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tanstack-ai-memory-hindsight

Use when wiring hindsight() from @tanstack/ai-memory/hindsight — a hosted memory adapter that buckets memory per conversation and exposes retain/recall/reflect tools to the model. Requires the optional @vectorize-io/hindsight-client peer.

73

Quality

92%

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Low

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SKILL.md
Quality
Evals
Security

Quality

Content

92%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 compact, high-signal body: executable setup code, concrete option defaults, and product-specific facts with zero filler. The only gap is slightly incomplete executable coverage around the optional peer dependency install and tool/output examples.

DimensionReasoningScore

Conciseness

45 lean lines with no padding and no explanation of concepts Claude already knows — statements like "Hindsight owns extraction and ranking server-side" and "bank id is {tenantId|_}__{user}__{threadId}" are product-specific facts, not filler. Every section earns its place, matching the 'lean and efficient; assumes Claude's competence' anchor.

5 / 5

Actionability

The Setup block is executable and copy-paste ready (imports, session-derived factory, middleware wiring) and Options list concrete values with defaults ("'low' | 'mid' | 'high'", "HINDSIGHT_URL or http://localhost:8888"). Minor gaps keep it at anchor 4 rather than 5: no install command for the optional peer dependency and no example showing budget/callback usage or what the returned tools look like.

4 / 5

Workflow Clarity

A simple single-purpose skill — wire the adapter — where the single action is unambiguous, including a safety checkpoint ("never from req.body") for deriving the scope. No destructive or batch operations require validation, so the simple-skill exception applies and the score reaches 5.

5 / 5

Progressive Disclosure

The skill is under 50 lines, needs no external references (none exist in the bundle), and is cleanly organized into Setup, Options, and Tools sections — per the rubric guideline this earns a 5 with well-organized sections alone.

5 / 5

Total

19

/

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 tight, third-person description that explicitly covers both what the adapter does and when to use it, anchored by exact package, function, and tool names. Keyword coverage and capability breadth leave minor room for synonyms and broader action enumeration.

DimensionReasoningScore

Specificity

Names several concrete capabilities — "wiring hindsight() from @tanstack/ai-memory/hindsight", "buckets memory per conversation", "exposes retain/recall/reflect tools to the model", "Requires the optional @vectorize-io/hindsight-client peer" — matching the 'several specific actions; minor gaps' anchor. It falls short of 5 because it doesn't comprehensively cover what the skill helps with beyond the initial wiring.

4 / 5

Completeness

Explicitly answers both: what ("a hosted memory adapter that buckets memory per conversation and exposes retain/recall/reflect tools to the model") and when ("Use when wiring hindsight() from @tanstack/ai-memory/hindsight") with a concrete trigger phrase. The when-clause is specific and improvable only by adding variants, not by making it more explicit, so anchor 5 fits better than 4.

5 / 5

Trigger Term Quality

Includes the exact natural terms a user would say for this niche — the package path "@tanstack/ai-memory/hindsight", "hindsight()", "retain/recall/reflect", "memory adapter" — but misses common synonyms like "long-term memory" or "conversation memory", fitting the 'good keyword coverage; a few natural terms missing' anchor rather than comprehensive 5.

4 / 5

Distinctiveness Conflict Risk

Names one specific function from one specific package plus its peer dependency — a clear niche with distinct triggers that no generic skill would claim, matching the 'clear niche with distinct triggers; minimal conflict risk' anchor.

5 / 5

Total

18

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
TanStack/ai
Reviewed

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