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Copy file name to clipboardExpand all lines: i18n/en/src/e-social-media/e1-instagram-facebook-ai-guide.md
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@@ -892,6 +892,24 @@ For each tag, provide:
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Keep the total at 20-25 tags/post.
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Allocate by the "5-5-5-10" strategy: 5 large tags + 5 medium tags + 5 small tags + 10 long-tail tags.
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<data_discipline>
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- Any figure involving money, volume, ranking, or fee rates must come from what I supplied above. Anything I didn't give you is "missing" — **do not estimate, and do not draw on industry averages or platform fee rates from memory**. Those go stale, and I may spend real money on them
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- When you need a figure to continue, tell me where to look it up and which field to read, then stop and wait for me to supply it
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- Tag every conclusion with its source: [supplied by me] or [model inference]. For inferences, state what the inference rests on
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</data_discipline>
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<output_format>
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Output the tags in 5 categories (brand tags / product tags / community tags / trending tags / long-tail tags), one tag per line: tag name | estimated post volume | recommended use scenario.
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</output_format>
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<self_check>
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Check and report each item before delivery:
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① Total 20-25 tags, allocated by 5-5-5-10 (5 large + 5 medium + 5 small + 10 long-tail)
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② Every tag provides all three fields: name / estimated post volume / use scenario
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③ Tags are relevant to the category and target market, not invented
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④ Post-volume estimates are tagged [supplied by me] or [model inference]
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</self_check>
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```
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### 9.3 Competitor Instagram Analysis
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- When you need a fact to make a judgment, tell me which official source to verify it against, then stop and ask me
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- Tag every conclusion with its source: [supplied by me] or [model inference]
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</data_discipline>
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<output_format>
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Output one section per competitor (each: content strategy | interaction strategy | Shopping strategy | ad strategy | growth strategy), then 3 strategies worth borrowing, 3 opportunity points, and the differentiation direction.
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</output_format>
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<self_check>
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Check and report each item before delivery:
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① All 3 competitors covered with all 5 analyses, none missing
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② Exactly 3 strategies worth borrowing and exactly 3 opportunity points
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③ Competitor data (follower counts, posting frequency, etc.) comes from what I supplied; anything missing is written as "missing"
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④ Every conclusion is tagged [supplied by me] or [model inference]
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</self_check>
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```
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---
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- When you need a fact to make a judgment, tell me which official source to verify it against, then stop and ask me
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- Tag every conclusion with its source: [supplied by me] or [model inference]
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</data_discipline>
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<output_format>
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Output the 7 items in order: algorithm-performance assessment → bottleneck metric → save-rate improvement strategy → share-rate improvement strategy → best posting time → frequency recommendation → 5 topic suggestions.
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</output_format>
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<self_check>
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Check and report each item before delivery:
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① Metric figures (reach / engagement rate / save rate / share rate) come from my supplied data; anything missing is written as "missing"
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② Industry benchmarks are labeled as reference lines, not measured values
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③ Save-rate / share-rate improvement strategies are concrete and actionable
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④ The 5 topic suggestions align with algorithm preferences (completion / save / share rate)
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</self_check>
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```
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---
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- For anything sent to a customer (replies, emails, templates), don't make commitments I haven't authorized: refund amounts, compensation, timelines, or exceptions to platform policy must be confirmed by me before they go in
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- Flag any claim touching efficacy, safety, environmental, or patent language separately for manual review
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