100x-search-query

100x-search-query

One-sentence positioning

Input a product/persona card, output 15 English search phrases each for the three platforms Pinterest / TikTok / Reddit, used to find visual reference material, inspiration images, and benchmark content. Belongs to the 100x system L2 creative generation layer, corresponding to the "search keywords" step.

When to trigger

The user says:

• "Help me find reference images" / "find inspiration images" / "where to find reference images" / "give me search keywords"
• "what should I search on Pinterest" / "find reference images"
• "need TikTok/Reddit search terms for this product"
• Or directly gives a product card / persona card and asks for a set of search terms

Input

Minimum input (Category A, hard required):category(category, free text, e.g. "health supplements" "home" "beauty personal care"; refer to future taxonomies/，Forbidden to apply any client-specific category dictionary）。product_name is not an input the user must provide——when a specific brand/product name is unavailable, use "[品类锚点] <category>" placeholder to keep running (schema.json requires that in the output product_name must be a non-empty string, that is "required by the output contract", not "required by user input", the two are not the same thing). See workflow.md Phase 1 Category A validation.

Soft supplement (Category B, if missing go through three-level degradation, see workflow.md Phase 1）：core_benefit、 target_audience、brand_tone、topic_angle（default/aesthetic/pain-driven/ sales-push one of).

Optional upstream outputs (Category C, if missing silently skip, does not block, and never requires the user to run other skills first): persona card, insight results, viral point results.If provided, must genuinely influence generation——at the 2C stage at least 6 entries must reflect the persona's specific audience/identity angle, cannot just accept the card but produce output the same as if it were not given, see workflow.md Phase 1 step 4 / corresponding paragraphs in Phase 2.

Output

For structure see schema.json：queries.pinterest/tiktok/reddit 15 entries each {q, intent_cn, stage}， meta.based_on_5a Declare this run's 5A coverage. When Category C (persona/insight) input is received, meta.persona_informed must be true and meta.persona_descriptor_terms must list the specific audience/identity terms extracted from the card, otherwise it does not count as compliant output (Axiom 5); when no Category C input is received both fields may be omitted. Optionally render 3 Markdown tables (one per platform, columns:# / query / search_intent_cn / 5a_stage）。

Core constraints (5 axioms, see axioms.md）

1. Exactly 15 entries per platform, all English ASCII, 1 short or mixed Chinese = invalid
2. Platform differentiation locked: Pinterest aesthetic words / TikTok hashtag+meme words / Reddit pain-point questions, cross-platform mixing = invalid
3. Generated based on 5A intent layering,meta.based_on_5a required non-empty, 45 entries cover ≥3 stages
4. Each entry must carry a ≤20-character Chinese search intent annotation, format must be "closed-set category label + pure Chinese explanation" (known limitation: this isformat validation, can block "copying the whole English translation verbatim", but cannot block the more hidden case of "attaching a legitimate label shell while the content is still word-for-word literal translation", for example giving literal translation content a "questioning:" prefix at random will pass——this is a known semantic gap, not a "guarantee of zero literal translation", see axioms.md Axiom 4 TODO)
5. When persona/insight input is received it must genuinely be reflected in the output: persona_informed=true when, at least 6 of the 45 entries must hit persona_descriptor_terms the specific audience/identity terms declared, otherwise invalid (known limitation: the word-list criterion cannot block "perfunctorily picking a few overly broad words to make up the numbers", it can only block "completely unused", see axioms.md Axiom 5)

Boundaries (no exceptions): Regardless of the source language of the product copy (multilingual input such as English and Spanish is supported), the output search termsare always in English—this is a direct corollary of Axiom 1, not an additional restriction.There is no non-English version as an option: The output phrases are strictly constrained by the ASCII strong validation of schema.json , with no non-English output branch.

Three-Phase Flow

See workflow.md: Phase 1 receive + validate (Category A/B/C) → Phase 2 (5A assignment → platform bucket generation → per-item self-check → batch self-check) → Phase 3 user-triggered rework (L1 single item / L2 single bucket / L3 all;there is no L4—Axiom 1 has no exception for non-English output, see "Boundaries" above).

Independent Invocation Guarantee

Category A missing (i.e., category missing—product_name not being able to get a specific brand name does not count as Category A failure, see the "Input" section above) → fixed refusal script to follow up, no guessing, no fabrication. Never require the user to "run other skills first." Category B missing goes through three-level degradation (complete → ask one question → inline inference +meta.warningshint). Category C missing is silently skipped.

Banned Words

let me / hope / perhaps / probably / maybe / possibly / let's; AI customer-service tone (as an AI / I'd be happy to / feel free to); ineffective aesthetic words attractive/beautiful/stunning/serene/pristine/elegant/ cinematic/professional/studio/flawless; do not fabricate subreddit (this skill by default does not add the r/xxx prefix, see axioms.md TODO); do not fabricate effects/certifications/user testimonials.

Sensitive Category Signal Detection (content policy guardrail, known to have limitations, not an axiom)

This skill scans category/product_name as well as all generated q/intent_cn, ifsimultaneously hit "sensitive category signals" (such as sexual health/intimate care terms and their synonyms/euphemisms) and "authority claim signals" (such as fabricated FDA/doctor/expert certification terms and their synonyms),it will not refuse to generate, but will forcibly append a fixed notice in the produced meta.warnings ; for the criteria see workflow.md Phase1 Step 6, for the signal word list see scripts/validate.js。

Known Limitations (stated truthfully, not "fully resolved"): This is a fixed keyword-list criterion, not a semantic criterion, and naturally has two ceilings: ① The word list only covers common synonyms/euphemisms; any newly coined word/alternative phrasing not included in the list can still bypass it; ② It can only scan fields that exist in the final output JSON (category/ product_name/all q/all intent_cn), and cannot see the full original input text that Phase1 read at the time and that did not permeate into these fields at all.Design Note: The scan scope for both signals is unified as full-text field scanning (category/product_name and the finally generated query and intent_cn text), and the word list also supplements common synonyms (this only narrows the gap, it does not close it). It cannot be claimed that "expanding the list will close it"—if a stronger guarantee is needed, semantic-layer detection is required, and this is the same class of problem as the "format lock vs semantic lock" ceiling in Axiom 4 TODO.

Routing (recommended, not a hard dependency)

• Has a product but lacks category/selling-point profile → persona/profile-type skill (if already built)
• Wants to convert searched material into generation prompts → prompt assembly-type skill (if already built)
• Want media fission instead of finding reference images → visual fission type skill (if already built)
• Want to return to the entry point for re-triage → 100x system main entry (if already built)

All of the above are "recommended on demand after output", not prerequisites; if the corresponding skill has not yet been built, it does not affect this skill's ability to work independently.

Factory self-check

Run node scripts/validate.js --selftest to verify. Axioms 2/3 are cross-item aggregation rules,schema.json (vanilla JSON Schema) cannot express them; what actually performs the determination is scripts/validate.js：

node scripts/validate.js <bundle.json> [bundle2.json ...]   # 校验产出
node scripts/validate.js --selftest                          # 跑内置回归用例

Source

This skill's methodology is based on the inspiration search methodology system, adopting a self-contained design (including axioms.md、workflow.md、sources.md、schema.json and validation scripts), does not depend on external private paths, and contains no private data. For the item-by-item evolution description, see sources.md。