agent-memory-mcp

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

Quality

41%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

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npx tessl skill review --optimize ./skills/agent-memory-mcp/SKILL.md

Quality

Discovery

17%

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 is too abstract and buzzword-heavy, reading more like a product tagline than actionable skill guidance. It fails to specify concrete actions the skill performs and completely lacks trigger guidance ('Use when...'), making it difficult for Claude to know when to select this skill over others.

Suggestions

Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user asks to save, recall, or search for architectural decisions, design patterns, or project knowledge.'

Replace abstract language with concrete actions, e.g., 'Stores and retrieves architectural decisions, design patterns, and project context. Supports searching past decisions, logging new patterns, and updating project knowledge.'

Include natural trigger terms users would actually say, such as 'remember this', 'what did we decide about', 'log this decision', 'search notes', 'ADR', 'design decision'.

Dimension	Reasoning	Score
Specificity	It names the domain ('memory system', 'knowledge management') and mentions some characteristics ('persistent, searchable') but doesn't list concrete actions the skill performs. The parenthetical '(Architecture, Patterns, Decisions)' hints at content types but doesn't describe what the skill actually does with them.	2 / 3
Completeness	The 'what' is vaguely described as a 'hybrid memory system' but lacks concrete actions. There is no 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill, which per the rubric should cap completeness at 2, and the weak 'what' brings it to 1.	1 / 3
Trigger Term Quality	The description uses abstract/technical terms like 'hybrid memory system', 'persistent', 'searchable knowledge management', and 'AI agents' which are unlikely to match natural user queries. Users would more likely say things like 'save this decision', 'remember this pattern', 'look up architecture notes', none of which are present.	1 / 3
Distinctiveness Conflict Risk	The mention of 'hybrid memory system' and the specific categories (Architecture, Patterns, Decisions) provide some distinctiveness, but 'knowledge management' is broad enough to overlap with note-taking, documentation, or other memory/context skills.	2 / 3
	Total	6 / 12 Passed

Implementation

64%

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

The skill provides actionable setup instructions and clear MCP tool documentation with concrete examples. However, it suffers from generic boilerplate sections ('When to Use', 'Limitations') that waste tokens, and lacks validation/verification steps in the setup workflow. The content would benefit from trimming filler and adding error-handling guidance.

Suggestions

Remove or replace the generic 'When to Use' and 'Limitations' sections with project-specific guidance (e.g., when to use memory_write vs memory_search, what memory types are supported).

Add a validation step after server startup, such as 'Verify the server is running: curl http://localhost:<port>/health' or checking expected console output.

Add brief error recovery guidance for common setup failures (e.g., port conflicts, missing Node.js version).

Dimension	Reasoning	Score
Conciseness	The content is mostly efficient but includes some unnecessary filler. The 'When to Use' and 'Limitations' sections are generic boilerplate that add no real value. The MCP tool descriptions are reasonably lean but could be tighter.	2 / 3
Actionability	Setup steps include concrete, copy-paste-ready bash commands. MCP tool documentation provides specific argument signatures and usage examples with realistic invocations. The dashboard startup command is also concrete.	3 / 3
Workflow Clarity	The setup workflow is clearly sequenced (clone → install → start), but there are no validation checkpoints—no way to verify the server started correctly, no error recovery guidance, and no verification step after installation. For a server setup workflow, missing validation caps this at 2.	2 / 3
Progressive Disclosure	The content is reasonably organized with clear sections, but everything is inline in a single file with no references to supporting documentation. The MCP tool reference section could be split out, and there's no link to a README or detailed API docs. However, for a skill of this size (~80 lines), the inline approach is borderline acceptable.	2 / 3
	Total	9 / 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: sickn33/antigravity-awesome-skills
Commit: cb8a3ab

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

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