Agent-Skills.md

Agent Skills: X Algorithm Engagement Signals

Reference for X algorithm engagement types and signals. Use when analyzing engagement metrics, action predictions, or understanding what signals the algorithm tracks.

UncategorizedID: cloudai-x/x-algo-skills/x-algo-engagement

Repository

cloudai-x/x-algo-skills
CloudAI-X
102

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pnpm dlx add-skill https://github.com/CloudAI-X/x-algo-skills/tree/HEAD/x-algo-engagement

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x-algo-engagement/SKILL.md

Skill Metadata

Name
x-algo-engagement
Description
Reference for X algorithm engagement types and signals. Use when analyzing engagement metrics, action predictions, or understanding what signals the algorithm tracks.

X Algorithm Engagement Signals

The X recommendation algorithm tracks 18 engagement action types plus 1 continuous metric. These are predicted by the Phoenix ML model and used to calculate weighted scores.

PhoenixScores Struct

Defined in home-mixer/candidate_pipeline/candidate.rs:

pub struct PhoenixScores {
    // Positive engagement signals
    pub favorite_score: Option<f64>,
    pub reply_score: Option<f64>,
    pub retweet_score: Option<f64>,
    pub quote_score: Option<f64>,
    pub share_score: Option<f64>,
    pub share_via_dm_score: Option<f64>,
    pub share_via_copy_link_score: Option<f64>,
    pub follow_author_score: Option<f64>,

    // Engagement metrics
    pub photo_expand_score: Option<f64>,
    pub click_score: Option<f64>,
    pub profile_click_score: Option<f64>,
    pub vqv_score: Option<f64>,              // Video Quality View
    pub dwell_score: Option<f64>,
    pub quoted_click_score: Option<f64>,

    // Negative signals
    pub not_interested_score: Option<f64>,
    pub block_author_score: Option<f64>,
    pub mute_author_score: Option<f64>,
    pub report_score: Option<f64>,

    // Continuous actions
    pub dwell_time: Option<f64>,
}

Action Types by Category

Positive Engagement (High Value)

| Action | Proto Name | Description | | ----------------- | ------------------------- | ----------------------------------- | | Favorite | ServerTweetFav | User likes the post | | Reply | ServerTweetReply | User replies to the post | | Retweet | ServerTweetRetweet | User reposts without comment | | Quote | ServerTweetQuote | User reposts with their own comment | | Follow Author | ClientTweetFollowAuthor | User follows the post's author |

Sharing Actions

| Action | Proto Name | Description | | ----------------------- | -------------------------------------- | ------------------------------------ | | Share | ClientTweetShare | Generic share action | | Share via DM | ClientTweetClickSendViaDirectMessage | User shares via direct message | | Share via Copy Link | ClientTweetShareViaCopyLink | User copies link to share externally |

Engagement Metrics

| Action | Proto Name | Description | | ----------------- | ----------------------------- | --------------------------------------------------------------- | | Photo Expand | ClientTweetPhotoExpand | User expands photo to view | | Click | ClientTweetClick | User clicks on the post | | Profile Click | ClientTweetClickProfile | User clicks author's profile | | VQV | ClientTweetVideoQualityView | Video Quality View - user watches video for meaningful duration | | Dwell | ClientTweetRecapDwelled | User dwells (pauses) on the post | | Quoted Click | ClientQuotedTweetClick | User clicks on a quoted post |

Negative Signals

| Action | Proto Name | Description | | ------------------ | ---------------------------- | ---------------------------- | | Not Interested | ClientTweetNotInterestedIn | User marks as not interested | | Block Author | ClientTweetBlockAuthor | User blocks the author | | Mute Author | ClientTweetMuteAuthor | User mutes the author | | Report | ClientTweetReport | User reports the post |

Continuous Actions

| Action | Proto Name | Description | | -------------- | ----------- | -------------------------------------------- | | Dwell Time | DwellTime | Continuous value: seconds spent viewing post |

How Scores Are Obtained

The PhoenixScorer (home-mixer/scorers/phoenix_scorer.rs) calls the Phoenix prediction service:

  1. Input: User history + candidate posts
  2. Output: Log probabilities for each action type per candidate
  3. Conversion: probability = exp(log_prob)
fn extract_phoenix_scores(&self, p: &ActionPredictions) -> PhoenixScores {
    PhoenixScores {
        favorite_score: p.get(ActionName::ServerTweetFav),
        reply_score: p.get(ActionName::ServerTweetReply),
        retweet_score: p.get(ActionName::ServerTweetRetweet),
        // ... maps each action to its probability
    }
}

Signal Interpretation

  • Scores are probabilities (0.0 to 1.0): P(user takes action | user sees post)
  • Higher = more likely: A favorite_score of 0.15 means 15% predicted chance of like
  • Negative signals have negative weights: High report_score reduces overall ranking
  • VQV requires minimum video duration: Only applies to videos > MIN_VIDEO_DURATION_MS

Related Skills

  • /x-algo-scoring - How these signals are combined into a weighted score
  • /x-algo-ml - How Phoenix model predicts these probabilities