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agent-memory-mcp

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./cli-tool/components/skills/ai-research/agent-memory-mcp/SKILL.md

The canonical home for this skill is agent-memory-mcp in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

68%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 delivers a clear, executable setup path and a well-organized MCP tool reference with concrete args and examples. Its main weaknesses are the absence of any validation/verification checkpoints in the setup workflow and the missing step showing how an agent actually connects to the started MCP server.

Suggestions

Add a validation checkpoint after starting the server, e.g. "Verify the server is running: curl http://localhost:3333/health" or "Confirm memory_stats({}) returns before proceeding".

Show how to register the MCP server with the agent's client configuration (e.g., the MCP server entry/command), since without it the setup does not produce a usable connection.

Trim the intro sentence that restates the description and elaborate or remove the unexplained "automatically syncs with project documentation" claim.

DimensionReasoningScore

Conciseness

The body is lean — setup commands and tool args with no explanations of concepts Claude already knows. Minor trim opportunities: the intro sentence ("a persistent, searchable memory bank that automatically syncs with project documentation") duplicates the frontmatter description and makes an unelaborated "automatically syncs" claim. This matches the efficient-with-minor-trims anchor rather than the every-token-earns-its-place anchor (5).

4 / 5

Actionability

Commands are copy-paste ready ("git clone https://github.com/webzler/agentMemory.git .agent/skills/agent-memory", "npm run start-server my-project $(pwd)", dashboard at "http://localhost:3333") and each MCP tool documents typed args with a usage example. It falls short of anchor 5 because the step to register or connect the MCP server to the agent's client is never shown, and no expected output is given for any command.

4 / 5

Workflow Clarity

Setup is a clearly ordered sequence (clone → install → compile → start server → use tools), but there are no validation checkpoints at all — nothing to confirm the server started or that the MCP connection works before use. This matches "steps listed but validation gaps; checkpoints missing or implicit" rather than anchor 4, which requires most checkpoints present (the operations are non-destructive, so the destructive-cap does not apply).

3 / 5

Progressive Disclosure

The skill is self-contained with no bundle files and no nested references, and its sections (Prerequisites, Setup, Capabilities, Dashboard) are well organized and appropriately sized. It matches the good-structure anchor; it does not reach 5 because the body (~78 lines) exceeds the under-50-line exception where a fully inline skill scores 5 without external references.

4 / 5

Total

15

/

20

Passed

Description

50%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 clearly states what the skill is (a persistent, searchable memory system for AI agents with typed knowledge), but it omits any guidance on when to use it and uses no natural trigger phrases. Scores sit uniformly at the midpoint because the "what" is decent while the "when" and user-voice triggers are absent.

Suggestions

Add an explicit trigger clause, e.g. "Use when the user asks to remember, save, or recall project knowledge, architecture decisions, or recurring patterns."

Replace abstract phrasing with concrete actions: "Records, searches, and retrieves long-term memories (architecture decisions, patterns) via an MCP server."

Define what "hybrid" means or drop it, and add common synonyms (memory bank, decision records, ADRs) to reduce overlap with generic memory skills.

DimensionReasoningScore

Specificity

"provides persistent, searchable knowledge management" names the domain and 1-2 capability qualities, with scope types in "(Architecture, Patterns, Decisions)", but lacks concrete action verbs like record, retrieve, or sync. It is more concrete than the bare domain-name anchor (2) but far less action-listing than anchors 4-5.

3 / 5

Completeness

The "what" is stated ("a hybrid memory system that provides persistent, searchable knowledge management") but there is no "Use when..." clause or equivalent trigger guidance, which caps completeness at 3. It cannot score 4 because the "when" is not even weakly explicit.

3 / 5

Trigger Term Quality

"memory" and "knowledge management" are relevant keywords, but the natural phrases users would actually say ("remember this", "recall", "decision record", "ADR") are missing. Keyword coverage is relevant but incomplete, matching anchor 3 rather than the good coverage of anchor 4.

3 / 5

Distinctiveness Conflict Risk

The typed-memory niche (Architecture, Patterns, Decisions) is somewhat specific, but "hybrid memory system" and "knowledge management" would overlap with any other memory or note-taking skill, and "hybrid" is never defined. It is not entirely generic (1-2) but does not have the clear distinct triggers of anchor 5 or the minor-overlap profile of anchor 4.

3 / 5

Total

12

/

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

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

davila7/claude-code-templates

Path

cli-tool/components/skills/ai-research/agent-memory-mcp/SKILL.md

Reviewed

Table of Contents

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