Promptyard
Prompt

System Prompt Analyzer

Static analysis catching common prompt anti-patterns and surfacing token counts.

Tokens (gpt-4o)
97
Findings
2
Warnings
1
info"Helpful AI assistant" framing

Consider a more specific persona. "You are a senior data engineer answering production questions" beats "you are a helpful assistant" for any technical task.

warnHedge against hallucination only with prose

Telling the model to "be accurate" doesn't prevent hallucination. Pair with retrieval, citations, or schema-constrained output.

Heuristics, not rules. Some signals (long sentences, "helpful assistant") can be intentional. Use as a checklist while writing, not a pass/fail gate.

What good prompts have in common

  • Concrete persona. "Senior data engineer" not "helpful assistant".
  • Clear task framing. What\'s the input, what\'s the desired output, what\'s the success criteria.
  • Examples for non-trivial formats. Show, don\'t just tell.
  • Positive instructions. "Always quote line numbers" beats "don\'t respond without line numbers".
  • Schema for structured output. If you want JSON, give a schema or example.
  • Tag-delimited sections in long prompts. XML for Claude, markdown for GPT.

FAQ

Are these checks "right"?
They're heuristics derived from common patterns in production failures and from Anthropic / OpenAI prompting guides. Heuristics aren't rules — many flagged patterns are fine in context.
Why flag "helpful AI assistant" framing?
It's near-universal boilerplate from older prompt-engineering tutorials. A specific persona ("You are a senior backend engineer reviewing pull requests") consistently beats the generic version on technical tasks.
Why warn about negative instructions?
Models pattern-match on what you say to do, not what you say not to do. "Don't use markdown" is less reliable than "Output plain text only". When you must use a negative, pair with a positive: "Don't X; instead, Y".
What about prompt-injection checks?
Not yet. Prompt injection is a runtime concern (variable substitution + user input). This tool checks the static prompt only. For injection mitigation, validate user inputs at the boundary and use distinct system / user role separation.

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