Preface

The drafting of bids and tenders increasingly relies on models, which brings with it a set of recurring issues: boilerplate sentence structures, piled-up vocabulary, mismatched data, and residual formatting errors—all resulting in an obvious “AI tone.” Manual review paragraph by paragraph is time-consuming, and missing a single detail can easily lead to being flagged during evaluation. Laomo AI-Tone Removal Master (老默去AI味道大师) acts as a gatekeeper to address this problem: it turns “de-AI-ification” into an executable detection process. Covering eight dimensions—vocabulary, templates, content, rhetoric, data, consistency, output cleanliness, and layout rhythm—it performs a unified scan on drafting outputs such as technical bids, commercial bids, proposals, and reports.

The following introduces the positioning, capabilities, and usage of this Skill.

What is this

Laomo AI-Tone Removal Master (located at @user_f67fc7cb/lm-qaiwd-skill) is a community-sourced “De-AI” Skill for bid drafting. The publisher is user_f67fc7cb, categorized under office-efficiency, version 1.0.0, with a declaration of no API Key required (requires_api_key=false). It focuses on a specific problem set: intercepting AI traces, false content, redundancy, and formatting issues common in the drafting process through a mandatory process, rather than relying on fragmented manual checks.

The official one-sentence summary is: “A skill for removing AI flavors from tender documents.”

Core Functions

According to the Skill’s description, it provides an eight-layer detection system corresponding to several typical problems in drafting outputs:

  1. Vocabulary Layer: Screens for template-based wording and piled-up modifiers.
  2. Template Layer: Identifies monotonous sentence structures.
  3. Content Layer: Removes vague expressions such as “empty writing” (vague descriptions) and “pseudo-narratives.”
  4. Rhetoric Layer: Corrects over-commitment and exaggerated rhetoric.
  5. Data Layer: Verifies data authenticity, performs anti-hallucination checks, and enables traceability.
  6. Consistency Layer: Checks for self-consistency in expressions and logic throughout the document.
  7. Output Cleanliness Layer: Cleans up residual formatting, marks, and other “dirty” outputs.
  8. Layout Rhythm Layer: Regularizes tables and paragraphs to avoid messy layouts.

The official positioning positions this detection suite as the sole entry point and mandatory gatekeeper for “De-AI-ification” within the bidding system, covering all drafting outputs including technical bids, commercial bids, proposals, and reports. It is forcibly auto-loaded during stages such as drafting, polishing, review, audit, and re-verification. Trigger keywords include: De-AI / AI flavor / Simplify / Reduce / Bid optimization / Tender documents / Technical proposals / Polish / Remove AI traces / AI fingerprints / Six-layer detection / Seven-layer detection / Eight-layer detection / Output cleanliness / Layout rhythm / Table regularization / Paragraph alignment / Red line / Anti-hallucination / Traceability / Bid review / Technical bid review / Audit / Re-verify / Quality check / Bid self-check.

Note: This eight-layer system, trigger keywords, and the “mandatory gatekeeper” positioning are derived from the Skill’s own description. The official snippet captured contains only the single sentence “A skill for removing AI flavors from tender documents.” The two differ in detail and scope.

Installation and Activation

Publicly available information does not provide directly executable installation commands or directory paths. Currently, it is confirmed that this Skill is published on SkillHub at coordinates @user_f67fc7cb/lm-qaiwd-skill, with a source of “community,” and a tag declaration of requires_api_key=false. Therefore, no API Key preparation is needed before activation. However, the documentation does not specify which client (Cursor, Codex CLI, Claude Code, etc.) to use for loading it, and this article makes no speculation on this matter.

Typical Usage

The available reproducible workflow comes from the official description of trigger conditions:

  1. When drafting, polishing, reviewing, auditing, or re-verifying technical bids, commercial bids, proposals, reports, or tender copy, the Skill will automatically load based on trigger keywords.
  2. Once loaded, it scans the current drafting output item by item across the eight layers. It focuses on handling AI tone removal, removing vagueness, removing falsities, removing redundancy, and removing format residues, while performing authenticity and traceability checks on data.
  3. The scan results are used for revision to ensure the output meets the “De-AI-ification” gatekeeper requirements.

Applicable Scenarios and Notes

It is suitable for individuals who frequently produce bidding documents such as technical bids, commercial bids, proposals, and reports, and wish to reduce AI traces and data errors. Its value lies in solidifying fragmented manual checks into a unified process.

The limitations lie here as well: Official public materials do not elaborate on the specific judgment criteria, rule details, and scoring standards for the eight-layer detection. The actual effectiveness needs to be verified on your own documents. Additionally, as this Skill is community-sourced, it is recommended to review its detection rules personally before use to avoid misjudgments.

Conclusion

Laomo AI-Tone Removal Master transforms “De-AI-ification” from manual paragraph-by-paragraph reading into an executable eight-layer detection gatekeeper. It covers vocabulary, templates, content, rhetoric, data, consistency, output cleanliness, and layout rhythm, applicable to drafting outputs like technical bids, commercial bids, proposals, and reports. Official URL: https://api.skillhub.cn/user_f67fc7cb/lm-qaiwd-skill