declaude
declaude rewrites Claude assistant outputs from verbose assistant-voice into plain English while keeping code blocks, lists, and document structure intact. It runs on Qwen2.5-14B on declaude's own infrastructure, processing text in memory and discarding it immediately without logging or database storage. Deployment options include a Claude Code plugin (automatic reply rewriting), MCP server (browser sign-in, no key pasting), or API endpoint for custom integrations. The free tier supports 100 translations and 5 documents monthly; the paid tier ($5/month) unlocks unlimited translations and 500 documents monthly. Best suited for AI content agencies, technical writing shops, and documentation teams that already resell Claude-based workflows and need to reduce manual output cleanup.
declaude is an AI text generator, priced at $5/month on the Paid plan, integrating with Claude Code, MCP, GitHub, and Qwen2.5-14B. InnovaAI scores it 5/10 for agency resale.
Agency Audit
declaude strips verbose Claude outputs into plain English while preserving code blocks and document structure, running on Qwen2.5-14B via its own infrastructure. It integrates as a Claude Code plugin, MCP server, or standalone document processor, making it relevant for AI content agencies, technical writing shops, and documentation teams that resell Claude-powered workflows. The free tier (100 translations/month) supports light testing; the paid tier ($5/month) unlocks unlimited translations and 500 documents monthly. Resale potential exists primarily as an add-on to existing Claude retainers rather than a standalone product.
5.0/10
48%
1d about a day
- You deliver Claude-based content or technical writing retainers and clients complain about verbose assistant replies that require manual cleanup.
- Your agency uses Claude Code for client projects and wants to automate output formatting without touching transcripts or token counts.
- You process Markdown documentation for clients and need a rewrite layer that preserves code blocks and structure while simplifying language.
- Your clients use ChatGPT, Gemini, or other non-Claude AI assistants as their primary tool; declaude only processes Claude outputs.
- You need white-label branding for client-facing surfaces; declaude displays its own brand in the interface.
- You require HIPAA or SOC2 Type II compliance; the content does not document these certifications.
Profit Path
$5/mo
$600–$1.5K/project
Hybrid
From 242 published agency rates in USA, 25th to 75th percentile x 20h of assumed delivery time. Rates are self-reported directory profiles, not observed transactions.
Platform Features
Core capabilities of declaude
Claude Code plugin installation
Two commands hook declaude into Claude Code, rewriting replies in plain English without modifying transcripts or token billing. Agencies can deploy this across client accounts without manual intervention per conversation.
MCP server with browser sign-in
Run declaude as an MCP server over HTTP, eliminating API key pasting and simplifying client onboarding. Supports browser-based authentication for non-technical team members.
Markdown document batch processing
Upload Markdown files up to 2 MB (paid tier) and receive rewritten versions with code blocks and structure intact. Useful for agencies processing client documentation backlogs in bulk.
Code and structure preservation
Rewrites only natural language passages; code blocks, lists, and formatting survive unchanged. Critical for technical writing and documentation agencies where output structure must remain intact.
On-device processing with no logging
Text is processed in memory on declaude's own GPUs and discarded immediately; never written to disk, databases, or logs. Reduces data residency concerns for agencies handling client content.
API endpoint for custom integrations
POST requests to the translate endpoint allow agencies to embed declaude into custom workflows, client dashboards, or internal tools without relying on plugin or MCP deployment.
What Makes declaude Different
Unique advantages vs similar tools in this niche
Preserves code and structure while rewriting
vs Generic paraphrasing tools that may break formattingThe tool explicitly states that meaning, code, and structure survive intact.
Runs on open-source model on own GPUs
vs Cloud-based AI services with data retentionText is processed in memory and discarded, never written to disk, a database, or logs.
Multiple integration methods
vs Single-interface rewriting toolsOffers a Claude Code plugin, MCP server, and document processor for flexible usage.
Investment ROI Calculator
Value equation analysis for declaude, based on the Hormozi framework
What is the Hormozi framework? A four-factor score: (what the service delivers × how reliably it delivers) divided by (how long it takes × how much effort it requires). A higher Value Multiplier means a better return on the time and money invested: faster, easier, and more proven results.
2.2× value multiple: invest $5/mo and agencies typically charge $600–$1.5K/project for the work it powers.
Why This Succeeds
Higher is betterClient Results Potential
What your clients actually get
Incremental gains: position as part of a larger solution stack
declaude rewrites assistant-voice into plain English. Meaning, code, and structure survive intact.
Reliability Score
How consistently this delivers results
Early-stage track record: validate with a small pilot first
Runs on an open-source model (Qwen2.5-14B) on our own GPUs.
Implementation Challenges
Lower is betterTime to First Revenue
How long until you can start earning
Fast launch: about a day to first delivery
Get started within hours: minimal setup required
Setup Effort
What it takes to get running
Near-turnkey: minimal setup before you can sell
Low effort: self-service setup with guided onboarding
Viable opportunity. declaude returns 2.2× on investment. Focus on the highest-margin service packages to maximize return.
Pricing
declaude platform cost to your agency
Paid: $5/mo
Free
- 100 translations per month
- 5 documents per month, 200 KB
- No card required
Paid
- Unlimited translations
- 500 documents per month, 2 MB
No verified white-label program for declaude: client-facing delivery runs under the platform's native branding.
Reality Check
declaude depends entirely on Claude as the upstream output source, so it only adds value if your clients are already using Claude extensively. The $5/month paid tier has a modest ceiling for per-client MRR, making it viable only as a bundled feature rather than a standalone retainer line item.
Low effort: self-service setup with guided onboarding
How This Accelerates White-Label Services
Who It's For
- ✓ai-content-agencies
- ✓technical-writing-agencies
- ✓documentation-agencies
Acceleration Steps
- 1Sign up and connect your account
- 2Configure rewrite verbose ai assistant outputs into plain english
- 3Connect Claude Code
- 4Launch your first client project
Academy for declaude
Work through it in order: the course for this service first, then the modules behind it.
Course for this service
declaude Agency Implementation, Productizing AI Output Cleanup
Learn how to integrate declaude into your Claude-based workflows to eliminate manual output editing and deliver polished client deliverables at scale. This course covers plugin deployment, MCP server setup, batch document processing, and pricing models for reselling plain-English rewrites as a standalone service or add-on to existing AI content packages.
Open the courseNo Academy modules are published for this service yet. Browse the full Academy
Why this category matters
The commercial case before the tooling.
Core concepts
The mental model you need to price and scope the work.
- Editorial Layer PremiumConcept
Editorial Layer Premium is the pricing model that separates agencies charging $150 per post from those charging $2,500 for the same word count. The generator is the commodity input; the billable asset is the judgment applied on top: voice enforcement, claim verification, source selection, and the decision about what not to publish. Forrester's September 2026 analysis argues private AI deployments outperform public tools for B2B marketing precisely because shared model access erases differentiation, which means two agencies running the same prompt on the same public model deliver near-identical drafts. The layer above the draft is where retainers survive. ContentIQ illustrates the mechanic in product form: it retrieves sources, tests each claim, and discards unsupported ones before writing, so the deliverable ships with a verification trail a client can audit. An agency selling that trail sells judgment. An agency selling raw output sells typing time, and typing time reprices toward zero at every renewal.
- Editorial Layer PremiumConcept
The generator is the cheap part; the editorial layer is the billable part. Agencies that price AI text work by output volume compete against every freelancer with a $20 subscription, and that pitch collapses at renewal. Agencies that price the judgment around the output (voice enforcement, claim verification, source quality, citation readiness) hold rate. ContentIQ illustrates the split: it retrieves sources, tests each claim, and discards unsupported ones before writing, which is editorial policy expressed as tooling rather than typing speed. The same logic explains why a rule like Thomas Ptacek's, restricting LLMs to copyediting human drafts, is a pricing position and not a purist stance. When a client asks what they are paying for, the answer is the layer that decides what is true and what sounds like them. Sell that layer, and the generator becomes a cost line you can swap without renegotiating the retainer.
- Commodity Collapse ThresholdConcept
The Commodity Collapse Threshold is the point at which a client stops paying for text output and starts paying only for judgment about voice, claims, and sourcing. Every AI text generator in this category can produce a 1,200-word draft in under two minutes, so the typing itself has no defensible price. What holds margin is the layer above generation: brand-voice enforcement, fact-checking against real sources, and citation flow. ContentIQ illustrates the pattern by retrieving sources and discarding claims that fail verification before an article is written, which is editorial work a bare generator cannot do. Forrester's September 2026 analysis makes the same point at the model level: shared public models erase differentiation, so two agencies running identical prompts ship near-identical drafts. Agencies that price the generator hit the threshold within one renewal cycle. Agencies that price the editorial layer keep the retainer.
Decision and risk
How to judge the fit, and the ways it goes wrong.
- AI Text Generators Rule: Price the Editorial Layer, Not the TypingEvaluation Rule
Sell and price the editorial layer (voice enforcement, claim verification, source flow) as the deliverable, and treat the generator as an internal cost input rather than the product.
- When Two Agencies Share One Model, Sell the Source TrailEvaluation Rule
Sell the editorial layer (voice rules, claim verification, source trail) and treat the generator as interchangeable typing capacity.
- AI Text Generators Decision: Editorial Layer vs Generator ResaleDecision Framework
IF a client's content need is volume with a defensible voice, claim standard, and citation trail, THEN sell the editorial layer (style guide, fact-check pass, source panel) on top of a generator and price the retainer against judgment hours. IF the client only wants cheaper words and will not fund review, THEN resell raw generation and expect the account to reprice to commodity within one renewal cycle.
- The Commodity Draft Trap: Why AI Text Generators Stall Agency Retainers After the First RenewalFailure Pattern
- The Citation Collapse: Why AI Text Generators Lose Client Trust When Claims Outrun SourcesFailure Pattern
Delivery system
Blueprints and procedures for running it as a service.
- Editorial Layer Retainer Build (10-14 days)Implementation Blueprint
A productized engagement that wraps AI text generators in the editorial controls clients actually pay for: voice governance, claim verification, and source flow. Agencies sell judgment and accountability, not typing speed.
- Source Verification Gate (QA)Operating Procedure
- Brand Voice Intake and Style Guide Lock (Onboarding)Operating Procedure
- Editorial Layer Handoff to Client Review (Handoff)Operating Procedure
13 modules selected for declaude
Frequently Asked Questions
Answers about pricing, setup, implementation
declaude rewrites verbose Claude assistant outputs into plain English while preserving code blocks, lists, and document structure. It runs on Qwen2.5-14B and can be deployed as a Claude Code plugin (automatic reply rewriting), MCP server (browser sign-in), or document processor (batch Markdown rewriting). Agencies use it to reduce manual cleanup of Claude outputs in client workflows.
declaude offers 2 pricing tiers, at $5/mo (Paid). Agencies typically achieve 48% profit margins when reselling to clients.
No verified white-label program. Client-facing surfaces display the declaude brand, so you cannot present a fully branded interface to end clients. The tool is best positioned as a backend utility for your own Claude workflows rather than a client-facing product.
Yes. declaude is available as a native Claude Code plugin (installed via /plugin marketplace add tenkenco/declaude) and as an MCP server over HTTP (claude mcp add --transport http). Both integrations support browser-based or key-based authentication without requiring separate infrastructure.
Claude Code plugin setup takes under 2 minutes (two commands in Claude Code settings). MCP server setup requires configuring the HTTP endpoint once at the agency level, then clients authenticate via browser. Document processing requires no setup; clients can upload files immediately after account creation.
AI content agencies that resell Claude-powered writing or research retainers, technical writing agencies producing API documentation or developer guides, and documentation agencies managing Markdown-based knowledge bases. Any vertical where clients generate Claude outputs that require language simplification without structural changes.