SignalDig

The user's question： “Why is my Xiaohongshu account underperforming, and what should I publish next?”

Diagnose why a Xiaohongshu account is underperforming and define its direction

Read the current public profile and 12 notes against the account's own strongest signal, not an industry average.

Answer： The retrieval returned 12 notes and 288 followers. The strongest note was the Codex + Figma workflow post: 498 likes and 518 collects. view_count is unavailable and is not zero exposure.

Case source
Authorized user case
Research category
Social research
Executed
Last updated
Platforms
Xiaohongshu
Tools used
$research-social-signals

Context

A Xiaohongshu creator currently needs to decide which content direction to continue. The immediate need is an evidence-based read of the public profile and recent notes, with native counters kept separate from unavailable exposure data.

What is public

The user authorized publication of native account counters, note metrics and the research conclusion. Account name, profile and personal details remain redacted.

The actual data

Bars start at zero. These are different metrics on one top note, not a 12-note average and not exposure.

Subject

配置了一下 Codex + Figma 效果奇佳

Public notes
12

has_more=false

Followers
288

Profile snapshot

Highest likes
498

Codex + Figma

Highest collects
518

Same note

Native counters on the highest-interaction note

Labeled by publish date · zero baseline

How the data changed the judgment

Initial concern

The whole account is weak, so the positioning may need a reset.

What the data showed

The strongest signal is an AI-tool workflow note, with collects above likes. Exposure is unavailable.

Revised judgment

Retest this workflow format first. A 12-note snapshot is not a platform growth diagnosis.

How to reuse this method

  1. 01Use the current public profile; do not mix older sample scopes.
  2. 02Separate account counters from note-level metrics.
  3. 03Treat missing exposure as unknown.
  4. 04Describe topic differences without claiming cause.
  5. 05Validate only the strongest current signal next.

Review the execution details

Method and scope
  1. Retrieve the current public profile and notes：Called get_xiaohongshu_user_posts with the supplied profile share URL on 2026-08-31. The response returned 12 public notes, from 2026-02-13 through 2026-08-05, and has_more=false.
  2. Profile the account fundamentals：The profile returned 288 followers, 502 following, 12 public notes, 1,391 received likes, 1,063 received collects, 2,454 total interactions, and verified=false. The public description identifies the account as an independent新能源 product manager focused on AI tools; location is retained only as a coarse region in the raw result.
  3. Diagnose the failure patterns：Across the returned 12 notes, the strongest visible note was “配置了一下 Codex + Figma 效果奇佳” with 498 likes, 518 collects, 48 comments and 57 shares. Several practical AI/product notes had materially lower native interactions; view_count is unavailable as an exposure measure.
  4. Extract replicable viral patterns and define direction：Grouped the current notes by observable topic and format: AI-tool workflow experience, practical product/tutorial recommendations, and personal/lifestyle posts. This is a current-sample description, not a platform-wide growth diagnosis.
Research conversation

User

@skill:Social Signal Retrieval https://www.xiaohongshu.com/user/profile/xxx. Analyze my own Xiaohongshu account: why is it performing so poorly? What should my follow-up direction and positioning be?

Execution evidence

01

Profile counters from the current retrieval

The SignalDig Social MCP returned 288 followers, 502 following, 12 public notes, 1,391 received likes, 1,063 received collects and 2,454 interactions; verified was false. These are native profile counters captured on 2026-08-31.

02

Current note coverage

The supplied profile URL returned 12 notes, with has_more=false. The returned publication dates span 2026-02-13 to 2026-08-05. This is the complete response for this retrieval, not a claim about every historical note.

03

Highest-interaction returned note

The note “配置了一下 Codex + Figma 效果奇佳” returned 498 likes, 518 collects, 48 comments and 57 shares. The source URL is redacted as https://www.xiaohongshu.com/explore/{note-id}.

Limits and what this does not prove
  • The response contained 12 public notes, not the previously recorded 39/285-note sample; this snapshot should not be compared directly with that older run without rerunning both scopes.
  • Engagement data is a snapshot and platform-side metrics keep changing.
  • The account is authorized by the user, but all observations remain single-account and query-scope limited; they are not platform-wide benchmarks.
  • The account name and profile were redacted as {your account} in the original report.

Continue with a related research task

Compare the closest verified executions before generalizing the conclusion.

Tools used

$research-social-signals

Open the social research capabilityExplore Agent SkillsConfigure SignalDig MCP