Coding

Ai Writing Quality Check

Try it

Get exact phrase matches with character positions to fix banned content before publishing.

What it does

Scans text for banned phrases and AI clichés, returning precise correction targets with character positions and surrounding context. Iterate through rewrites until the check passes. Works on headlines, CTAs, social posts, emails, landing pages, and long-form blog content.

When to use it

  • Marketing copy pre-publish gate
  • Headline and CTA rewrite loops
  • Social post phrase compliance
  • Blog draft quality gating

The skill document

AI Writing Quality Check

Freshness

Last updated: 2026-06-24.

If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.

What This Tool Does

Catch banned phrases, and overused AI clichés in draft copy before you ship it - built for iterative rewrite loops inside AI content workflows. Point this tool at a headline, CTA, social post, email, landing page, or long-form blog and get back field-level correction targets: the exact matched phrase, its character index, surrounding context, and the reason it was flagged. Agents can take those corrections, rewrite inline, and re-run the check until the copy passes - no vague "improve this" feedback, no guessing. Ideal for marketing ops, content teams, SEO writers, brand compliance reviewers, and any AI copywriting pipeline that needs a deterministic, repeatable quality gate.

Product Instructions

AI Writing Quality Check

Use this tool to scan writing and return exact correction targets for rewrite loops.

Actions

get_instructions

Returns this documentation.

check_for_banned_phrases

Checks content for banned phrases and returns normalized correction guidance.

Parameters:

  • content (required): writing content to check.

Example

{
  "action": "check_for_banned_phrases",
  "content": "Our customers love us. Ask our AI."
}

Rewrite Loop

  1. Run check_for_banned_phrases with content.
  2. If passed is true, publish.
  3. If passed is false, rewrite each entry in corrections.
  4. Run check_for_banned_phrases again until passed is true.

When To Use

  • Use this skill for AI Writing Quality Check on AgentPMT.
  • Use it when an agent needs this specific tool's behavior, schema, inputs, outputs, and invocation shape.
  • Search and activation keywords: ai writing quality check, pre publish quality checks for marketing copy, headline and cta rewrite loops, social post phrase compliance checks, blog and article draft quality gating, check for banned phrases, content.
  • Supported action names: check_for_banned_phrases.

Use Cases

  • Pre-publish quality checks for marketing copy
  • Headline and CTA rewrite loops
  • Social post phrase compliance checks
  • Blog and article draft quality gating
  • Email subject line banned-phrase screening
  • Landing page hero copy sanity checks
  • Product description compliance review
  • Ad copy phrase-list enforcement
  • Brand voice guardrails for AI copywriters
  • Automated copy review inside multi-step agent workflows
  • SEO draft cleanup before publishing
  • AI cliché detection in long-form content
  • Field-level correction feedback for content editors
  • Consistent enforcement of organization-wide banned-phrase policy
  • Repeatable copy quality gates in content approval workflows

Categories And Industries

No categories or industry tags are published for this tool.

Actions And Schema

Complete generated action schema: ./schema.md. Supported action count: 1. x402 action routes are enabled and listed in ./schema.md.

  • check_for_banned_phrases (action slug: check-for-banned-phrases): Check writing for banned phrases and return correction targets tied to the content field. Price: 5 credits. Parameters: content.

Live Schema And Examples

Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.

  • Exact schema: call agentpmt-tool-search-and-execution with action: "get_schema", and tool_id: "ai-writing-quality-check".
  • Detailed examples: call agentpmt-tool-search-and-execution with action: "get_instructions" and tool_id: "ai-writing-quality-check", or call this product with action: "get_instructions" when the product tool is already selected.
  • Treat returned live schema and instructions as more specific than this generated summary.

MCP schema lookup through the main AgentPMT MCP server:

{
  "method": "tools/call",
  "params": {
    "name": "AgentPMT-Tool-Search-and-Execution",
    "arguments": {
      "action": "get_schema",
      "tool_id": "ai-writing-quality-check"
    }
  }
}

For live examples, keep the same MCP tool and use these arguments:

{
  "action": "get_instructions",
  "tool_id": "ai-writing-quality-check"
}

Authenticated AgentPMT REST schema lookup body:

{
  "name": "agentpmt-tool-search-and-execution",
  "parameters": {
    "action": "get_schema",
    "tool_id": "ai-writing-quality-check"
  }
}

Authenticated AgentPMT REST live examples body:

{
  "name": "agentpmt-tool-search-and-execution",
  "parameters": {
    "action": "get_instructions",
    "tool_id": "ai-writing-quality-check"
  }
}

Call This Tool

Product slug: ai-writing-quality-check

Marketplace page: https://www.agentpmt.com/marketplace/ai-writing-quality-check

  • AgentPMT account route: first use ../agentpmt-account-mcp-rest-api-setup to connect the main MCP server or REST API for an Agent Group where this tool is enabled.
  • No-account AgentAddress/x402 route: first use ../agentpmt-no-account-agentaddress-x402 for the canonical payment and wallet setup instructions.
  • AgentPMT overview: use ../what-is-agentpmt for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.

If those setup skills are not installed beside this product skill, use the downloads below.

Core AgentPMT setup skills:

  • What AgentPMT is: ../what-is-agentpmt
  • AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup
  • No-account AgentAddress/x402 setup: ../agentpmt-no-account-agentaddress-x402

skills.sh install script:

npx skills add AgentPMT/agent-skills --skill what-is-agentpmt
npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup
npx skills add AgentPMT/agent-skills --skill agentpmt-no-account-agentaddress-x402

MCP call shape after the main AgentPMT MCP server is connected:

{
  "method": "tools/call",
  "params": {
    "name": "AI-Writing-Quality-Check",
    "arguments": {
      "action": "check_for_banned_phrases",
      "content": "Draft marketing copy to check for banned phrases."
    }
  }
}

Use the exact tool name returned by tools/list; the name above is the expected readable form.

Authenticated AgentPMT REST call body:

{
  "name": "ai-writing-quality-check",
  "parameters": {
    "action": "check_for_banned_phrases",
    "content": "Draft marketing copy to check for banned phrases."
  }
}

Use the setup skill for the account connection details before making REST calls.

Response Handling

  • Treat the returned JSON as the source of truth for this tool call.
  • If the response includes warnings or correction targets, apply them before retrying.
  • If the response includes a passed or success-style boolean, use it as the workflow gate.
  • If validation fails or the response shape is unclear, call get_schema or get_instructions before retrying.
  • If check_for_banned_phrases fails, preserve the request parameters and retry only after fixing schema, auth, or payment errors.

Security

  • Do not place account secrets, wallet private keys, mnemonics, signatures, or payment headers in prompts or logs.
  • Keep tool inputs scoped to the minimum content needed for the task.
  • Use the setup skills for credential handling; this product skill only defines product-specific behavior.

AgentPMT Reference

Questions people ask

What does the output look like?
Returns a passed boolean and an array of corrections. Each correction includes the exact matched phrase, its character index, surrounding context, and the reason it was flagged.
Does it catch AI clichés or just banned words?
It detects both organization-specific banned phrases and overused AI clichés commonly found in AI-generated draft copy.
How does the rewrite loop work?
Run check_for_banned_phrases, rewrite each entry in the corrections array, then run again until passed equals true before publishing.

Related skills

Join meeting

Join video meetings as a voice bot, visual avatar, or avatar with live screen sharing.

by johnpatternai22 installs8 stars

Regret Minimization

Make irreversible life decisions by projecting to 80 and naming which regret you'd rather live with.

by deciqai1 installs2 stars

Ansoff Matrix

Prioritize growth directions with a 2×2 risk framework — pick one bet and commit.

by deciqai2 installs2 stars

Framing Effect

Detect when presentation language is steering your decision instead of the facts themselves.

by deciqai1 installs2 stars

Tunnel Vision & Slack

Escape the scarcity trap — diagnose bandwidth consumption and design protected slack to restore strategic capacity.

by deciqai1 installs2 stars

More from agentpmt

Browse all skills

blender-3d-modeling

Cloud-based Blender: render 3D models, generate turntable videos, and convert file formats without local installs.

by agentpmt3 installs

document-ocr-agent

Extract text, structured entities, and metadata from any PDF, image, or scanned document.

by agentpmt3 installs

Minecraft Custom Mod Builder

Generate install-ready Minecraft Bedrock add-ons, skin packs, Fabric and NeoForge mods with runtime verification and visual proof.

by agentpmt2 installs

gmail-all-email-actions

Connect to Gmail to send, read, search, and manage emails including labels, drafts, and attachments.

by agentpmt1 installs