Name: memory-systems
Rating: 53.6 (1 reviews)
Author: administrakt0r

memory-systems

Design short-term, long-term, and graph-based memory architectures. Use when building agents that must persist across sessions, needing to maintain entity consistency across conversations, or implementing reasoning over accumulated knowledge.

Quality

60%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/memory-systems/SKILL.md

The canonical home for this skill is memory-systems in administrakt0r/AI-Agents-Safe-Coding-Skills

Quality

Content

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

The body is a thorough but verbose conceptual survey that over-explains fundamentals Claude already knows, with only partial actionability from incomplete code examples and a broken reference to a non-existent implementation file. It reads more as a reference article than a lean skill.

Suggestions

Cut the conceptual re-explanation of memory fundamentals (context-memory spectrum, 'why simple vector stores fall short', KG basics) and keep only design decisions Claude would not infer.

Make code examples executable by defining or stubbing the referenced objects (memory, temporal_graph, now()) or framing them as interface contracts with concrete library calls.

Either create the referenced 'Implementation Reference' file under references/ and link it with a real path, or remove the dangling reference and move the benchmark table into a separate file.

Dimension	Reasoning	Score
Conciseness	The body extensively re-explains concepts Claude already knows (the context-memory spectrum, why vector stores fall short, what knowledge graphs are), with multiple padded sections that could be cut; it is noticeably verbose rather than maximally padded.	2 / 5
Actionability	Code examples exist but reference undefined objects (memory.store, temporal_graph.query, now()), and the implementation patterns are described abstractly ('Implementation uses the file system hierarchy...') without complete executable detail.	3 / 5
Workflow Clarity	The consolidation process lists a sequence ('Identify outdated facts, merge related facts, update validity periods, archive or delete obsolete facts, rebuild indexes') but has no validation checkpoints; this is a design skill so the destructive-cap does not apply.	3 / 5
Progressive Disclosure	Clear section headers provide structure, but no bundle files exist (references/ scripts/ assets/ absent), the cited 'Implementation Reference' points to no real file, and detailed material (benchmark tables, layer-by-layer exposition) that could be split remains inlined.	3 / 5
	Total	11 / 20 Passed

Description

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

The description cleanly answers both 'what' and 'when' with concrete, natural trigger phrases and a distinct niche. Its main weakness is a single action verb ('Design') with no enumerated concrete operations, which limits specificity.

Dimension	Reasoning	Score
Specificity	Names the domain ('short-term, long-term, and graph-based memory architectures') with the single action verb 'Design' but offers no further concrete actions, matching the anchor for 1-2 concrete actions without comprehensive coverage.	3 / 5
Completeness	Explicitly states what it does ('Design ... memory architectures') and when to use it ('Use when building agents that must persist across sessions...') with concrete trigger phrases, matching the top anchor.	5 / 5
Trigger Term Quality	Includes natural phrases a user would say ('persist across sessions', 'entity consistency across conversations', 'reasoning over accumulated knowledge') with good coverage, missing only a few common synonyms.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (memory architectures) with distinct triggers, with only minor overlap risk against closely related context/multi-agent skills.	4 / 5
	Total	16 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/memory-systems/SKILL.md
Commit: 57c135b

Reviewed: 3 days ago

Table of Contents

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