ai-code-mode

LLM-generated TypeScript execution in sandboxed environments: createCodeModeTool() with isolate drivers (createNodeIsolateDriver, createQuickJSIsolateDriver, createQuickJSBunIsolateDriver, createCloudflareIsolateDriver), codeModeWithSnippets() for persistent snippet libraries, trust strategies, snippet storage (FileSystem, LocalStorage, InMemory, Mongo), client-side execution progress via code_mode:* custom events in useChat.

Quality

73%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

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tessl review fix ./packages/ai-code-mode/skills/ai-code-mode/SKILL.md

Quality

Content

78%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.

The content is highly actionable with executable examples and well-organized patterns and pitfalls. Its weaknesses are length that could benefit from splitting reference material into bundle files, and the absence of explicit validation feedback loops for risky operations.

Suggestions

Move the driver configuration tables and code_mode event catalogs into reference files under references/ (e.g., drivers.md, events.md) and link to them from SKILL.md to improve progressive disclosure.

Add an explicit validate->fix->retry checkpoint for destructive/risky operations such as the isolated-vm probe and sandbox timeout configuration.

Trim or factor out the longer duplicated code blocks (e.g., repeated driver creation) into shared snippets to reduce token cost.

Dimension	Reasoning	Score
Conciseness	The body is dense and technical, assuming Claude's competence and avoiding generic concept explanations, but is long with several full code blocks that could be trimmed or pushed to references.	4 / 5
Actionability	Provides fully executable, copy-paste TypeScript covering setup, all four drivers, snippets, trust strategies, client-side event handling, and lazy tools across the common cases.	5 / 5
Workflow Clarity	Core patterns and Common Mistakes are clearly sequenced with concrete guidance (e.g., probe before skipProbe, set finite timeout, keep secrets in host), though it lacks explicit validate->fix->retry feedback loops.	4 / 5
Progressive Disclosure	No bundle files exist in references/scripts/assets, so all reference material (driver config tables, event catalogs, API details) is inlined in SKILL.md rather than split into one-level-deep referenced files.	3 / 5
	Total	16 / 20 Passed

Description

67%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.

The description is highly specific and clearly distinguishable, naming concrete APIs, drivers, storage options, and events. Its main weakness is the absence of an explicit 'Use when' trigger clause and a reliance on technical jargon over natural user phrasing.

Suggestions

Add an explicit 'Use when...' clause stating when to invoke this skill (e.g., 'Use when running LLM-generated TypeScript in a sandbox, building code-mode chat tools, or managing persistent AI code snippets').

Include natural-language trigger phrases users would actually say ('run AI-generated code safely', 'execute TypeScript from the LLM', 'persistent code snippets') alongside the API names.

Lead with a plain-language summary of the capability before enumerating the function names, to aid natural triggering.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete capabilities with specific named functions (createCodeModeTool, codeModeWithSnippets), four named isolate drivers, named storage backends, and code_mode:* events, giving comprehensive coverage.	5 / 5
Completeness	Clearly answers 'what does this do' with concrete capabilities, but provides no 'Use when...' or equivalent explicit guidance on when to invoke the skill, which caps completeness at 3.	3 / 5
Trigger Term Quality	Includes a few relevant phrases like 'code mode' and 'sandboxed environments', but relies heavily on API/function-name jargon and omits natural user variations such as 'LLM-generated code', 'run AI code', or 'execute TypeScript'.	3 / 5
Distinctiveness Conflict Risk	Targets a specific TanStack code-mode niche with unique triggers (isolates, snippet libraries, code_mode events) and minimal overlap risk with unrelated skills.	5 / 5
	Total	16 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (527 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: TanStack/ai
Path: packages/ai-code-mode/skills/ai-code-mode/SKILL.md
Commit: 2822885

Reviewed: 3 days ago

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