Name: ai-persistence
Rating: 75.2 (1 reviews)
Author: TanStack

ai-persistence

Durability and state persistence for TanStack AI chats with @tanstack/ai-persistence. Routes to server chat persistence (withPersistence), client persistence (localStorage/IndexedDB), the store contracts, and adapter recipes. Distinguishes delivery durability (resumable streams) from conversation state. Use when conversations must survive reloads, multi-device, approvals, or server restarts — NOT for stream reconnect alone.

Quality

93%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

87%

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

The body is lean, actionable, and well-structured with strong progressive disclosure, but workflow clarity is held back by an implicit rather than explicit validation checkpoint for the database-adapter work that the skill directs users to perform.

Suggestions

Promote the conformance testkit into an explicit numbered step in the production-stack workflow (e.g. "5. Validate: run runPersistenceConformance against your adapter; if it fails, fix and re-run") so the validate→fix→retry loop is visible.

Add a short adapter-writing checklist that sequences implement-stores → run-conformance → wire-withPersistence, mirroring the destructive/batch feedback-loop pattern the skill implies but does not spell out.

Surface the GET/hydrate route (reconstructChat) as an explicit step alongside the POST sketch so the server-authoritative load path is sequenced, not just mentioned in prose.

Dimension	Reasoning	Score
Conciseness	The body is table-driven and dense with no filler — it never explains what TanStack AI or databases are, and every line (contracts table, halves table, authoritative-history contract, critical rules) earns its place.	3 / 3
Actionability	Two copy-paste-ready TS/TSX blocks (server POST handler, client useChat) plus concrete named exports and specific do/don't rules ("saveThread is full overwrite", "createOrResume is insert-if-absent") give fully executable guidance.	3 / 3
Workflow Clarity	The "Recommended production stack" is a numbered sequence and "Critical rules" act as a checklist, but the conformance testkit is named rather than embedded as an explicit validate→fix→retry checkpoint, leaving validation implicit for database/batch adapter work.	2 / 3
Progressive Disclosure	No bundle files are present (references/scripts/assets absent), and the body is a well-organized overview that routes to one-level-deep sibling skills via clearly signaled tables, keeping inline content appropriately lean.	3 / 3
	Total	11 / 12 Passed

Description

100%

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 specific, trigger-rich, complete, and self-disambiguating, with concrete named APIs and both positive and negative use-when guidance. It scores at the top of every dimension.

Dimension	Reasoning	Score
Specificity	Names concrete capabilities and APIs — "server chat persistence (withPersistence), client persistence (localStorage/IndexedDB), the store contracts, and adapter recipes" — listing multiple specific actions rather than vague language.	3 / 3
Completeness	Clearly answers what ("Durability and state persistence for TanStack AI chats...") and when ("Use when conversations must survive reloads, multi-device, approvals, or server restarts"), with an explicit negative trigger ruling out stream-reconnect alone.	3 / 3
Trigger Term Quality	Natural user-facing triggers like "conversations must survive reloads, multi-device, approvals, or server restarts" read as things a developer would actually say; the unavoidable API jargon is balanced by these plain-language triggers.	3 / 3
Distinctiveness Conflict Risk	"NOT for stream reconnect alone" explicitly disambiguates delivery durability from state persistence, carving a clear niche unlikely to trigger sibling skills.	3 / 3
	Total	12 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: TanStack/ai
Path: packages/ai-persistence/skills/ai-persistence/SKILL.md
Commit: 1120f0f

Reviewed: about 13 hours ago

Table of Contents

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