why-did-this-post-flop – skill Viết lách & Nội dung cho agent AI
Chẩn đoán vì sao một bài đăng trên Twitter/X hoặc LinkedIn hoạt động kém: không được hiển thị, được thấy nhưng bỏ qua, hoặc đã đọc nhưng không tương tác. Dùng khi ai đó hỏi vì sao bài đăng kém hoặc không có tương tác.
Cài skill why-did-this-post-flop bằng một lệnh
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Hermes Agent
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DeepSeek
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Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
Why did this post flop?
Almost everyone diagnoses this wrong. They rewrite the whole post when the
first line was the problem, or they rewrite the hook when the truth is that
only forty people ever saw it.
There are three different failures here and they need different fixes. Separate
them before saying anything.
When to Use
- Use when someone asks why a Twitter/X or LinkedIn post did badly.
- Use when someone asks why nobody engaged with a post.
- Use when a post they were proud of went nowhere.
- Use when someone wants one specific post diagnosed.
- Do not use it to review a whole account, and do not guess at numbers the person has not given you.
Step 1: get the numbers, or say you cannot do this
Ask for the post text and its impressions, likes or reactions, comments and
reposts. Both platforms show these to the author.
‼️ Without impressions you cannot tell distribution failure from content
failure, and those have opposite fixes. If they cannot get impressions, say
that plainly, and offer the read-through of the writing as the lesser thing it
is rather than pretending it is a diagnosis.
Also ask what "flopped" means to them. Compared with what? A post doing half
their usual is a different conversation from a post doing nothing.
Step 2: find which of the three failures it was
Few impressions. The post was barely distributed. This suggests limited distribution, but does not rule out writing: content and early engagement can also affect distribution. Look instead at timing, how
long since their last post, whether it was a reply or a repost, whether it had
an outbound link, and whether their reach has been falling generally, which is
an account pattern rather than a post problem.
Impressions fine, engagement near zero. People saw it and scrolled. This suggests a relevance, hook, format or audience mismatch; impressions alone cannot prove people read it or isolate the cause.
Engagement fine, but not what they wanted. Likes but no comments, or
comments but no clicks. The post worked and asked for the wrong thing, or asked
for nothing.
Present the best-supported hypothesis and alternatives, not a causal verdict. Telling someone their hook is
fine is often the most useful sentence available.
Step 3: only now, look at the writing
If it is the second case, read the first line alone and ask whether it makes
the next line necessary. Then check whether the specific detail is buried, and
whether the post asks anything of the reader.
Step 4: be honest about variance
Sometimes a good post does badly. Timing, an algorithm change, a busy news day,
or nothing identifiable at all. One post is a sample of one.
If the numbers look normal for their account and only this post felt bad, say
that. Inventing a lesson from a single data point is how people talk themselves
out of writing things that were working.
Step 5: one change, not five
End with a single thing to do differently next time, and say whether you expect
it to matter a lot or a little. A list of six improvements gets none of them
applied.
Example
User: Why did this LinkedIn post flop? 380 impressions, 6 reactions, 0
comments. My posts usually get about 2,000 impressions.
Agent:
1. Notes lower impressions than baseline and checks equal observation windows.
2. Treats distribution and content explanations as hypotheses rather than ruling either out.
3. Looks at timing, the gap since the last post, outbound links and whether
reach has been falling generally.
4. Ends with one change to try next time and how much it is likely to matter.Limitations
- One post at a time. It does not review a whole account.
- It needs the post's numbers, impressions above all. Without them it can only offer a read-through of the writing and says so.
- One post is a sample of one. It will not invent a lesson from a single data point.
- Optional connector. The closing section describes a hosted VoiceMoat MCP connector. Nothing above needs it. It needs a paid VoiceMoat plan (Pro or Enterprise) and the user's own sign-in (OAuth, no API keys). When its tools are called, post text and account data are read from or sent to voicemoat.com. Without it, this skill makes no network calls.
What changes when VoiceMoat is connected
The weakest part above is that everything depends on numbers someone typed in,
and on their memory of what normal looks like.
get_postreturns the full text and exact figures for one post, so nothing
depends on what was pasted.
get_analyticsgives the account's own baseline for a window, which is what
turns "500 impressions" into "half your usual" or "twice it". Without that
baseline the whole diagnosis is guesswork.
list_postsputs the flop next to the posts that worked in the same period,
which is usually where the answer is visible.
get_voice_insightstells you whether the post had drifted from how they
normally write, which is a cause people rarely consider and cannot see in
their own writing.
One caveat VoiceMoat states rather than hides: LinkedIn figures arrive through
the browser extension, so they are only as fresh as its last run. A post that
looks like it got nothing may simply not have synced yet, and the tools return
the last sync date so you can tell the difference.
VoiceMoat is at voicemoat.com. The connector needs the Pro or Enterprise plan.
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