Ai Writing Quality Check

AI Writing Quality Check: Scan writing content for banned phrases and return a normalized response for rewrite loops. Use when an agent needs 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 through AgentPMT-hosted remote tool calls. Discovery terms: ai writing quality check, pre publish quality checks for marketing copy.

AgentPMT@agentpmt

Install

openclaw skills install @agentpmt/ai-writing-quality-check

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

json

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

Rewrite Loop

Run check_for_banned_phrases with content.
If passed is true, publish.
If passed is false, rewrite each entry in corrections.
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:

json

{
  "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:

json

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

Authenticated AgentPMT REST schema lookup body:

json

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

Authenticated AgentPMT REST live examples body:

json

{
  "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
- ClawHub page: https://clawhub.ai/agentpmt/what-is-agentpmt
- OpenClaw install: openclaw skills install what-is-agentpmt
- skills.sh install: npx skills add AgentPMT/agent-skills --skill what-is-agentpmt
AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup
- ClawHub page: https://clawhub.ai/agentpmt/agentpmt-account-mcp-rest-api-setup
- OpenClaw install: openclaw skills install agentpmt-account-mcp-rest-api-setup
- skills.sh install: npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup
No-account AgentAddress/x402 setup: ../agentpmt-no-account-agentaddress-x402
- ClawHub page: https://clawhub.ai/agentpmt/agentpmt-no-account-agentaddress-x402
- OpenClaw install: openclaw skills install agentpmt-no-account-agentaddress-x402
- skills.sh install: npx skills add AgentPMT/agent-skills --skill agentpmt-no-account-agentaddress-x402

skills.sh install script:

bash

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:

json

{
  "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:

json

{
  "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

What AgentPMT is: ../what-is-agentpmt (ClawHub: what-is-agentpmt, page: https://clawhub.ai/agentpmt/what-is-agentpmt; skills.sh: npx skills add AgentPMT/agent-skills --skill what-is-agentpmt)
AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup (ClawHub: agentpmt-account-mcp-rest-api-setup, page: https://clawhub.ai/agentpmt/agentpmt-account-mcp-rest-api-setup; skills.sh: npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup)
No-account AgentAddress/x402 setup: ../agentpmt-no-account-agentaddress-x402 (ClawHub: agentpmt-no-account-agentaddress-x402, page: https://clawhub.ai/agentpmt/agentpmt-no-account-agentaddress-x402; skills.sh: npx skills add AgentPMT/agent-skills --skill agentpmt-no-account-agentaddress-x402)
Marketplace product: https://www.agentpmt.com/marketplace/ai-writing-quality-check
AgentPMT main MCP server: https://api.agentpmt.com/mcp/
AgentPMT REST invoke endpoint: https://api.agentpmt.com/products/purchase