agent-memory-mcp

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

8.00x

Quality

41%

Does it follow best practices?

Impact

96%

8.00x

Average score across 3 eval scenarios

Securityby

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/agent-memory-mcp/SKILL.md

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

Quality

Content

64%Scale 1-3

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

The skill provides solid, actionable setup instructions and clear MCP tool documentation with concrete examples. However, it lacks validation/verification steps in the workflow (e.g., confirming the server is running), includes a vacuous 'When to Use' section, and could benefit from error recovery guidance and references to deeper documentation.

Suggestions

Add a validation step after 'Start the MCP Server' (e.g., expected console output or a health check command) to confirm successful startup.

Remove or replace the 'When to Use' section with genuinely useful guidance about when to invoke memory_write vs memory_search in a typical agent workflow.

Add brief troubleshooting notes for common failure modes (e.g., port conflicts, missing Node.js version, compilation errors).

Dimension	Reasoning	Score
Conciseness	Mostly efficient but includes some unnecessary filler like 'This skill provides a persistent, searchable memory bank that automatically syncs with project documentation' which restates the description, and the 'When to Use' section is a meaningless tautology. The MCP tool docs are reasonably lean.	2 / 3
Actionability	Provides concrete, copy-paste-ready bash commands for setup, start, and dashboard. MCP tool documentation includes specific argument signatures and usage examples with actual function calls. Setup steps are fully executable.	3 / 3
Workflow Clarity	Setup steps are clearly sequenced (clone → install → start), but there are no validation checkpoints — no way to verify the server started successfully, no error recovery guidance, and no mention of what to do if compilation or startup fails.	2 / 3
Progressive Disclosure	Content is reasonably structured with clear sections (Setup, Capabilities, Dashboard), but everything is inline in one file. The tool reference section could be split out for a skill of this size, and there are no references to additional documentation (e.g., advanced configuration, troubleshooting, or the project's own README).	2 / 3
	Total	9 / 12 Passed

Description

17%Scale 1-3

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 reads more like a product tagline than a functional skill description. It lacks concrete actions, natural trigger terms, and any explicit guidance on when Claude should select this skill. The parenthetical hints at scope but doesn't compensate for the overall vagueness.

Suggestions

Add explicit concrete actions such as 'Store and retrieve architecture decisions, design patterns, and project knowledge' instead of abstract 'knowledge management'.

Add a 'Use when...' clause with natural trigger terms like 'remember this decision', 'what patterns have we used', 'save architecture note', 'look up previous decisions'.

Replace marketing-style language ('hybrid memory system', 'AI agents') with plain, action-oriented language that describes what the skill actually does for the user.

Dimension	Reasoning	Score
Specificity	Names the domain ('memory system', 'knowledge management') and hints at what it stores ('Architecture, Patterns, Decisions'), but doesn't list concrete actions like 'store decisions', 'search patterns', 'retrieve architecture notes'.	2 / 3
Completeness	Describes what it is at a high level but has no 'Use when...' clause or equivalent explicit trigger guidance. The 'when' is entirely missing, which per the rubric caps completeness at 2, and the 'what' is also vague enough to warrant a 1.	1 / 3
Trigger Term Quality	Uses technical/abstract terms like 'hybrid memory system', 'persistent, searchable knowledge management', and 'AI agents' which are not natural phrases a user would say. Missing common trigger terms like 'remember', 'save note', 'look up decision', 'project memory'.	1 / 3
Distinctiveness Conflict Risk	The parenthetical '(Architecture, Patterns, Decisions)' provides some niche specificity, but 'knowledge management' and 'memory system' are broad enough to overlap with note-taking, documentation, or other memory-related skills.	2 / 3
	Total	6 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

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

	Total	10 / 11 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/agent-memory-mcp/SKILL.md
Commit: 7520423

Reviewed: ~11 hours ago

Table of Contents

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