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mem0-vercel-ai-sdk

Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also triggers for Next.js apps needing memory-augmented AI. DO NOT TRIGGER when: user asks about direct Python/TS SDK calls without Vercel (use mem0 skill), or CLI terminal commands (use mem0-cli skill).

70

Quality

86%

Does it follow best practices?

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SecuritybySnyk

High

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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.

A strong, executable skill body with copy-paste code, well-organized tables, and proper progressive disclosure to real reference files. Only minor conciseness trims and more explicit verification cues would lift it further.

DimensionReasoningScore

Conciseness

Mostly lean and action-oriented (code, tables, bullets) with only minor over-explanation such as 'The wrapped model approach is the simplest' and the 'What happens under the hood' prose that could be trimmed.

4 / 5

Actionability

Multiple complete, copy-paste-ready TypeScript examples covering install, env, wrapped model, standalone utilities, streaming, and provider selection, plus tables mapping providers to env vars and functions to return types.

5 / 5

Workflow Clarity

Clear sequenced setup (Step 1/Step 2) and well-labeled patterns with enumerated internal flows; some verification checkpoints are implicit rather than explicit, but the skill is non-destructive so the destructive cap does not apply.

4 / 5

Progressive Disclosure

SKILL.md is a concise overview with a clearly signaled References table linking to three real one-level-deep bundle files (provider-api.md, memory-utilities.md, usage-patterns.md), keeping bulk API detail out of the main body.

5 / 5

Total

18

/

20

Passed

Description

87%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.

A well-constructed description with explicit what/when guidance, broad trigger coverage, and strong disambiguation against related skills. The main room for improvement is converting more technical API identifiers into natural-language phrasing.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions/APIs ("retrieves and stores memories", createMem0, retrieveMemories, addMemories, searchMemories) but relies on API identifiers rather than a fully comprehensive prose list of capabilities, leaving minor coverage gaps.

4 / 5

Completeness

Explicitly answers both 'what' (Mem0 provider that retrieves and stores memories during LLM calls) and 'when' via an explicit 'TRIGGER when' clause with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Broad coverage of natural terms and synonyms ("vercel ai sdk", "mem0 vercel", "AI SDK provider", "AI SDK memory") plus function names and a Next.js scenario, though a few entries are technical identifiers rather than phrases a user would naturally say.

4 / 5

Distinctiveness Conflict Risk

Clear niche (Vercel AI SDK provider) with distinct triggers and explicit disambiguation against sibling skills via 'DO NOT TRIGGER ... use mem0 skill / mem0-cli skill', giving minimal conflict risk.

5 / 5

Total

18

/

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 2 suspicious

Warning

Total

15

/

16

Passed

Repository
mem0ai/mem0
Reviewed

Table of Contents

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