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agent-memory-systems

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.

47

Quality

50%

Does it follow best practices?

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SecuritybySnyk

Passed

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

Quality

Content

46%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 lean, well-organized index page with exemplary one-level-deep reference signaling, but it delegates everything to the reference file: no concrete guidance, decision rules, or quick-start material survives in the body, and it wastes tokens duplicating the description verbatim. The Example section is circular and adds no value. The single 1088-line reference file works but would navigate better split by topic.

Suggestions

Add a small amount of concrete in-body guidance — e.g. a memory-type selection table (semantic/episodic/procedural → when to use) or a minimal LangMem/vector-store quick-start snippet — so the body is actionable without opening the reference.

Delete the opening paragraph that duplicates the description verbatim and tighten the 'Key insight' editorializing; the body should start with the guide pointer and When-to-Use triggers.

Replace the circular Example ('Use @agent-memory-systems for this task: Memory is the cornerstone...') with a real user request, and consider splitting detailed-guide.md into topical files (frameworks, vector stores, chunking, decay) for easier focused loading.

DimensionReasoningScore

Conciseness

The opening paragraph duplicates the frontmatter description verbatim ('Memory is the cornerstone... every interaction starts from zero... organize them'), and the 'Key insight' paragraph is editorial padding, though the CoALA terminology note is defensible field-specific knowledge. This matches anchor 3 — mostly efficient but includes unnecessary explanation that could be tightened — rather than 4, because the verbatim duplication is a clear trim target.

3 / 5

Actionability

The body's only concrete directive is 'Read [the detailed guide](references/detailed-guide.md) before executing this skill' (the file exists), with no code, commands, or specific steps in the body itself; the Example section is circular, echoing the description instead of showing a real task. This matches anchor 2 (minimal concrete guidance, high-level hints missing specific steps); not 3 because nothing even partially executable lives in the body — all substance is delegated to the reference.

2 / 5

Workflow Clarity

The single workflow — read the guide, 'for focused work, load the relevant sections; for end-to-end work, read the guide completely' — is unambiguous, but the body contains no procedure steps, checkpoints, or decision guidance (e.g., which memory type or vector store to choose). Matches anchor 3: sequence present but checkpoints/decision structure missing; the destructive/batch validation cap does not apply to this knowledge skill.

3 / 5

Progressive Disclosure

The body is short and well-sectioned, and its one reference is clearly signaled with explicit load instructions; the referenced file (references/detailed-guide.md) is real and exactly one level deep with no further nested references. However, all detail — 1088 lines spanning memory frameworks, vector stores, chunking strategies, and decay patterns — sits in a single monolithic file that could be split by topic, so this matches anchor 4 (good structure, minor organization gaps) rather than 5's 'content appropriately split'.

4 / 5

Total

12

/

20

Passed

Description

53%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.

The description communicates a clear topical scope for agent memory architecture but reads as a topic map rather than a capability statement: it has no action verbs and no 'when to use' trigger clause, capping both specificity and completeness. Trigger keywords are present but miss the natural synonyms and tool names users would say. It is reasonably distinct from neighboring skills.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user mentions agent memory, long-term memory, remembering across sessions, RAG, vector stores, LangMem, or MemGPT' — this lifts completeness from 3 and improves trigger-term coverage.

Replace topical coverage language with concrete actions: e.g. 'Design and implement agent memory systems: short-term context-window management, long-term vector-store retrieval, and CoALA-style semantic/episodic/procedural memory architecture.'

Include the natural synonyms and tool names (remember across sessions, RAG, conversation history, LangMem, MemGPT) that currently only appear in the body's When-to-Use section.

DimensionReasoningScore

Specificity

The description names the domain and enumerates concrete sub-areas ('short-term (context window), long-term (vector stores), and the cognitive architectures'), but uses only the generic verb 'covers' with no concrete capability actions. It sits between anchor 2 (domain named, actions minimal) and anchor 3 (domain plus 1-2 concrete actions) — the sub-topic enumeration is more informative than anchor 2 but lacks the action concreteness of anchor 3.

3 / 5

Completeness

The 'what' is clear (architecture of agent memory across three sub-areas), but there is no 'Use when...' clause or equivalent trigger guidance anywhere in the description, which the judging guidelines explicitly cap at 3. This matches anchor 3 exactly: clear 'what', 'when' missing; not 4 because no when-guidance is present even weakly.

3 / 5

Trigger Term Quality

Natural terms like 'agent memory', 'context window', and 'vector stores' are present, but common variations users would actually say — 'remember across sessions', 'RAG', 'conversation history', 'LangMem', 'MemGPT' — are absent (they appear only in the body's When-to-Use list). This matches anchor 3: some relevant keywords but missing common variations or synonyms.

3 / 5

Distinctiveness Conflict Risk

'Agent memory' architecture with terms like 'cognitive architectures' and 'short-term/long-term memory' is a distinct niche with only minor overlap risk against closely related RAG or context-management skills. Closer to anchor 4 ('mostly distinct; minor overlap risk') than anchor 3, which would imply broader overlap; not 5 because 'memory' alone is a broad term that could collide with generic persistence skills.

4 / 5

Total

13

/

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
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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