Check that functions, methods, and imports exist in the software version being used before writing code. Identify uncertain calls, framework mix-ups, and deprecated interfaces so implementation decisions rely on verified details.
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Use when the user says 'no hallucinations', 'verify APIs', 'reality check', or 'don't invent functions'. Prevents the agent from calling methods, imports, or variables that do not provably exist in the user's installed version.
安装前可以查看交给 AI 代理的指令内容。
Inventing a function that doesn't exist is the opposite of efficiency. You wrote a line that looks minimal. You shipped a bug that takes an hour to debug. The true minimal path is: use only what is provably there.
This skill is a reality-check layer applied before any code is written. It is not about being slow — it is about being correct the first time. Use it alongside minimalist when the user wants both less code and verified code.
Before you write any function call, import, or method access, you must be able to answer:
"Does this exist in the version the user is running?"
If the answer is "probably" or "I think so" — stop. You don't know. Say so.
Made-up methods:
fs.readFileLines() does not exist in Node.js.path.combine() is .NET, not Node.js.csv.read_csv() is pandas, not Python's csv module.Writing these is not minimal code — it is confident garbage.
Framework confusion. Every framework has a twin that sounds like it:
render_template (Flask) vs render() (Django)useForm() (react-hook-form) vs nothing built into Reactapp.listen() (Express) vs server.listen() (raw Node.js http)Deprecated APIs. Writing a deprecated method is writing code that will break on the next upgrade.
When you are not sure if a method exists, annotate it inline:
// verify fs.openAsBlob exists in your Node.js version (>= 20.0)
const blob = await fs.openAsBlob(path);
One comment costs nothing. A silent wrong call costs an hour of the user's time.
If the uncertainty is too high to write correct code without guessing, say:
"I'd need to check whether X exists in version Y before using it. What version are you on?"
| Anti-Pattern | What to do instead |
|---|---|
| Writing a method call you vaguely remember | Stop and verify the exact signature |
| Silently using a deprecated API | Use the current API and note the deprecation |
| Assuming API parity across frameworks | Explicitly name the framework and version |
| Guessing import paths | Check the package's actual export structure |
| Using an API from a different language's stdlib | Verify it exists in this language |
| Writing "it should work" without checking | Ask what version the user is on |
engineering/minimalist — use together: minimalist reduces code volume; strict-api ensures what is written is correct.engineering/zero-hallucination-coder — similar goal; broader hallucination prevention beyond APIs.engineering/karpathy-coder — Karpathy-inspired behavioral guardrails for LLM-assisted coding.还没有评价。欢迎分享你的使用感受。
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Audit web applications for accessibility issues against WCAG 2.2 Level A and AA, the web accessibility standards. Get framework-specific code fixes, contrast checks, verification steps, and reports, with options for automated checks in development pipelines.
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Plan A/B tests that compare page variations, from headlines to pricing layouts. Define a hypothesis, choose success metrics, calculate sample size and duration, and prepare launch checks and results reports to support decisions.
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Create paid ad headlines and body copy tailored to each platform's character limits. Use existing performance data to develop variations, explore new messaging angles, and check copy for length, quality, and potential rejection risks.
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Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.
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Audit and improve content intended for citation in AI answers. Review evidence, author information, and structure, generate revised content and structured metadata, and keep a local record of observed citations across AI services.
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Create signed records for consequential agent actions such as deployments, deletions, and payments. Decide which actions need evidence, record the agent, action, target, and policy, then verify the resulting certificate offline to detect later changes.
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