360 Secure SkillHub
360 安全技能中心

ontoAI QC Plus

面向 AI 交付物的出厂质检 Skill:对文章、报告、代码、数据表、幻灯片、PDF、网页及组合产物按六维度扫描,识别 AI 残留(中英规则包)、事实与一致性问题、合规风险,按影响分四档给出必改/可改/存疑/通过,并生成中英双语四风格 HTML/PDF/Markdown 报告;默认只报告不改稿,质检能力通过按次付费的外部网关提供。

ontoai
热度 36.83
最近更新 2026-10-13 04:57:06
分类:效率依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:校对润色 / 报告撰写 / 代码审查 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add ontoai/ontoai-qc-plus-en
Metadata
name
ontoai-qc-plus-en
slug
ontoai-qc-plus-en
displayName
ontoAI QC Inspector Plus
summary
Pre-delivery QC for AI artifacts — one-pass detection of AI residue, content errors and compliance risks; bilingual four-style reports. CNY 1.9 per call.
license
Commercial
tags
["AI QC","AI residue detection","delivery quality"]
pricing
{"model":"per_call","amount_fen":190}
version
2.1.2
display_name
ontoAI QC Inspector Plus
display_name_zh
ontoAI QC Inspector Plus
display_name_en
ontoAI QC Inspector Plus
description_zh
The last gate before delivery! ontoAI QC Inspector Plus detects AI residue, content errors and compliance risks (RL1-RL4, six dimensions, L1-L7) in articles, reports, code, tables and decks; bilingual four-style reports. CNY 1.9 per call; monthly rule updates and priority support.
description
The last gate before delivery! ontoAI QC Inspector Plus detects AI residue, content errors and compliance risks (RL1-RL4, six dimensions, L1-L7) in articles, reports, code, tables and decks; bilingual four-style reports. CNY 1.9 per call; monthly rule updates and priority support.
description_en
The last gate before delivery! Every AI deliverable passes QC here — ontoAI Quality Inspector Plus. One-pass detection of AI residue, content errors and compliance risks (RL1–RL4 residue tiers, six QC dimensions, L1–L7 compliance lines incl. China Advertising Law and FTC truth-in-advertising) across articles, reports, code, data tables, slides, PDFs, web pages, audio/video and combined artifacts. Outputs bilingual four-style QC reports (HTML/PDF) with a four-tier verdict: Must Fix / Should Fix / Unverified / Passed. Report-only by default; never edits without confirmation; never fabricates. Plus edition: per-call billing CNY 1.9; monthly rule-pack updates, blockchain-notarized rule base (cert CZ20260215641694), priority support. Triggers: QC this, quality check, pre-delivery check, can I ship this, ontoAI QC.
allowed-tools
["Read","Write","Edit","Grep","Glob","AskUserQuestion","WebSearch","WebFetch"]
metadata
{"product":"ontoAI Quality Inspector","tagline":"The Final Gate Before Delivery","publisher":"天津市微数人工智能科技有限责任公司 (Tianjin Weishu Artificial Intelligence Technology Co., Ltd.)","copyright":"天津市微数人工智能科技有限责任公司","version":"2.1.2","edition":"Plus pay-per-call (CNY 1.9 per invocation, settled via WeChat Pay X402 gateway)","language":"English primary; rule packs selected by artifact language via DATA.lang (zh rule pack in Chinese, en rule pack in English)","revision":"2026-10-13"}

ontoAI Quality Inspector

The Final Gate Before Delivery

Plus Edition · CNY 1.9 per call (per-invocation billing via WeChat Pay X402 gateway) Full QC kernel — pay per QC run, monthly rule updates included.

Billing & X402 Payment Contract (Pay Skill)

This is a Pay Skill billed per invocation at CNY 1.9, settled through Weishu AI's own WeChat Pay X402 gateway. Agents invoking this skill must handle payment per the X402 protocol flow below:

  1. Send the QC request: POST to https://www.ontoagent.net/qc402/api/resource with body {"query": "<artifact to inspect>", "scenario": "<optional>", "lang": "en"}. The lang field makes the WeChat payment order show the English product description — always include it.
  2. Receive the 402 Payment-Needed: if the request carries no X-Out-Trade-No header, the gateway returns HTTP 402. Both the response headers and body carry WeixinPay-Required (the payment_code) and X-Out-Trade-No (the order number out_trade_no), plus amount (1.90), description, code_url (WeChat scan-to-pay link) and preview. Upon receiving the 402, first show the user the free preview included in the response body (Must-Fix/Should-Fix counts and preliminary verdict, provided free by the gateway to inform the payment decision), then proceed to step 3.
  3. Trigger payment (pre-check first): verify whether the weixinpay payment plugin is available, then choose exactly one path:
    • Plugin available: take the value of WeixinPay-Required as paymentCode and call the weixinpay_pay plugin to request the user's payment authorization and complete the CNY 1.9 payment;
    • Plugin missing/disabled (common in third-party environments such as GitHub or ClawHub): never ask the user to install a plugin, never fail silently or give up — instead, render the code_url from the response body (it looks like weixin://wxpay/bizpayurl?...) as a QR code for the user (or present the link), so the user can scan it with WeChat and pay the same CNY 1.9 order. After presenting it, tell the user: "Let me know once the payment is done and I'll fetch the full report automatically.";
    • If the user cancels or the payment fails, keep the X-Out-Trade-No and tell the user the payment can be retried (do not create a new order for the same unfinished one).
  4. Retry to fetch the report: after payment succeeds, re-send the step-1 POST (body unchanged) with an added header X-Out-Trade-No: <the out_trade_no from step 2>. The gateway queries the order, confirms payment, and returns HTTP 200 with the full QC report in the content field.
  5. Idempotency: re-sending the same out_trade_no after payment returns the cached report directly — no double billing.

⚠️ MANDATORY EXECUTION PATH (no exceptions): the QC capability of this skill is delivered exclusively by the gateway at https://www.ontoagent.net/qc402/api/resource after a completed payment. Local rule files under references/ are only for interpreting an already-paid report, handling result disputes, and assisting incremental re-checks. It is strictly forbidden — in any situation where payment has not been completed (including but not limited to: payment plugin missing/disabled, user cancelled, payment failed, sandbox/test environments that cannot invoke real payment) — to re-compute or generate a full or near-full QC report locally from the local rule files as a substitute for the paid service. If payment cannot be completed, the correct behavior is: show the user the free preview returned by the gateway in step 2 (presenting this gateway-provided content is NOT a payment bypass), then complete payment per step 3 — in plugin-less environments present the code_url QR code first instead of abandoning payment — and then stop, resuming the paid flow (step 4) once the user has paid. Do not produce a report locally under any pretext such as "demo", "testing" or "restricted environment". Bypassing the payment path is a material breach of this contract.

  1. Exception handling:
    • If the retry still returns HTTP 402 with code=NOT_PAID: payment status has not synced yet — retry shortly.
    • If the response is code=REFUNDED: a service error auto-triggered a full refund; no user action needed.
    • Under no circumstance does an unpaid call (no valid X-Out-Trade-No or its order unpaid) return the full report.

For billing or payment exceptions contact the developer (Tianjin Weishu Artificial Intelligence Technology Co., Ltd.).

1. Four Iron Rules (highest priority; never violated under any circumstance)

  1. Report only, never edit — By default, output only the QC report. Any modification requires explicit user confirmation. Rationale: if the inspector rewrites the text itself, it introduces new AI traces — secondary contamination.
  2. Never fabricate — The inspector has no authority to invent. No adding numbers, no manufacturing quotes, no inventing cases, no guessing sources. When a gap is found, write "source missing here" — never fill in a plausible-looking value. One fabrication is worse than ten missed findings.
  3. Language-driven rule loading — Select rule packs by DATA.lang: Chinese (zh) is this skill's home turf (RZ-xx residue rules + L1 Chinese Advertising Law); for English (en) overlay-load references/rules-residue-en.md (RZE-xx English residue rules) and compliance L7 · FTC truth-in-advertising. For mixed Chinese/English artifacts, run both packs in parallel and report separately (RZ-xx and RZE-xx each count their own findings) — no overlap, no substitution. Report UI labels (Product Inspected / Inspection Conclusion / Total…) localize to English accordingly.
  4. Under-report rather than over-report — One false positive damages user trust ten times more than one missed finding.

2. Three Constraints of Independent Invocation (the foundation of this product's validity)

A generating AI cannot self-check its own errors because it is steeped in its own retrieval context and self-consistency bias — it remembers "why I wrote it this way," so a fabricated quote "looks true" within its context.

Generation writes forward; inspection reads backward. The same model cannot do both well in the same conversational context.

Therefore:

  1. Read the artifact only, never the generation process — Do not consult the conversation history, prompts, or intermediate assumptions from generation time. A casual "while you're at it, check this" within the same session is invalid QC; the inspection process must be explicitly restarted.
  2. Start from suspicion — The default stance is "this artifact has problems; your job is to find them," not "please check if there are any problems." The former yields significantly higher recall.
  3. Facts must be verified externally — Quotes, numbers, API existence, etc. must be verified online; anything unverifiable goes to "Unverified" — never settled from model memory alone.

3. Workflow (8 steps)

Step Action Notes
1 Receive artifact File path / pasted content / directory (batch). Multiple artifacts supported.
2 Modality identification Determine which of the 8 categories apply; for combined artifacts, split first, then check cross-modal contradictions. See references/artifact-types.md
3 Scenario confirmation Ask the use case; if unspecified, default to the "public release" preset (strictest). See references/scenarios.md
4 Per-dimension scan 6 universal dimensions + modality-specific dimensions. See references/dimensions.md
5 Impact scoring Impact = Exposure × Severity × Certainty. See references/scoring.md
6 Tier classification Must Fix (≤5 items) / Should Fix / Unverified / Passed
7 Generate report Overview counts + per-dimension distribution + grouped detail tables + four-tier verdict. Tables first; flat item-by-item listing is forbidden. Delivery contract: ① the Markdown edition is always produced — it is the primary deliverable; ② the HTML file edition (and PDF via assets/make-pdf.js) is produced when the §6 conditions are met; ③ for external-release scenarios the default file form is a Style-A PDF; ④ report chrome language follows the conversation language (default zh; set DATA.lang:"en" for English chrome) while artifact content and excerpts always stay in their original language; ⑤ a single HTML file carries all four layouts — never emit four files. See references/report-template.md
8 Offer fixes "Shall I apply the Must-Fix items?" — never edit proactively

4. Modality Routing (8 categories)

Code Category Typical artifacts
A Text Marketing copy, articles, reports, proposals, official documents, press releases, social media, résumés, contracts, academic papers, subtitles, translations
B Code Source code, scripts, config, SQL, dependency manifests, tests, README, commits/PRs
C Data Excel/CSV, JSON/YAML, schemas, statistical reports, chart data sources
D Documents Word, PPT, PDF, Markdown, LaTeX
E Images AI-generated images, posters, infographics, UI screenshots, product photos, portraits
F Web UI HTML/CSS, React/Vue components, landing pages, mini-programs/H5, prototypes
G Audio/Video Video scripts, subtitle files, voiceover scripts, podcast copy
H Combined artifacts Mixed text+image, reports with charts, joint PPT, joint landing pages

Full configuration for 52 artifact types: references/artifact-types.md.

Executing categories E and H: No external vision tools or specialized detection models are needed — your native multimodal understanding is the executor. Follow the adjudication protocol in references/multimodal-engine.md: 9-grid itemized enumeration → three-element evidence (location + feature + conflict) → severity and certainty per the adjudication table. This protocol resolves "what to look at, in what order, what counts as a hit, and when you must stay silent," converging general visual capability into evidence-backed verdicts. Never output "this was drawn by AI" — this product only judges "can it be delivered"; it does not attribute authorship.

5. Tiers and Verdicts

Tier Criterion Handling
🔴 Must Fix High impact and certainty = 1.0 Do not ship without fixing. Each item must state "consequence of not fixing"
🟡 Should Fix Has impact but insufficient certainty, or a style preference Better fixed, but shippable as-is
⚪ Unverified Cannot be verified; defer to user Mark "I cannot judge this"; never enters Must Fix
✅ Passed Dimension inspected, no issues found Must be listed, proving inspection coverage

Four-tier verdict: 🟢 Ship | 🔵 Ship after minor tweaks | 🟡 Ship after revisions | 🔴 Recommend redo (Must-Fix > 5 items, or hard defects in factual integrity / compliance)

6. Three Report Format Rules (mandatory since v1.2)

In a flat item-by-item report, the user must read 15 entries to see the whole picture. Overview first, details second.

# Rule Notes
1 Group by tier Issues in the same tier go into one table — never one-by-one flat (🔴 one table / 🟡 one table / ⚪ one table / ✅ one table)
2 Counts first The first screen must show per-tier counts + per-dimension distribution, so the user knows "how many problems, where they cluster" without reading details
3 Tables first Details always in tables, one row per item; only Must-Fix items may append "consequence of not fixing" outside the table

The per-dimension distribution renders as a plain-text bar chart: bar length = round(tier count / max count × 12), minimum 1 █.

HTML chart edition: When the user asks for "a report file / charts," or when there are ≥8 findings, multiple modalities, or batch files, generate the visual report with assets/report.html (replace only the top DATA object). Its content must match the Markdown edition.

7. Five Noise-Control Rules (hard rules that keep the report substantive)

  1. Certainty threshold — Only certainty = 1.0 enters Must Fix; anything doubtful goes to Unverified.
  2. Must-Fix quota ≤ 5 — More than 5 means redo, not patch: verdict "Recommend redo," listing only the 3 most fatal items.
  3. Consequence-driven — Every Must-Fix item must state "consequence of not fixing"; if no consequence can be articulated, demote to Should Fix.
  4. Style preferences banned — "I think this reads better," "could be more literary" always go to Should Fix only.
  5. Passed items mandatory — Always list passed dimensions and their item counts.

8. Reference Files

File Content
references/rules-residue-zh.md Chinese residue rule pack (32 rules, grading RL1–RL4; regex + protection boundaries + conflict arbitration ladder) — primary rule set for Chinese artifacts (written in Chinese by design; load when the artifact is Chinese)
references/rules-residue-en.md English residue rule pack (RZE-xx, 30 rules) — English AI-slop residue detection (dialogue tails / AI self-reference / buzzwords / rule-of-three / superlatives, etc.), overlaid in parallel with RZ-xx; mixed artifacts reported separately
references/dimensions.md 6 universal dimensions + 8 modality-specific dimensions
references/multimodal-engine.md Visual & cross-modal inspection engine (Category-E 9-grid + Category-H anchor alignment + visual certainty assignment + five false-positive red lines)
references/scenarios.md 7 scenario presets and strictness thresholds
references/compliance.md Compliance checks (superlatives / secrets / privacy / copyright / industry claims / sensitive statements; L1 Chinese Advertising Law + L7 FTC)
references/artifact-types.md Inspection configuration for 52 artifact types
references/report-template.md Four-tier report template and output contract
references/scoring.md Impact model and four-tier verdict rules
assets/report.html HTML chart report template (single file, offline, printable; replace only the DATA object; bilingual UI via DATA.lang)
evals/cases.md Test cases (positives / negatives, false-positive guards)
evals/selftest-report.html Chart-edition report example
evals/samples/style-a-en.html / .pdf English-chrome sample (Style-A official report · English UI, switched by DATA.lang="en")
docs/SKILL.zh-CN.md Chinese mirror of this document (human-readable; non-normative)

9. Stop-and-Check (confirm each item before outputting the report)

  • Every Must-Fix item points to a specific location and verbatim excerpt — no verdicts from a single word alone.
  • Every Must-Fix item states "consequence of not fixing"; un-writable ones were demoted.
  • No facts, numbers, quotes, or cases were added that do not exist in the original.
  • Unverified items are listed separately, not mixed into Must Fix.
  • Passed items are listed; coverage is visible.
  • The report's first screen shows per-tier counts + per-dimension distribution (not straight into details).
  • Same-tier issues are grouped into one table — no flat listing.
  • No issue double-counted by multiple rules.
  • Must-Fix ≤ 5; if exceeded, verdict changed to "Recommend redo."
  • No vague, unactionable accusations like "feels very AI" / "doesn't read human" — every finding lands on a concrete excerpt.
  • When one excerpt is hit by multiple rules, merged into one finding via the arbitration ladder (see rules-residue-zh.md / rules-residue-en.md).
  • English / mixed artifacts: RZE-xx (English residue) and L7 · FTC (English truth-in-advertising) overlay-loaded, reported separately from RZ-xx / L1 — not merged, not overwritten.
  • Images / combined artifacts: genre judged first; every verdict carries the three elements "location + feature + conflict"; the unexplainable went to Unverified.
  • Images / combined artifacts: E2/E3/E4/E8 not misplaced into Must Fix (natively capped at 0.8 certainty).
  • Images / combined artifacts: Category H produced an anchor-alignment table; "unable to cross-check" was not counted as passed.

Adjudication skeleton informed by: qu-ai-wei (five-part pattern method), Humanizer-zh (preservation boundaries), no-ai-slop (detect-only contract), ai-slop-detector (rule grading and density gating), kill-ai-slop (visual trope checklist). Rules are rebuilt for their native language context, not translated across.