionability

It provides concrete, mostly executable code blocks (Mem0, Cognee) and specific field-level recovery guidance, but some examples use undefined variables ('graph') or placeholder strings ('any data') that prevent fully copy-paste-ready execution.

4 / 5

Workflow Clarity

The escalation path and error-recovery list give a clear ordered sequence, but the memory-consolidation workflow (a destructive/batch operation) lacks explicit validate→fix→retry checkpoints, capping clarity at 3.

3 / 5

Progressive Disclosure

Good structure with a well-signaled one-level reference to references/implementation.md for code, but the bundled scripts/memory_store.py is not referenced from the body, leaving a minor discoverability gap.

4 / 5

Total

14

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states both what it does and when to use it, with explicit routing to distinguish it from neighboring skills. Minor room to add common synonyms or extensions for even richer trigger coverage.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete capabilities — 'cross-session knowledge retention, entity tracking, temporal validity, graph or vector retrieval, memory consolidation, and memory benchmark selection' — covering the skill's scope comprehensively.

5 / 5

Completeness

It answers both 'what' (persistent semantic memory with the enumerated capabilities) and 'when' ('This skill should be used for...') with concrete trigger phrases and explicit routing guidance.

5 / 5

Trigger Term Quality

Strong coverage of natural domain phrases ('persistent semantic memory', 'entity tracking', 'memory consolidation') but limited synonym or extension variation compared to the broad-synonym ideal, so a few natural terms are effectively missing.

4 / 5

Distinctiveness Conflict Risk

It carves a clear niche (persistent semantic memory) and explicitly routes adjacent work away ('Route file-backed scratchpads to filesystem-context, handoff summaries to context-compression'), minimizing conflict risk.

5 / 5

Total

19

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
muratcankoylan/Agent-Skills-for-Context-Engineering
Reviewed

Table of Contents

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