KI-Negativmuster in Texten.

The opening explains the author's framework before making the reader's next action or question clear.

Possible cues: long conceptual preface; implementation taxonomy before first action.

Exceptions: A conceptual essay may aim to establish a framework; a reference page may serve lookup rather than onboarding.

• Microsoft Learn style and voice quick start

  Organize technical documentation around the customer's task; limit distracting qualifiers and asides. A documentation style policy, not empirical evidence about LLM prevalence or factual truth.

Sections repeat the same conclusion, stock transition or fixed template without adding a distinct fact or helping comparison.

Possible cues: repeated wrap-up paragraphs; identical feature-benefit cadence; synonymous summaries.

Exceptions: API references, accessibility cues and parallel comparisons benefit from deliberate consistency. Repetition does not establish machine authorship.

• Use simple words, concise sentences

  Prefer precise verbs and consistent terminology; remove words that add no information. Context and meaning still determine whether a modifier or longer explanation is needed.

• Linguistic and Embedding-Based Profiling of Texts Generated by Humans and Large Language Models

  Reports aggregate linguistic and semantic variation across eight domains and eleven models. Abstract reviewed. Distributional differences are not per-sentence defects, a detector, or a ranking of current Claude/Codex writing quality.

Structure obscures a sequence, comparison or explanation, or an informational heading fails to identify the section's topic or reader task.

Possible cues: one-sentence subsections; nested lists without hierarchy; bold labels on every sentence.

Exceptions: Long references need navigation; procedures need steps; comparison tables can reduce rather than add reading work. A question heading is useful when readers ask that question and the section answers it. An accepted positioning headline can prioritize tone and memorability.

• OpenAI model guidance: Personality and writing style

  Explicit control of prose, terminology and repeated rhetorical patterns. Rolling model documentation; not a comparative study or a rule for every OpenAI/Codex output.

• Claude prompting best practices

  Positive directions and examples can specify the desired output style. Provider advice, not proof that this catalogue improves a particular model. The document describes different defaults across models.

• Measuring AI ‘Slop’ in Text

  Reader judgments depend on relevance, information and structure in the evaluated domains. English news and QA with a small expert panel. Context for review criteria, not proof that these prompts improve models.

• Problem Patterns in AI: Beyond Hallucinations

  Practitioner examples distinguish requested information from added interpretation. Editorial observations and an informal poll; no measured failure rates or established training causes.

Optional controls, deep implementation details or tangential background interrupt the shortest complete route to the stated task.

Possible cues: layout settings before first review; authentication protocol before opening the app; unrelated architecture aside.

Exceptions: A prerequisite or material failure mode may be essential before the action; reference pages intentionally contain detail.

• Microsoft Learn style and voice quick start

  Organize technical documentation around the customer's task; limit distracting qualifiers and asides. A documentation style policy, not empirical evidence about LLM prevalence or factual truth.

An answer to a bounded task becomes an exhaustive list of possible concerns, with no ordering by relevance or dependency.

Possible cues: consider A, B, C and many unrelated topics; flat list of optional and required work.

Exceptions: A requested exhaustive inventory, compliance checklist or API reference needs complete coverage. Preserve actual dependencies and material risks.

• Microsoft Learn style and voice quick start

  Organize technical documentation around the customer's task; limit distracting qualifiers and asides. A documentation style policy, not empirical evidence about LLM prevalence or factual truth.

A fixed rhetorical template determines the number and shape of points instead of the actual ideas, or filler is added to complete a triad.

Possible cues: why X? because Y repeated without an actual reader question; a third point added only to complete a triad.

Exceptions: A real FAQ, a mnemonic with three necessary parts, deliberate approved positioning and parallel API entries can justify a recurring form.

• OpenAI model guidance: Personality and writing style

  Explicit control of prose, terminology and repeated rhetorical patterns. Rolling model documentation; not a comparative study or a rule for every OpenAI/Codex output.

• Linguistic and Embedding-Based Profiling of Texts Generated by Humans and Large Language Models

  Reports aggregate linguistic and semantic variation across eight domains and eleven models. Abstract reviewed. Distributional differences are not per-sentence defects, a detector, or a ranking of current Claude/Codex writing quality.

A usage guide mixes implemented behavior with proposals, temporary rollout history or hypothetical capabilities.

Possible cues: will support; would allow; in a future release.

Exceptions: Roadmaps, migration guides and release notes intentionally discuss time and change; asynchronous behavior may require future tense.

• Present tense

  Describe general implemented behavior in the present; preserve future tense for actual future timing. Grammar alone cannot determine feature maturity.

• Future features

  Keep unannounced future capabilities out of ordinary product documentation. Google's internal publication-approval requirement is not adopted as a Voice authorization rule. Explicit plans remain valid document types.

Stacked hedges weaken a verified fact, or a suggested simplification would remove an actual condition, unknown or risk.

Possible cues: generally may perhaps; preferred without a stated alternative; repeated generic disclaimers.

Exceptions: Scientific uncertainty, security conditions, configuration dependence, estimates and genuine alternatives require qualification.

• Microsoft Learn style and voice quick start

  Organize technical documentation around the customer's task; limit distracting qualifiers and asides. A documentation style policy, not empirical evidence about LLM prevalence or factual truth.

A feature is followed by a benefit, conclusion or recommendation that the provided evidence does not establish.

Possible cues: therefore reduces cognitive load; this ensures success; because it is Git-based.

Exceptions: A documented mechanism, bounded measurement or explicitly stated hypothesis can justify a causal explanation.

• Prompting Claude Fable 5

  Connect status to observed results and explain outcomes without private working shorthand. Guidance for a named model and agentic setting; not a general claim about all Claude versions.

A count, superlative, guarantee, release claim or evaluative modifier exceeds the observed scope, omits its decision criterion, or treats plausible source text as verified product behavior.

Possible cues: all pages verified; production-ready; guaranteed improvement; percentages without conditions; valid exceptions without a stated criterion.

Exceptions: An exact API invariant or properly scoped measurement can support absolute wording. A stated decision criterion can justify a modifier. For example, valid JSON names a syntactic requirement; it does not mean that a schema was checked. Exception criteria may be supplied by the adjacent rule instead of repeated in every heading.

• Prompting Claude Fable 5

  Connect status to observed results and explain outcomes without private working shorthand. Guidance for a named model and agentic setting; not a general claim about all Claude versions.

• Use simple words, concise sentences

  Prefer precise verbs and consistent terminology; remove words that add no information. Context and meaning still determine whether a modifier or longer explanation is needed.

A progress or completion claim lacks a matching tool result, or success in one check is presented as broader readiness.

Possible cues: done without result evidence; tests passed used as editorial approval; source push described as deployment.

Exceptions: A brief result can refer to an accessible report rather than repeat every log line. Verified results do not need speculative hedging.

• Prompting Claude Fable 5

  Connect status to observed results and explain outcomes without private working shorthand. Guidance for a named model and agentic setting; not a general claim about all Claude versions.

A request for assessment receives flattering approval without a specific reason, or the answer changes its factual position only to agree with the user.

Possible cues: brilliant idea without assessment; you are absolutely right before checking; reflexive praise before critique.

Exceptions: A supported compliment, ordinary warmth and an explicit celebration are valid. Agreement is appropriate when the evidence supports it.

• Sycophancy in GPT-4o: what happened and what we’re doing about it

  Documents a specific GPT-4o update that became excessively agreeable and was rolled back. A historical provider incident, not proof that current OpenAI, Codex or Claude output is generally sycophantic.

• OpenAI Model Spec, 18 December 2025

  Describes evidence-proportionate treatment of viewpoints and constructive critique rather than reflexive agreement. A statement of intended behavior, not a measured account of model compliance or a mandate to choose a side when evidence is missing.

An evidence-based question is answered with interchangeable pros and cons or a generic “both are valid” despite a material difference already established in context.

Possible cues: both options are equally valid despite contrary evidence; it depends without naming the dependency.

Exceptions: Genuine uncertainty, value tradeoffs and comparably supported alternatives require balanced treatment. A request to explain a viewpoint is not an endorsement request.

• OpenAI Model Spec, 18 December 2025

  Describes evidence-proportionate treatment of viewpoints and constructive critique rather than reflexive agreement. A statement of intended behavior, not a measured account of model compliance or a mandate to choose a side when evidence is missing.

An abstract label leaves the reader unable to identify what data exists, where it lives or what operation happens.

Possible cues: source of record; mechanism; ecosystem alignment; orchestration surface.

Exceptions: A defined domain term is useful in a specialist reference; a concept may require explanation before implementation detail.

• Avoid jargon

  Specialist shorthand can help a specialist audience and obstruct other readers. Does not justify banning technical terms or identifying the author of a sentence.

New compound labels, unexplained abbreviations or synonyms force the reader to infer concepts that already have stable names.

Possible cues: hyphen-stacked labels; multiple names for one field; private working shorthand.

Exceptions: Exact API identifiers, established specialist terms and intentionally defined concepts must remain stable.

• Avoid jargon

  Specialist shorthand can help a specialist audience and obstruct other readers. Does not justify banning technical terms or identifying the author of a sentence.

• Prompting Claude Fable 5

  Connect status to observed results and explain outcomes without private working shorthand. Guidance for a named model and agentic setting; not a general claim about all Claude versions.

A rhetorical opposition introduces an alternative the audience did not need to distinguish, instead of explaining the actual behavior.

Possible cues: not X, but Y; this is not about; rather than merely.

Exceptions: Comparing version semantics, correcting a likely misconception or preserving approved positioning can require a contrast.

• OpenAI model guidance: Personality and writing style

  Explicit control of prose, terminology and repeated rhetorical patterns. Rolling model documentation; not a comparative study or a rule for every OpenAI/Codex output.

Compression removes the subject, condition or relationship needed by a reader who did not follow the working session.

Possible cues: dense arrow chains; unexplained identifier sequences; fragment-only result reports.

Exceptions: Diagrams, table cells, button labels and familiar notation can be concise fragments.

• Prompting Claude Fable 5

  Connect status to observed results and explain outcomes without private working shorthand. Guidance for a named model and agentic setting; not a general claim about all Claude versions.

Ornamental wording obscures the subject or operation, or asks readers to interpret a metaphor without useful explanatory detail.

Possible cues: facilitate the execution of; robust seamless workflow; powerful mechanism.

Exceptions: A defined technical adjective or an approved quotation can be exact and useful; word-list membership is not a defect. An explanatory metaphor can make a mechanism easier to understand; accepted positioning may deliberately use rhythm or figurative wording.

• Use simple words, concise sentences

  Prefer precise verbs and consistent terminology; remove words that add no information. Context and meaning still determine whether a modifier or longer explanation is needed.

• Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Edits

  Distinguishes distracting ornament, vague detail and awkward phrasing in expert edits. Creative-writing study. Applying its categories to informational headings is an editorial derivation, not a measured heading detector.

The deliverable recounts abandoned approaches, internal filenames or conversation turns that do not explain the present result.

Possible cues: we initially considered; after your earlier feedback; during this session.

Exceptions: Decision records, incident reports, changelogs and research notebooks need history and provenance.

• Prompting Claude Fable 5

  Connect status to observed results and explain outcomes without private working shorthand. Guidance for a named model and agentic setting; not a general claim about all Claude versions.

• Microsoft Learn style and voice quick start

  Organize technical documentation around the customer's task; limit distracting qualifiers and asides. A documentation style policy, not empirical evidence about LLM prevalence or factual truth.

Framing adds an interpretive premise or result promise unsupported by the supplied material, or announces importance without useful scope.

Possible cues: it is worth noting; this section clearly explains; the key thing to understand.

Exceptions: A short scope sentence can distinguish a protocol reference from a tutorial or identify excluded versions. A result heading can state a supported conclusion. An accepted positioning headline is not automatically an unsupported factual claim.

• OpenAI model guidance: Personality and writing style

  Explicit control of prose, terminology and repeated rhetorical patterns. Rolling model documentation; not a comparative study or a rule for every OpenAI/Codex output.

• Problem Patterns in AI: Beyond Hallucinations

  Practitioner examples distinguish requested information from added interpretation. Editorial observations and an informal poll; no measured failure rates or established training causes.

• Measuring AI ‘Slop’ in Text

  Reader judgments depend on relevance, information and structure in the evaluated domains. English news and QA with a small expert panel. Context for review criteria, not proof that these prompts improve models.