Agent Prompt Stress-Tester

Pressure-test an agent prompt for gaps before you ship it.

  • $29 Free
  • 45 sec
  • No signup
1

Paste your agent prompt

2

See the scored gap report

3

Apply the suggested fixes

You get: A gap report on your agent prompt plus concrete fixes.

Paste your agent prompt

0 words - analyzed locally, no network calls.

Gap report

0

out of 100

Empty

  • !Clear role / identity

    Open with a clear identity, e.g. 'You are a code reviewer that...'. Without a role the agent has no anchor.

  • !Scoped responsibility

    State the single responsibility and what is out of scope. An unbounded agent drifts into unrelated work.

  • !Explicit process / steps

    Give a short numbered process (what to read, what to do, how to report). It keeps behavior consistent across runs.

  • !Success criteria / definition of done

    Define done: what must be true to consider the task complete. Without it the agent stops arbitrarily.

  • !Output format specified

    Say how to reply (a diff, a bullet list, JSON, under N words). Callers that depend on the shape need this.

  • !Guardrails / failure handling

    Add guardrails: what to do when unclear ('state your assumption, do not guess') and what it must never do.

  • !Examples or references

    Add at least one example of good input/output. Examples resolve ambiguity that instructions alone cannot.

Heuristic check only - it scans for signals of good structure, it does not run your prompt. A high score means well-formed, not guaranteed-correct.

What this stress-tester actually checks

A good agent prompt is not about clever wording - it is about structure. Agents that misbehave almost always have a structural gap: no clear role, no bounded scope, no definition of done, no guardrails for ambiguity. This tool scans your pasted prompt for the signals that those structural elements are present, scores each one, and tells you exactly what is missing and how to fix it. It runs entirely in your browser: nothing is sent to a server, no model is called, and your prompt never leaves the page.

Because it is a heuristic, a high score means the prompt is well-formed, not that it is guaranteed to work. It is a linter, not a judge. But in practice, prompts that pass all seven checks fail far less often than prompts that skip them, because the failures they catch are the ones that produce vague, drifting, or dangerous agent behavior.

The seven things a solid agent prompt needs

  • Clear role - the agent knows who it is. 'You are a security-focused code reviewer' anchors every decision it makes.
  • Scoped responsibility - what it should do and, just as important, what it should not. Unbounded agents wander into unrelated work.
  • Explicit process - a short ordered procedure so behavior is consistent from run to run.
  • Success criteria - a definition of done, so the agent stops at the right point instead of arbitrarily.
  • Output format - the shape of the reply (a diff, a bullet list, JSON), especially when something downstream depends on it.
  • Guardrails - what to do when unclear ('state your assumption, do not guess') and what it must never do (force push, delete, spend).
  • Examples - at least one concrete sample that resolves the ambiguity instructions alone leave behind.

Why scope and guardrails carry the most weight

The two failures that cause the most real damage are unbounded scope and missing guardrails. An agent with no scope will happily 'help' by editing files it was never asked to touch. An agent with no guardrails will guess when it should have asked, or run a destructive command because nothing told it not to. These are not style problems - they are the difference between an agent you can trust to run and one you have to babysit. That is why this tool weights them heavily and why fixing them first gives the biggest reliability gain.

The 'state your assumption' rule

The single highest-leverage line you can add to almost any agent prompt is: 'If anything is ambiguous, state your assumption and proceed, rather than guessing silently.' It converts a whole class of silent, hard-to-debug failures into visible, correctable ones.

How to read your score

  1. 80-100 (Strong) - the prompt has the structural bones of a reliable agent. Focus your remaining effort on the content of each section, not its presence.
  2. 55-79 (Decent) - workable but missing one or two important elements. Fix the gaps flagged in red first; they are usually scope, success criteria, or guardrails.
  3. Below 55 (Weak) - the prompt is likely to produce inconsistent or drifting behavior. Rebuild it around the seven elements before relying on the agent.
  4. Remember the score measures structure, not correctness. A well-structured prompt with wrong instructions still scores high - you still have to read it.

Turning gaps into fixes

Each failed check comes with a specific, copyable fix - not just 'add guardrails' but the actual sentence pattern to add. Work top to bottom: role first, then scope, then process, then the done-criteria and output format, then guardrails and examples. You do not need a long prompt to pass; you need a complete one. Many of the best agent prompts are under 200 words but hit all seven elements crisply. Longer is not better, because every line is loaded on each run and costs tokens.

Where this fits in building agents

Use this after you draft a subagent with the Subagent Generator and before you save it to .claude/agents/. Paste the body, read the gap report, patch the holes, and only then commit the file. It is the cheap quality gate that catches the mistakes you would otherwise only discover when the agent misbehaves mid-task. Pair it with tool scoping - a tight prompt plus a minimal tool set is what makes a subagent both safe and reliable.

What it deliberately does not do

This tool does not run your prompt, call a model, or judge whether your instructions are correct for your goal. It cannot tell you that your reviewer should also check for SQL injection, or that your test-writer targets the wrong framework - that is on you. It checks that the prompt is well-formed, which is necessary but not sufficient. Treat a strong score as permission to ship the structure, then still read the content with your own eyes.

Frequently asked questions

  • Does this send my prompt anywhere?

    No. The analysis is 100% client-side - it runs in your browser with no network calls, no API, and no storage. Your prompt never leaves the page, so it is safe to paste proprietary agent prompts.

  • How is the score calculated?

    It checks for signals of seven structural elements - role, scope, process, success criteria, output format, guardrails, and examples - each with a weight. The score is the weighted percentage of checks your prompt passes.

  • Does a high score mean my agent will work?

    It means the prompt is well-structured, not that it is correct. This is a linter, not a judge. It cannot know if your instructions match your goal, so a strong score still requires you to read the content yourself.

  • Which gap should I fix first?

    Scope and guardrails, because they prevent the most damaging failures - agents editing things they should not touch, or guessing and running risky commands. After those, add success criteria and an output format.

  • How long should an agent prompt be?

    Complete, not long. Many excellent prompts are under 200 words while hitting all seven elements. Every line is loaded on each run and costs tokens, so favor a tight prompt that covers the essentials over a sprawling one.

  • Can I use this for system prompts too?

    Yes. The same seven structural checks apply to any agent or system prompt, whether it is a subagent body, an --append-system-prompt string, or a CLAUDE.md role block. Paste any of them and read the gap report.

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