agent-v3-memory-specialist

Agent skill for v3-memory-specialist - invoke with $agent-v3-memory-specialist

1.77x

Quality

Does it follow best practices?

Impact

85%

1.77x

Average score across 3 eval scenarios

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-v3-memory-specialist/SKILL.md

Quality

Discovery

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description is essentially a placeholder that provides no useful information about the skill's capabilities, domain, or trigger conditions. It fails on every dimension because it only states the skill's internal name and invocation syntax without describing any concrete actions or usage scenarios.

Suggestions

Describe what the skill actually does with concrete actions (e.g., 'Stores, retrieves, and manages persistent memory entries across conversations').

Add an explicit 'Use when...' clause with natural trigger terms users would say (e.g., 'Use when the user asks to remember something, recall previous context, or manage stored notes').

Replace the internal jargon 'v3-memory-specialist' with user-facing language that clearly distinguishes this skill from other potentially similar skills.

Dimension	Reasoning	Score
Specificity	The description contains no concrete actions whatsoever. 'Agent skill for v3-memory-specialist' is entirely vague and does not describe what the skill actually does.	1 / 3
Completeness	Neither 'what does this do' nor 'when should Claude use it' is answered. The description only states the skill's internal name and invocation command.	1 / 3
Trigger Term Quality	There are no natural keywords a user would say. 'v3-memory-specialist' is internal jargon, and 'invoke with $agent-v3-memory-specialist' is a technical invocation instruction, not a trigger term.	1 / 3
Distinctiveness Conflict Risk	The description is so generic that it provides no distinguishing information. 'Memory specialist' is vague and could overlap with any skill involving memory, context, or data storage.	1 / 3
	Total	4 / 12 Passed

Implementation

12%

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

This skill reads as a project planning/architecture document rather than an actionable skill for Claude. It is extremely verbose, repeating performance claims throughout, and contains no truly executable code—only illustrative TypeScript and SQL referencing non-existent libraries and interfaces. The content would benefit from being drastically reduced to concrete, executable steps with clear validation checkpoints.

Suggestions

Reduce content by 70-80%: remove ASCII diagrams, repeated performance claims, and architectural explanations. Focus on the specific commands/code Claude should execute to perform memory migration.

Replace illustrative TypeScript classes with actual executable code or concrete CLI commands that Claude can run, referencing real libraries and tools.

Split content into separate files: keep SKILL.md as a concise overview with references to MIGRATION.md, BENCHMARKS.md, and SONA.md for detailed procedures.

Add explicit validation checkpoints with concrete commands between migration phases (e.g., 'Run `npm test -- --grep memory` and verify all tests pass before proceeding to Phase 2').

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~250+ lines. Explains architecture, migration phases, SONA integration, and coordination points in exhaustive detail that Claude doesn't need. ASCII diagrams, repeated performance claims (150x-12,500x mentioned 6+ times), and extensive TypeScript classes that are illustrative rather than executable all waste tokens. Much of this reads like a project planning document, not a skill.	1 / 3
Actionability	Despite containing many code blocks, none are truly executable—they reference non-existent classes (AgentDBAdapter, HNSWIndexer, HNSWIndex), fictional npm packages (agentic-flow@alpha), and undefined interfaces. The migration phases use bash code blocks that are actually bullet-point lists, not commands. The SQL migration example uses a fictional 'generate_embedding()' function. This is aspirational design documentation, not actionable guidance.	1 / 3
Workflow Clarity	There is a phased migration strategy (Phase 1-3) with some sequencing, and a validation section with success criteria checklist. However, the phases are vague ('Week 3: AgentDB adapter creation') without concrete validation checkpoints between steps. The benchmark code is illustrative but doesn't specify how to actually run validation or what to do if benchmarks fail.	2 / 3
Progressive Disclosure	Monolithic wall of text with no references to external files and no bundle files provided. All content—architecture, migration, SONA integration, benchmarks, coordination—is inlined in a single massive document. Content like the SONA integration details, data migration plans, and benchmark suites should be in separate referenced files.	1 / 3
	Total	5 / 12 Passed

Validation

100%

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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: ruvnet/claude-flow
Commit: ca77f83

Reviewed: 3 days ago

Table of Contents

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