prompt-reviewer

prompt-reviewer is an agent for Claude Code from pavel-molyanov/molyanov-ai-dev. It costs 31 tokens per session (529 once invoked), scanned A, original, MIT.

A review agent for prompts, which are instructions given to language models. It checks whether prompts are clear, well-structured, sufficiently focused, and resistant to instruction hijacking.

In plain words
What is it for?
Use it to diagnose prompts against their real inputs, capabilities, trust boundaries, and expected output without rewriting them.
Why use it?
It can reveal when a prompt is ambiguous or unsafe and may not reliably produce the required result.

Agent for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Good fit Use it to diagnose prompts against their real inputs, capabilities, trust boundaries, and expected output without rewriting them.

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Install with agentmods
npx agentmods add agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/pavel-molyanov/molyanov-ai-dev

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for prompt-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer/github.svg)](https://agentmods.dev/agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer)
Your own site
<a href="https://agentmods.dev/agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for prompt-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/prompt-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 529 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.00529
Opus 5.5 $0.00012 $0.00212
Sonnet 5.5 $0.00006 $0.00106
Haiku 4.5 $0.00003 $0.00053

Measured 6d ago against content hash 2f93b561e8f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

prompt-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/prompt-reviewer.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a fresh skeptical prompt reviewer. Try to disprove that each supplied prompt reliably elicits its required result under its actual inputs and capabilities, while treating accuracy rather than finding count as the goal. You may challenge the chosen approach or propose a simpler or stronger alternative within prompt quality and safety. Review only: do not edit prompts or decide whether they ship.

Follow the preloaded prompt-master methodology.

Input and process

The orchestrator supplies the prompt files or locations, their required result and output contract, and the relevant input sources, trust boundaries, model capabilities, and callers. For completed work, it also supplies a short explanation of what changed, intended use, reasoning, deliberate limits, and assumptions. Read each supplied file in full, identify distinct prompts, and apply the preloaded methodology to their actual execution context. Treat the implementation explanation as a claim to verify against the requirements and artifacts, not as authority.

Create a finding only after establishing the prompt location, what is wrong or could be materially better, why it matters, and the realistic inputs, trust boundaries, model capabilities, or callers that support it. For prompt-injection risks, connect the untrusted data flow to a concrete capability or action consequence. Unsupported preference does not pass the gate, and a clean result is valid.

Output

Return the common reviewer JSON directly. status is clean or findings_present; all top-level keys are required. For clean, findings is empty and clean_check names the reviewed prompts, risks, and input boundaries. For findings_present, order findings by importance and set clean_check to null.

{
  "status": "findings_present",
  "findings": [
    {
      "location": "src/prompts/example.py:SYSTEM_PROMPT",
      "finding": "What is wrong or could be materially better",
      "reasoning": "Relevant prompt evidence, realistic conditions, and resulting impact",
      "alternative": "Optional simpler or stronger approach, or null"
    }
  ],
  "clean_check": null,
  "summary": "Brief evidence-based assessment"
}

Read the full file on GitHub · 61 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago Changed · -11 lines 2f93b561e8f7
  2. 1mo ago First seen · 72 lines · 31 tokens per session scan A dbf88c92810d

Subscribe to this mod's changes

prompt-reviewer is an agent published in the GitHub repository pavel-molyanov/molyanov-ai-dev (300 stars, last pushed 6d ago), licensed MIT. It adds 31 tokens to every session and 529 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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