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conversation-memory

Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.

Quality

56%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

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

SKILL.md
Quality
Evals
Security

Quality

Content

22%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.

The body is a hollow skeleton: section headers promise substance (patterns, anti-patterns, sharp edges) but nearly all content is either empty, truncated mid-sentence, or placeholder comments. A reader learns the vocabulary of memory systems but nothing about how to actually build or operate one.

Suggestions

Give each Pattern and Anti-Pattern real content — concrete storage schemas, retrieval/relevance strategies, and consolidation triggers with small code or config examples instead of one-line glosses and empty headings.

Replace the placeholder solutions in the Sharp Edges table with actionable steps (e.g., a TTL/eviction policy for unbounded growth, a per-user namespace key scheme for isolation).

Delete the persona preamble and the circular 'When to Use' line, and complete the truncated 'core principles' list — the freed tokens should fund the actionable content above.

DimensionReasoningScore

Conciseness

Several sections are pure padding that add nothing Claude doesn't know: the persona preamble ('You're a memory systems specialist... memory is not just storage—it's about retrieval, relevance, and context') restates general knowledge, and 'When to Use' is circular filler ('This skill is applicable to execute the workflow or actions described in the overview'). Below anchor 3 because the unnecessary content is not incidental — it is a noticeable share of the body, including an anti-patterns section made only of empty headers.

2 / 5

Actionability

No code, commands, schemas, or concrete procedures appear anywhere. The Patterns section is one-line glosses ('Different memory tiers for different purposes') and the Sharp Edges 'solutions' are placeholder comments ('// Implement memory lifecycle management', '// Strict user isolation in memory'). Above anchor 1 only because the table names specific, real failure modes (unbounded growth, cross-user leakage) with severities — high-level hints, but no executable steps.

2 / 5

Workflow Clarity

No multi-step process is ever laid out — no sequence for designing, storing, retrieving, or consolidating memories, and the only numbered list ('Your core principles: 1. Memory types differ—short-term, lo') is literally truncated mid-word. There is no validation or verification guidance despite the skill covering batch/memory operations, matching anchor 1 (steps missing or incoherent; no sequence).

1 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/ directories) and the body references none, which is acceptable for a short skill — but the in-file organization does not earn a 5: the three Anti-Patterns headings have zero content beneath them, 'Capabilities' is a bare hyphenated noun list, and a truncated line breaks the Principles section. This matches anchor 3 ('some structure but could be better organized').

3 / 5

Total

8

/

20

Passed

Description

70%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 solid, appropriately brief description that clearly delimits the domain and includes explicit trigger terms. Its main weakness is that it describes a topic (types of memory) rather than what the skill actually does, leaving the capability statement implicit.

Suggestions

Replace the passive noun phrase with third-person action statements, e.g. 'Implements short-term, long-term, and entity-based memory for LLM conversations: storing, retrieving, and consolidating facts across sessions.'

Add a few missing natural trigger synonyms such as 'recall', 'persist user preferences', or 'remember me across sessions' to broaden when-matching without adding length.

DimensionReasoningScore

Specificity

The description states a clear domain ('Persistent memory systems for LLM conversations') and enumerates concrete scope ('short-term, long-term, and entity-based memory'), but contains no action verbs at all — it names what exists, not what the skill does. It sits above anchor 2 ('names the domain but actions are minimal or generic') because the three-type enumeration is concrete, but below anchor 4 because no specific capabilities (e.g., storing, retrieving, consolidating memories) are stated.

3 / 5

Completeness

Both parts are present: a 'what' ('Persistent memory systems... including short-term, long-term, and entity-based memory') and an explicit 'Use when:' clause with concrete trigger terms. Below anchor 5 because the 'what' is a static noun phrase rather than stated capabilities, and the trigger list is terse keywords rather than explicit user-scenario phrasing.

4 / 5

Trigger Term Quality

'conversation memory, remember, memory persistence, long-term memory, chat history' are terms users would naturally say. Below anchor 5 because common synonyms and variations are missing ('recall', 'persist user preferences', 'entity memory', 'remember me across sessions').

4 / 5

Distinctiveness Conflict Risk

The LLM-conversation-memory niche is well differentiated from adjacent skills. Minor overlap risk remains: 'remember' and 'chat history' are broad terms that could also fire for note-taking, preference-saving, or context-window skills, keeping it below anchor 5.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

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/conversation-memory/SKILL.md

Reviewed

Table of Contents

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