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tanstack-ai-memory-in-memory

Use when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and what NOT to use it for (multi-process or persistent).

77

Quality

96%

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

100%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.

An exemplary compact skill body: executable code, concrete defaults and signatures, clear use/neg-use decision guidance, and tidy sectioning with no padding. It assumes Claude's competence and adds only genuinely useful, non-obvious detail.

DimensionReasoningScore

Conciseness

Lean throughout — 'Zero-dependency recall/save adapter backed by a Map. Records vanish on process restart.' states only what Claude doesn't already know; no basic-concept padding and every section earns its place.

5 / 5

Actionability

Setup is copy-paste ready TypeScript, Options give concrete defaults (topK=6, minScore=0.15) and exact signatures (embedder: { embed(text): Promise<number[]> }, extract(turn, scope), render(hits)), and Capacity cites a real threshold (~100k records).

5 / 5

Workflow Clarity

A simple single-purpose skill whose single action (import → inMemory() → memoryMiddleware) is unambiguous; the 'When NOT to use it' section plus redirect to redis() provides an explicit decision checkpoint. No destructive/batch ops, so the validation cap does not apply.

5 / 5

Progressive Disclosure

Under 50 lines with no bundle files and no need for external references; sections (When to use / When NOT to use / Setup / Options / Capacity) are well-organized and the only cross-reference is a clearly signaled one-level pointer to the sibling redis skill.

5 / 5

Total

20

/

20

Passed

Description

92%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 tight, well-targeted description that states both capability and trigger conditions explicitly and carves out a distinct niche with clear negative guidance. The only mild gap is trigger-term breadth, which is largely inherent to this API-specific skill.

DimensionReasoningScore

Specificity

Names the adapter and enumerates its full surface concretely — 'setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and what NOT to use it for (multi-process or persistent)', giving comprehensive coverage of the niche rather than generic actions.

5 / 5

Completeness

Explicitly answers both 'what' ('explains setup, options...') and 'when' ('Use when wiring inMemory()... when to pick it... and what NOT to use it for') with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Includes the precise API token 'inMemory()' and package path '@tanstack/ai-memory/in-memory' plus 'multi-process' and 'persistent' — strong natural coverage for this developer-facing niche, but lacks synonyms or variations that would push it to a 5.

4 / 5

Distinctiveness Conflict Risk

A sharply bounded niche (a specific in-memory adapter) with explicit negative guidance ('what NOT to use it for (multi-process or persistent)') redirecting to the redis skill, minimizing overlap with sibling skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
TanStack/ai
Reviewed

Table of Contents

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