Best AI Job Description Writers, Tested & Ranked (2026)

Job postings are the first impression a company makes on a candidate. Get the language wrong and qualified people self-select out before clicking apply. Get the tone wrong and the candidate pool narrows in ways that create compliance risk. According to SHRM research, 82% of candidates are more likely to apply when a pay range is included in a job listing, and pay transparency is just one of dozens of language signals that shape who shows up in your funnel. The right AI job description tool addresses those signals at scale.

This guide covers the four AI job description writers that talent acquisition teams are actively evaluating in 2026: Textio, Datapeople (now by Payscale), Ongig, and GoHire. Each was scored across five dimensions: bias-detection depth, generative writing quality, ATS integration, tone and template control, and value for price. The ranking reflects where each tool actually excels and where the trade-offs show up.

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How AI Job Description Tools Transform Recruiting Teams

Most job descriptions are written fast, by people who know the role but not necessarily the language patterns that determine whether diverse candidates apply. A hiring manager drafting a senior engineering role will naturally reach for the vocabulary they know, and that vocabulary often carries gender coding, credential inflation, and exclusionary phrasing that narrows the applicant pool before sourcing has even started.

AI job description tools solve this at the point of creation rather than after the fact. They catch biased language in real time, suggest inclusive alternatives, score drafts against outcome data, and enforce brand consistency across teams. For recruiting operations managing dozens or hundreds of open roles simultaneously, the compounding effect of consistently better job copy is measurable: broader pipelines, faster time-to-fill, and reduced legal exposure from discriminatory language.

The Problems That Drive Adoption of AI Job Description Tools:

• Biased language reducing applicant diversity. Gendered, ageist, or ability-coded language discourages qualified candidates from applying, often without recruiters noticing it is there.
• Inconsistent tone and structure across teams. When every hiring manager writes their own job descriptions without guardrails, brand voice erodes and candidate experience suffers.
• Missing compliance requirements. Pay transparency laws, EEO statements, and accessibility language requirements are increasingly mandated by state and federal regulation, and manual review does not scale.
• Slow drafting cycles. Writing a quality job description from scratch takes time that most lean recruiting teams do not have when managing high-volume hiring.

The best AI job description tools do not just write faster. They write smarter, with training data tied directly to hiring outcomes rather than general-purpose language models.

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What to Look for in an AI Job Description Tool

Not all AI job description software is built the same way. A general-purpose writing assistant trained on web content will not catch the gender-coded phrases that reduce female applicants. A bias checker without generative capability helps audit but does not draft. The tools that earn a place in a TA tech stack typically check every box below, and the gaps between tools become visible when you stack the rubric.

Here is what matters most when evaluating AI job description writers:

Key Criteria for Evaluating AI Job Description Tools:

• Bias detection depth and specificity. Does the tool flag only gender language, or does it catch race, age, ability, neurodiversity, and LGBTQ+ coded phrasing as well?
• Outcome-backed scoring. Are suggestions tied to real hiring outcome data, applicant rates, diversity metrics, time-to-fill, or are they based on general language heuristics?
• Generative AI writing quality. Can the tool produce an ATS-ready first draft from a job title alone, and does that draft require significant human editing to be usable?
• ATS and HRIS integration. Does the tool sync with Greenhouse, Workday, Lever, iCIMS, and similar platforms so job content flows without manual copy-paste?
• Template and approval workflows. Can teams build a governed library of approved templates and route drafts through structured review before they go live?
• Compliance automation. Does the tool automatically flag missing EEO statements, salary disclosure requirements, and accessibility language based on applicable laws?
• Pricing accessibility. Is the tool available to teams of different sizes, or does it require an enterprise commitment before a team can evaluate real output?

The tools reviewed below were measured against each of these criteria. Textio leads on bias depth and HR-specific outcome data. Datapeople leads on analytics and pay transparency compliance. Ongig leads on volume-scale management and compliance automation. GoHire is the only option with a free tier for teams exploring the category for the first time.

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How TA Teams Use AI Job Description Tools

Talent acquisition teams adopt AI job description tools at different stages of maturity, and the use cases vary by team size and hiring volume. The patterns that appear most consistently across high-performing recruiting organizations in 2026 are described below.

Standardizing language across distributed hiring managers. Large organizations with decentralized hiring structures face a specific problem: every department writes its own job descriptions, creating inconsistency in tone, structure, and language quality. AI tools with template libraries and approval workflows solve this by creating a governed starting point that teams customize within guardrails rather than drafting from a blank page.

Running pre-publish bias audits on existing job libraries. Many teams begin their AI tool journey by auditing an existing library of job descriptions written before inclusive language was a priority. Tools like Textio and Ongig can score and flag an entire job library, giving recruiting ops a clear picture of which postings carry the highest risk and prioritizing rewrites accordingly.

Speeding up time-to-publish for high-volume roles. For roles that open frequently, customer service, operations, entry-level, AI generative tools dramatically reduce the time from requisition to live posting. A recruiter who would spend 45 minutes writing a job description from scratch can produce a compliant, brand-consistent draft in under five minutes by entering a job title and a few role-specific parameters.

Monitoring compliance with pay transparency laws. As pay transparency legislation has expanded across US states and international jurisdictions, recruiting teams need systematic tooling rather than manual review. Datapeople has built pay transparency monitoring directly into its compliance layer, flagging postings that go live without salary disclosure in required jurisdictions.

Connecting job description quality to funnel metrics. The most sophisticated use case is closing the feedback loop between job description language and downstream outcomes. Tools integrated with ATS data can surface which postings drove qualified applicant volume and which underperformed, giving recruiting ops the evidence to refine language standards at the content level rather than guessing at sourcing adjustments.

Supporting skills-based hiring transitions. As organizations move away from credential-heavy job requirements toward skills-based criteria, AI tools that flag unnecessary degree requirements and suggest competency-based alternatives are becoming part of the job design workflow, not just the writing workflow.

The teams getting the most from AI job description tools are treating them as a content operations layer for talent acquisition, not just a writing assistant.

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Competitor Comparison: AI Job Description Tools for 2026

The table below provides a side-by-side view of the four tools evaluated in this guide across the dimensions that matter most to TA buyers. Use it as a fast-reference before diving into the individual reviews.

Criteria	Textio	Datapeople (by Payscale)	Ongig	GoHire
Bias Detection Depth	Excellent, gender, age, disability, neurodiversity	Strong, 8 specific bias types, color-coded flagging	Strong, 12+ bias types across 10,000+ word database	Basic, generative draft only, no dedicated bias audit
Outcome-Backed Scoring	Yes, proprietary HR outcome dataset	Yes, based on 100M+ job outcomes from 80 countries	Yes, 0-100 scoring with real-time feedback	No dedicated scoring
Generative Writing	Yes, Textio Verified first drafts	Yes, First Draft AI	Yes, title-to-description generation	Yes, 30-second draft generation
ATS Integration	Greenhouse, Lever, Workday, LinkedIn	Workday, Greenhouse, Lever, iCIMS, SAP, and more	Workday, Greenhouse, iCIMS, Lever, SAP SuccessFactors	Indeed, LinkedIn, ZipRecruiter (distribution only)
Compliance Automation	EEO, bias risk documentation	Pay transparency, EEO, EEOC/OFCCP	EEOC, OFCCP, pay transparency, salary disclosure	No dedicated compliance tooling
Template and Workflow Management	Yes, centralized library with brand customization	Yes, standardized templates and approval workflows	Yes, enterprise template management with version control	No template management
Multilingual Support	English only	Global (80 countries)	Limited	Limited
Pricing Entry Point	~$15,000/year	~$12,000/year average	~$11,999/year	Free (JD generator); paid ATS plans from ~$47/month
Best For	Enterprise HR teams with DEI mandates	Global enterprises needing comp-TA alignment	High-volume enterprise JD management	Startups and SMBs needing a free drafting entry point

Textio and Datapeople compete closely on bias detection and compliance depth. The clearest differentiator between them as of 2026 is Datapeople’s integration of pay transparency compliance and its direct connection to Payscale’s compensation data, useful for enterprises where TA and comp teams share a workflow. Ongig wins on raw volume management, with enterprise template infrastructure and ATS sync that handles hundreds of postings simultaneously. GoHire sits in a separate tier: the right starting point for teams that have never used a dedicated JD tool and need to experience the category before committing budget.

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Best AI Job Description Writers in 2026

1. Textio

Textio is the most purpose-built AI writing platform for HR content in this category, with the deepest outcome-backed bias detection and the broadest application across both recruiting and performance management language. For enterprise TA teams with active DEI mandates, it remains the benchmark.

Founded in Seattle in 2014, Textio built its platform specifically on HR writing data, not general web language, which is why its bias detection goes further than most competitors. The platform’s algorithms are trained on real-world hiring outcomes and performance reviews, with 10 million new HR records added every month. The platform is structured around two products: Textio Loop for recruiting content (job descriptions, sourcing outreach, employer brand copy) and Textio Lift for performance management writing.

Key Features:

• The Textio Score: Every job posting receives a real-time predictive score based on Textio’s proprietary dataset of hiring outcomes. The score updates as edits are made, so writers see immediately whether a change improves or reduces expected reach. T-Mobile saw 17% more women applicants and filled roles 5 days faster after maintaining high Textio Scores.
• Bias Detection Across Dimensions: The platform flags gender, age, disability, and neurodiversity coded language with specific word-level suggestions, not just a summary flag. Textio’s gender tone guidance shows if language is skewed and how to fix it, with gender-neutral content shown to resonate with the broadest applicant audience.
• Textio Verified Output: AI-generated drafts are pre-screened against Textio’s HR-specific model to reduce hallucinations and compliance risk before a writer sees the content. Everything Textio produces is screened to ensure it is safe for work, accurate, optimized for the task, and brand-aligned.
• Brand Customization: Organizations can program preferred vocabulary at the brand level, and those preferences apply across every draft the system generates.

Job Description-Specific Offerings:

• Textio Loop: Real-time scoring and rewriting of job posts, sourcing emails, and employer brand content
• Generative first drafts: Input a job title and key details; Textio produces an inclusive, data-backed draft
• Centralized job library: Store, version, and share approved job descriptions across teams with template management
• ATS integration: Extensions bring Textio directly into Workday, Greenhouse, and LinkedIn so guidance is available wherever teams write

Pricing: Starts at approximately $15,000/year. Mid-market teams typically land in the $30,000 to $75,000 range based on enterprise software transaction data. Enterprise pricing is custom. Plans include unlimited users and unlimited AI usage. A free trial option is available via the Textio website.

Pros:

• The deepest HR-specific bias detection in the category, trained on actual hiring outcomes rather than general language data
• Extends beyond job descriptions to performance reviews and sourcing outreach, making it a full HR writing platform rather than just a JD tool
• Real-time scoring gives writers immediate, actionable feedback at the word level
• Textio Verified output reduces the hallucination and inappropriate content risk common in general-purpose AI
• Serves over 25% of the Fortune 500, with customers including McDonald’s, Procter & Gamble, and Cisco

Cons:

• English-only support, which is a real constraint for organizations hiring in EMEA, LATAM, or APAC
• Implementation and adoption can take several weeks to a couple of months, requiring stakeholder buy-in and brand configuration before the platform delivers full value
• At $15,000+ entry price, difficult to justify for teams hiring fewer than 10 roles per year
• Bias suggestions can become formulaic for specialized roles, flagging terms that are industry-standard and contextually appropriate
• Platform scope is focused on HR and recruiting workflows; it is not designed for general content writing needs

For an enterprise talent acquisition team running high-volume hiring with active diversity and inclusion goals, Textio earns its price point. The depth of outcome-backed scoring and the extension of the same bias detection logic into performance reviews separates it from any general-purpose alternative. The catch is that smaller teams and global organizations need to weigh the English-only constraint carefully before committing.

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2. Datapeople (by Payscale)

Datapeople was acquired by Payscale in September 2025, creating the first major platform to directly connect compensation data and job posting content in a single workflow. For recruiting operations teams navigating pay transparency compliance across multiple jurisdictions, that integration is the most practically useful development in this category over the past year.

Founded in 2015 and now operating as part of the Payscale portfolio, Datapeople was built on the premise that job descriptions should be informed by outcome data rather than writing conventions alone. Its predictive scoring system draws on more than 100 million job outcomes from 80 countries, giving its language recommendations a global evidence base that most competitors cannot match.

Key Features:

• First Draft AI: Generates a data-backed initial draft based on job title and location input. Drafts are informed by optimal language patterns drawn from Datapeople’s outcome dataset rather than general web content.
• Smart Editor with Color-Coded Bias Flagging: A five-category system identifies eight specific bias types, using yellow to flag patterns for review, red to surface harmful content to remove, and green to reinforce good language choices, so teams understand not just what to change but why.
• Pay Transparency Compliance Monitoring: Flags job postings missing salary disclosure in jurisdictions where it is legally required, and monitors compliance across a live job library.
• Payscale Integration: Now connects job description language directly to Payscale’s compensation benchmarking data, so the pay range added to a posting reflects the company’s actual compensation structure.

Job Description-Specific Offerings:

• Guidance and Compliance AI: Identifies potential bias, legal, and accessibility issues during the drafting process
• Competitive job benchmarking: Compare your posting against similar open roles from local talent competitors
• ATS sync: Integrates with Workday, Greenhouse, Lever, iCIMS, SAP, Taleo, and SmartRecruiters, eliminating manual copy-paste workflows
• Role-based permissions: Mirror your ATS access controls across the Datapeople editing workflow
• Analytics dashboards: Measure job content performance and compliance gaps across active postings

Pricing: Custom quotes based on team size and job volume. Average annual cost runs approximately $12,000, with observed deals reaching $30,000 based on enterprise software transaction data. Datapeople prices roughly 15-25% below Textio for comparable seat counts. No self-serve tier.

Pros:

• Outcome dataset covers 100M+ job postings across 80 countries, the broadest geographic training base in this category
• Pay transparency compliance monitoring is built in, not an add-on, which is important for global enterprises navigating rapidly expanding salary disclosure laws
• The Payscale acquisition adds direct compensation data integration, connecting TA content to comp strategy in a way no other tool in this category currently offers
• SOC 2 Type II certified with enterprise-grade security and compliance
• Pricing accessible relative to Textio, with visible analytics that give hiring managers data to act on rather than abstract scores

Cons:

• Acquired by Payscale in September 2025, meaning the roadmap is still being integrated and buyers should confirm product continuity plans directly with the vendor
• The AI generative writing feature handles common roles well but struggles with highly specialized positions in niche fields
• Does not cover performance management writing the way Textio does, the scope is narrower
• Some users report scoring inconsistencies between similar job descriptions, which creates confusion during approval reviews
• Requires existing ATS infrastructure, Datapeople manages the job content layer, not the candidate pipeline

Datapeople is the strongest choice for global organizations that need pay transparency compliance built into their job description workflow and that want recruiting analytics tied to actual outcome data. The Payscale acquisition adds genuine strategic value for teams where compensation and talent acquisition share ownership of job content, though buyers should confirm roadmap details given that the integration is still relatively recent.

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3. Ongig

Ongig’s Text Analyzer is the most volume-capable platform in this category, built for enterprise recruiting organizations that need to manage, audit, and publish hundreds or thousands of job descriptions simultaneously while maintaining compliance and brand consistency.

Ongig’s core differentiator is the breadth of its bias detection library. The platform scans job content for biased language related to gender, age, race, disability, LGBTQ+ status, ethnicity, former felons, elitism, mental health, religion, and more, combined with structured enterprise infrastructure including role-based approval workflows, version control, bulk editing, and ATS sync. Ongig’s software has demonstrated up to 13% increases in overall apply clicks and up to 21% increases in women’s apply clicks based on platform data.

Key Features:

• Text Analyzer with 12+ Bias Types: Detects gender, race, ethnicity, disability, LGBTQ+, age, mental health, neurodiversity, elitism, and religion-coded language in real time, with specific word-level recommendations and a 0-100 scoring system. Offers visual feedback on bias in content and flags exclusionary words that may negatively impact apply rates.
• AI JD Generation: Input a job title and let the platform generate a structured, bias-reviewed draft. The Optimize Content feature shortens sentences and reduces masculine bias automatically, with score increases visible in real time as changes are applied.
• Compliance Automation: Automatically flags and manages salary disclosure requirements for applicable state and federal regulations, adds required EEO statement sections, and scans for EEOC and OFCCP compliance gaps. Ongig is SOC 2 Type II certified.
• Enterprise Workflow Management: Route job descriptions through edit-review-approve workflows with customizable alerts, real-time dashboards, version tracking, and bulk editing across a centralized job library.

Job Description-Specific Offerings:

• Text Analyzer: Real-time inclusive language scoring and replacement on existing or newly drafted job descriptions
• From-scratch generation: Enter a job title, click generate, receive an AI-drafted description ready for editing and scoring
• ATS integrations: Connects with Workday, Greenhouse, iCIMS, Lever, and SAP SuccessFactors, with one-way or two-way API sync
• Pay transparency management: Automatically flags salary disclosure gaps and compliance risks at the posting level
• Custom templates: Role-specific and brand-consistent template management standardized across teams and locations

Pricing: Starts at approximately $11,999/year for the core enterprise platform, with a Lite tier available at approximately $4,900/year for smaller teams. Pricing is based on job volume and feature requirements. A demo is required for exact quotes.

Pros:

• Bias detection covers the broadest range of categories in this review, including neurodiversity, mental health, religion, and former felon status that most competitors miss
• Compliance automation for pay transparency, EEO, and OFCCP requirements systematically reduces legal risk for high-volume recruiting teams
• Enterprise workflow infrastructure, version control, bulk editing, role-based approvals, built for organizations managing hundreds of job descriptions simultaneously
• ATS sync keeps career site, ATS, and job library automatically aligned with no manual reconciliation
• Tiered pricing structure accommodates smaller team entry points relative to Textio

Cons:

• Platform depth is oriented toward volume management, lean teams with low posting frequency may not use enough of the infrastructure to justify the cost
• Demo required before pricing is available, creating friction for buyers comparing multiple tools on a fast timeline
• Multilingual support is more limited than Datapeople’s global coverage
• Interface requires training time for recruiting teams adopting the platform without IT support
• Independent third-party review data is less publicly available than for Textio

Ongig is the practical choice for recruiting operations teams managing job description quality at enterprise scale, particularly when compliance automation and bulk workflow management are priorities. For an organization publishing 500 or more job descriptions per year across multiple hiring managers and ATS environments, the infrastructure Ongig provides is difficult to replicate with lighter tools.

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4. GoHire

GoHire is a hiring platform built for startups and SMBs. Its AI job description generator sits within a broader ATS product and is the only free-access AI JD tool among the four reviewed here. For early-stage companies that have never used a dedicated job description tool, GoHire is the lowest-friction place to start.

The AI JD generator requires only a job title and company name to produce a draft covering role summary, responsibilities, and qualifications in under 30 seconds. That draft is a starting point, not a finished product. GoHire does not offer bias scoring, outcome-backed language recommendations, or compliance automation in the way that Textio, Datapeople, and Ongig do.

Key Features:

• Free AI Job Description Generator: Produces a structured first draft in under 30 seconds from job title and company name input, with 700+ customizable templates as starting options.
• Multi-Board Job Distribution: Publish job descriptions directly to 15+ job boards including Indeed, LinkedIn, and ZipRecruiter from a single posting action.
• Full ATS Functionality: GoHire is a complete applicant tracking system, candidate pipeline management, interview scheduling, team collaboration, and automated stage actions are all included at the paid tier.
• Careers Page Content Generator: Produces employer brand content for company career pages, keeping messaging consistent with active job postings.

Job Description-Specific Offerings:

• AI JD generator: Title-and-name input produces a 30-second role description draft, free to use with a GoHire account
• Job description templates: 700+ customizable options across roles and industries
• Multi-board distribution: One-click publish to 15+ job boards reduces distribution admin significantly
• AI interview question generator and onboarding checklist generator included in the platform’s free AI tools suite

Pricing: The AI job description generator is free with a GoHire account. Full ATS plans start at approximately $47/month on lower-tier plans, with the Starter plan beginning around £69/month, Growth at £99/month, and Pro at £165/month. A 14-day free trial with full access to all features is available. All plans include unlimited team members.

Pros:

• The AI JD generator is free, no enterprise contract, no sales call required to start generating drafts
• 14-day free trial with full platform access gives teams a genuine evaluation window before committing
• Combines ATS and JD generation in one platform, reducing tool sprawl for SMBs managing their full hiring workflow in a single place
• Simple interface consistently cited by users for ease of adoption with minimal training required
• Affordable pricing accessible to startups and growing SMBs without large HR budgets

Cons:

• No bias detection or inclusive language scoring, the generator produces drafts but does not flag exclusionary or gendered language
• No outcome-backed scoring, there is no predictive signal about how a generated posting will perform on candidate diversity or application volume
• No compliance automation for EEO, OFCCP, or pay transparency laws
• No ATS integration with Greenhouse, Workday, or other enterprise systems, GoHire is a standalone ATS, not a tool that layers on top of an existing platform
• Limited depth for specialized roles, drafts from complex or niche positions require significant editing
• Not recommended for organizations with more than 100 employees where advanced features and integration depth become necessary

GoHire answers a clear need: teams that are writing job descriptions manually today and want to see what AI-generated output looks like before investing in a dedicated platform. The catch is that the free generator produces a draft, not an optimized posting. For organizations where inclusive language, bias compliance, and outcome data matter, GoHire is a starting point only, not a substitute for Textio, Datapeople, or Ongig.

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Evaluation Rubric: How These Tools Were Scored

The ranking in this guide was built on a 100-point rubric applied consistently across all four tools. Each dimension was weighted based on its practical impact on hiring outcomes for the median TA buyer.

Evaluation Dimension	Weight	What Was Measured
Bias Detection Depth	30%	Number and specificity of bias types detected; whether flagging is word-level or category-level; whether suggestions are backed by outcome data or heuristics
Generative Writing Quality	20%	Usability of AI-generated first drafts across common and specialized roles; edit time required before a draft is publishable
ATS and Workflow Integration	20%	Depth of ATS integrations; whether sync is one-way or two-way; availability of approval workflows, version control, and template management
Compliance Automation	20%	Whether pay transparency, EEO, and EEOC/OFCCP requirements are monitored and flagged automatically or left to manual review
Pricing and Accessibility	10%	Entry-point cost, availability of free or trial tiers, and whether pricing scales reasonably for different team sizes

The weighting reflects what matters most to heads of talent and recruiting operations leaders making this decision with real hiring outcomes on the line. Teams with primarily diversity-focused mandates should weight bias detection more heavily. Teams focused on compliance risk should weight the compliance automation dimension. Lean teams with limited budgets should weigh pricing accessibility against their actual hiring volume to determine whether the ROI case closes.

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Why Enterprise TA Teams Choose Textio Over Alternatives

Textio scores highest in this review because it is the only platform in the category that was purpose-built on HR writing data from the start. The depth of its bias detection, the predictive score model, and the Textio Verified output standard reflect a level of HR-specific product investment that general-purpose AI writing tools and lighter-weight JD generators cannot match.

For teams where inclusive hiring is measurable and auditable, where legal and compliance teams are involved in job content review and where DEI goals are tied to recruiting metrics, Textio gives the evidence trail and the writing quality that the use case requires. T-Mobile saw 17% more women applicants and filled roles 5 days faster after adopting high-scoring Textio job descriptions. Duolingo now requires all job posts to maintain a Textio Score of 85 or above before going live, and they averaged a score of 90 across their job library within the first year. Those are the kinds of measurable results that justify the investment.

The honest trade-offs are real: English-only, no self-serve evaluation, implementation that can take weeks before teams are fully operational. For global teams or budget-constrained recruiting organizations, Datapeople or Ongig are viable alternatives with their own meaningful strengths. But for the core use case, enterprise HR writing quality with outcome-backed bias detection and a full library of brand-governed templates, Textio remains the benchmark.

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Choosing the Right AI Job Description Tool for Your Team

The decision comes down to four buyer profiles.

Choose Textio if your recruiting organization has an active DEI mandate, hires at volume in English-language markets, and needs bias detection that goes beyond gender coding into age, disability, and neurodiversity language. The price requires justification, but the ROI case is clearest when time-to-fill and applicant diversity are tracked metrics.

Choose Datapeople if you are a global enterprise with hiring operations across multiple jurisdictions and a growing compliance requirement around pay transparency. The Payscale integration is the most practically useful development in this category for organizations where compensation and talent acquisition share ownership of job content.

Choose Ongig if your team manages hundreds of job descriptions across multiple hiring managers, ATS environments, and brand voices, and the operational challenge is consistency, compliance automation, and workflow management rather than writing guidance alone.

Choose GoHire if your organization is a startup or SMB, you have never used a dedicated JD tool before, and the goal is to start generating AI-drafted job descriptions immediately with no contract commitment. Understand that the free generator is a drafting tool, not a bias-detection or compliance platform.

Job description quality is a recruiting ops problem, not just a writing problem. The tools that treat it that way are the ones worth buying.