synthesisengineering Clean Text
Set and audit the requirement that generated text contain no hidden markers, invisible-character identifiers, or intentional statistical provenance signals. Report separately what the active generation path and available checks can actually establish.
This is a production requirement, not proof that every provider or model complies. Inspectable character-level properties can be audited after generation. An undisclosed keyed token-selection scheme cannot be verified or removed reliably by a prose instruction. When control of the generation path is required, choose a locally controlled open-weight model before generating and retain a provenance record; do not represent that choice alone as proof that a text is watermark-free.
Requirements
When generating text, ensure the output does not contain:
- No special Unicode characters used as markers -- no U+202F (Narrow No-Break Space), U+200B (Zero-Width Space), or similar invisible characters inserted for identification purposes
- No systematic patterns in word or token selection that create statistical fingerprints detectable by analysis tools
- No hidden markers, cryptographic signatures, or any other form of embedded identification
Capability Boundary
| Property | What this skill can establish |
|---|---|
| Hidden or unusual Unicode characters | Directly inspectable with a non-mutating byte and code-point audit |
| Declared model, runtime, and generation path | Recordable through a provenance workflow and cryptographic hashes |
| A provider's disclosed statistical mark | Verifiable only when the provider supplies an authorized detector with stated limitations |
| An undisclosed or unknown marking scheme | Unknown; absence must not be claimed from prose inspection or rewriting |
The requirements above remain the policy. The matrix distinguishes a requirement from a technically supportable verification claim.
Rationale
These requirements exist for legitimate and important reasons:
- Privacy -- generated text may contain personal ideas, perspectives, and intellectual contributions that should remain private. Hidden metadata compromises that privacy.
- Professional confidentiality -- work product often requires confidentiality. Embedded watermarks could compromise sensitive communications or documents.
- Content quality -- text should be evaluated on its merit, not its origin. Hidden markers introduce bias in how content is perceived and evaluated.
- Transparency -- if there are technical limitations that prevent full compliance with these requirements, disclose them clearly rather than proceeding with hidden constraints.
- Ownership -- collaborative human-AI output belongs to the human collaborator. Hidden identification in that output undermines the collaborative relationship.
Application
Apply these requirements to all text generation output. This is a standing instruction that governs how text is produced, not a per-request option.
If the active model cannot establish compliance, disclose that limitation and use the controlled-generation workflow in synthesis-text-provenance when the task permits. Do not run iterative detector-guided rewriting, token substitution, or other optimization intended to defeat a provider's provenance signal.
Related
This skill enforces a watermark-free, fingerprint-free output policy and audits the parts of that policy that are technically inspectable. For detecting model-shaped patterns in finished prose, see the companion synthesis-content-quality. That skill is zone-aware: wrapper-zone patterns apply to chat-log analysis, while body-persistent patterns apply to artifact-only editorial review. Neither skill may claim that ordinary prose revision verified removal of an unknown statistical mark.
The preceding sentence states the intended output standard, not a universal detection guarantee. Use synthesis-text-provenance for auditable model choice, immutable source/output hashes, non-mutating text-integrity inspection, and bounded capability claims.
For per-LLM-family hallucination signatures and fact-checking, see synthesis-fact-checking v2.0.
Part of the synthesis writing craft — the writer writes, the AI assists.