TikTok Video Fake View Estimate (by Video ID)

omnial/tiktok-video-fake-view-estimate

Given a TikTok video id, returns a heuristic fake-view estimate computed from the video's and creator's public metrics, not a TikTok figure: view, like, comment, save and share totals with engagement ratios; creator account age, followers and verified flag; a fake score with a confidence label, estimated fake views and share, eight dimension scores and notes; a traffic pool tier estimate; suspicious features; and a recommended action with a risk level.

activeper callv1

Price

Up to $0.0205 per call; you pay what the call used

The price shown is the price you pay. No monthly minimum. Top-ups start at $5.

Data source

TikTok

Data from TikTok.

Use it

Five steps: search, inspect, learn, run, settle. No per-tool setup; your agent reaches this tool through the meta-tools it already has.

agent

// 1. search: find the tool
omnial_search({ query: "what you need" })

// 2. inspect: price and input schema
omnial_inspect({ tool: "omnial/tiktok-video-fake-view-estimate" })

// 3. learn: read the usage guide at runtime
omnial_learn({ tool: "omnial/tiktok-video-fake-view-estimate" })

// 4. run: price the exact call first, then run it
omnial_execute({ tool: "omnial/tiktok-video-fake-view-estimate", input: { /* see input_schema */ }, dry_run: true })
omnial_execute({ tool: "omnial/tiktok-video-fake-view-estimate", input: { /* ... */ } })

// 5. settle: the call is charged when it finishes, nothing to do

Not connected yet? Point your MCP client at https://mcp.eden-engine.com/mcp, then copy a config for your client.

Pricing

Every charge this tool can incur.

Charge	Price
Per call	$0.0205

Updated: Oct 17, 2026

Input and output schemas

Input schema

input_schema.json

{
  "type": "object",
  "required": [
    "item_id"
  ],
  "properties": {
    "item_id": {
      "type": "string",
      "pattern": "^[0-9]+$",
      "description": "The TikTok video id, the number at the end of the video's link."
    },
    "content_category": {
      "enum": [
        "default",
        "verified_large"
      ],
      "type": "string",
      "default": "default",
      "description": "The engagement benchmark to compare against: default, or verified_large for large verified accounts. For the large verified account in the captured calls, both values returned the verified_large benchmark and the same scores."
    }
  },
  "additionalProperties": false
}

Output schema

output_schema.json

{
  "type": "object",
  "properties": {
    "video_id": {
      "type": "string",
      "description": "The analysed video's id."
    },
    "timestamp": {
      "type": "string",
      "description": "When the analysis ran (ISO 8601, no time zone)."
    },
    "data_sources": {
      "type": "object",
      "properties": {
        "video_info_available": {
          "type": "boolean"
        },
        "creator_data_available": {
          "type": "boolean"
        },
        "video_metrics_available": {
          "type": "boolean"
        }
      },
      "description": "Which inputs the analysis had."
    },
    "traffic_pool": {
      "type": "object",
      "properties": {
        "current_tier": {
          "type": "number",
          "description": "The tier reached, 1 to 8; higher means more traffic."
        },
        "expected_tier": {
          "type": "number",
          "description": "The tier organic traffic alone would predict."
        },
        "current_tier_name": {
          "type": "string"
        },
        "expected_tier_name": {
          "type": "string"
        },
        "current_views_range": {
          "type": "string",
          "description": "The view range of the current tier, such as 30M+."
        },
        "expected_views_range": {
          "type": "string"
        },
        "estimated_organic_views": {
          "type": "number",
          "description": "Total views minus the estimated fake views."
        }
      },
      "description": "Which traffic pool tier the video reached and which one organic traffic alone would predict."
    },
    "video_metrics": {
      "type": "object",
      "properties": {
        "total_likes": {
          "type": "number"
        },
        "total_views": {
          "type": "number"
        },
        "total_shares": {
          "type": "number"
        },
        "total_comments": {
          "type": "number"
        },
        "total_favorites": {
          "type": "number",
          "description": "Saves."
        },
        "engagement_rates": {
          "type": "object",
          "properties": {
            "like_ratio": {
              "type": "number",
              "description": "Likes per view."
            },
            "share_ratio": {
              "type": "number",
              "description": "Shares per view."
            },
            "comment_ratio": {
              "type": "number",
              "description": "Comments per view."
            },
            "favorite_ratio": {
              "type": "number",
              "description": "Saves per view."
            }
          }
        }
      },
      "description": "The video's public totals and engagement ratios."
    },
    "content_metrics": {
      "type": "object",
      "properties": {
        "content_type": {
          "type": "string",
          "description": "Such as video."
        },
        "created_by_ai": {
          "type": "boolean",
          "description": "Whether the video is marked as AI-generated."
        },
        "creation_time": {
          "type": "number",
          "description": "When the video was posted, Unix seconds."
        },
        "high_quality_upload": {
          "type": "boolean"
        }
      },
      "description": "Facts about the video itself."
    },
    "creator_metrics": {
      "type": "object",
      "properties": {
        "verified": {
          "type": "boolean"
        },
        "follower_count": {
          "type": "number"
        },
        "account_age_days": {
          "type": "number",
          "description": "Days since the creator's account was created."
        },
        "follower_view_ratio": {
          "type": "number",
          "description": "Views divided by the views the follower count would lead the analysis to expect."
        },
        "expected_views_from_followers": {
          "type": "number",
          "description": "The view count the analysis expects from the follower count."
        }
      },
      "description": "The creator account's public metrics as the analysis used them."
    },
    "recommendations": {
      "type": "object",
      "properties": {
        "action": {
          "type": "string",
          "description": "Such as no_action, monitor, scheduled_review or immediate_review."
        },
        "risk_level": {
          "type": "string",
          "description": "The video's fake-traffic risk level, such as low."
        },
        "suggested_steps": {
          "type": "array",
          "items": {
            "type": "string"
          }
        }
      },
      "description": "A suggested follow-up for the video."
    },
    "detailed_analysis": {
      "type": "object",
      "properties": {
        "engagement": {
          "type": "object",
          "properties": {
            "benchmark_category": {
              "type": "string",
              "description": "The engagement benchmark the analysis applied."
            },
            "engagement_health_score": {
              "type": "number",
              "description": "0 to 100; higher is healthier."
            },
            "engagement_suspicion_score": {
              "type": "number"
            }
          }
        },
        "fan_growth": {
          "type": "object",
          "properties": {
            "issues": {
              "type": "array",
              "items": {
                "type": "string"
              }
            },
            "growth_rates": {
              "type": "array",
              "items": {
                "type": "number"
              }
            },
            "fan_growth_score": {
              "type": "number"
            },
            "suspicious_indicators": {
              "type": "array",
              "items": {
                "type": "string"
              }
            },
            "suspicious_milestones": {
              "type": "number"
            }
          }
        },
        "consistency": {
          "type": "object",
          "properties": {
            "issues": {
              "type": "array",
              "items": {
                "type": "string"
              }
            },
            "consistency_score": {
              "type": "number"
            }
          }
        },
        "distribution": {
          "type": "object",
          "properties": {
            "issues": {
              "type": "array",
              "items": {
                "type": "string"
              }
            },
            "pattern_type": {
              "type": "string"
            },
            "distribution_score": {
              "type": "number"
            }
          }
        },
        "racing_mechanism": {
          "type": "object",
          "properties": {
            "issues": {
              "type": "array",
              "items": {
                "type": "string"
              }
            },
            "racing_score": {
              "type": "number"
            }
          }
        },
        "creator_credibility": {
          "type": "object",
          "properties": {
            "issues": {
              "type": "array",
              "items": {
                "type": "string"
              }
            },
            "credibility_score": {
              "type": "number"
            }
          }
        },
        "content_authenticity": {
          "type": "object",
          "properties": {
            "authenticity_score": {
              "type": "number"
            }
          }
        },
        "follower_correlation": {
          "type": "object",
          "properties": {
            "follower_tier": {
              "type": "string",
              "description": "The account-size bucket the analysis placed the creator in."
            },
            "tier_benchmarks": {
              "type": "object",
              "properties": {
                "view_ratio": {
                  "type": "object",
                  "properties": {
                    "avg": {
                      "type": "number"
                    },
                    "min": {
                      "type": "number"
                    },
                    "good": {
                      "type": "number"
                    }
                  }
                },
                "like_follower_ratio": {
                  "type": "object",
                  "properties": {
                    "avg": {
                      "type": "number"
                    },
                    "min": {
                      "type": "number"
                    },
                    "good": {
                      "type": "number"
                    }
                  }
                }
              }
            },
            "correlation_score": {
              "type": "number"
            }
          }
        },
        "statistical_anomalies": {
          "type": "object",
          "properties": {
            "method": {
              "type": "string",
              "description": "The method used, or insufficient_data when there was too little data to test."
            },
            "anomalies_detected": {
              "type": "boolean"
            }
          }
        }
      },
      "description": "Per-dimension detail behind the component scores."
    },
    "view_pattern_type": {
      "type": "string",
      "description": "The view pattern the analysis found, or insufficient_data."
    },
    "fake_view_analysis": {
      "type": "object",
      "properties": {
        "fake_score": {
          "type": "number",
          "description": "The overall fake-view score, 0 to 100; lower is better."
        },
        "is_suspicious": {
          "type": "boolean",
          "description": "The analysis's overall suspicious flag. It can be false while suspicious_features still lists anomalies, as in the captured calls."
        },
        "component_scores": {
          "type": "object",
          "properties": {
            "engagement_score": {
              "type": "number"
            },
            "fan_growth_score": {
              "type": "number"
            },
            "consistency_score": {
              "type": "number"
            },
            "distribution_score": {
              "type": "number"
            },
            "racing_mechanism_score": {
              "type": "number"
            },
            "creator_credibility_score": {
              "type": "number"
            },
            "content_authenticity_score": {
              "type": "number"
            },
            "follower_correlation_score": {
              "type": "number"
            }
          },
          "description": "Per-dimension anomaly scores, 0 to 100; lower is better."
        },
        "confidence_level": {
          "type": "string",
          "description": "A risk label for the score, such as Minimal."
        },
        "estimated_fake_views": {
          "type": "number"
        },
        "fake_view_percentage": {
          "type": "number",
          "description": "Estimated fake views as a percentage of total views."
        },
        "main_detection_reason": {
          "type": "string"
        }
      },
      "description": "The overall estimate. Scores run 0 to 100; lower is better."
    },
    "suspicious_features": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Anomalies the analysis listed as suspicious, as sentences."
    }
  },
  "description": "A heuristic fake-view assessment of one TikTok video."
}