HubVibe: Pay-per-Call Agent Tools: Web Search, Email Verify, KYC Screening, Stocks, Crypto, News

Predictive probability engine: regression, normal model, p-values

hubvibe_predictive_probability_engine

Read-onlyIdempotent

Predictive probability and regression engine: least-squares linear regression with standard errors, confidence and prediction intervals, a fitted normal distribution with quantiles and probability queries (P(y > t)), exact Student t and Jarque-Bera p-values. Points inline or from a BigQuery table. Deterministic arithmetic, no LLM: the same input always returns the same numbers. Input: points or table with x_column, y_column; optional metrics, predict_x, probability_queries. $0.50 per call. Returns: source{}, n, alpha, confidence_level, metrics[], linear_regression{}, normal_distribution{}, p_values{}, prediction[], notes[], method.

Input Schema

Name	Required	Description
`alpha`	No	Significance level for p-value validation and intervals. Default 0.05.
`table`	No	BigQuery table to read instead of `points`: project.dataset.table, readable by the node's service account (public datasets are). Needs x_column and y_column.
`points`	No	The data: [x, y] pairs (or {x, y} objects), 2 to 100000 of them; at least 3 for a regression. Use this OR `table`.
`metrics`	No	Which results to compute. Default: linear_regression, normal_distribution and p_values, plus prediction when predict_x is given.
`language`	No	Optional BCP-47 language tag (en, ja, ko, pt-BR): the human-readable strings of the result (notes, details, reasons) are translated into this language; data, codes, numbers and URLs are untouched. Default: as produced.
`max_rows`	No	Rows to read from `table`, default 10000. A larger table is reduced to this many rows by FARM_FINGERPRINT order, so the same table always yields the same rows.
`x_column`	No	Numeric column for x, with `table`.
`y_column`	No	Numeric column for y, with `table`.
`predict_x`	No	x values to predict y at, with mean and prediction intervals.
`distribution_of`	No	Which values the normal model fits. Default y.
`probability_queries`	No	Probabilities to read off the fitted normal model: {"below": v}, {"above": v} or {"between": [a, b]}.

Output Schema

Name	Required	Description	Default
`result`	Yes
`status`	Yes
`worker`	Yes
`price_usd`	Yes
`provenance`	Yes
`receipt_id`	Yes
`attribution`	No
`receipt_url`	Yes
`billing_warning`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 1, 2026

addedInput schema / minProperties
```
Added value: +1
```

removedInput schema / oneOf

Removed value: -[
-  {
-    "required": [
-      "points"
-    ]
-  },
-  {
-    "required": [
-      "table",
-      "x_column",
-      "y_column"
-    ]
-  }
-]

Changed23 schema fields changedOct 1, 2026

removedOutput schema / description

Removed value: -"The 200 body of every paid /work call. `result` is the worker's own output (its schema is per route); everything else is the same on every /work route. A receipt for the job is at `receipt_url`."

removedOutput schema / properties / attribution / description

Removed value: -"Present only when the result's text was machine-translated: the credit to show with it."

removedOutput schema / properties / attribution / items / description
```
Removed value: -"A credit."
```

removedOutput schema / properties / attribution / items / properties

Removed value: -{
-  "text": {
-    "description": "Credit.",
-    "examples": [
-      "Translated by Google"
-    ],
-    "type": "string"
-  },
-  "url": {
-    "description": "Link.",
-    "examples": [
-      "https://translate.google.com"
-    ],
-    "type": "string"
-  }
-}

removedOutput schema / properties / attribution / items / required
```
Removed value: -[
-  "text",
-  "url"
-]
```
removedOutput schema / properties / attribution / items / type
```
Removed value: -"object"
```

removedOutput schema / properties / billing_warning / description

Removed value: -"Present only when the charge was recorded with a caveat."

removedOutput schema / properties / billing_warning / examples
```
Removed value: -[
-  "settlement pending"
-]
```
removedOutput schema / properties / price_usd / description
```
Removed value: -"What this call cost, in USD."
```
removedOutput schema / properties / price_usd / examples
```
Removed value: -[
-  0.02
-]
```

removedOutput schema / properties / provenance / description

Removed value: -"How the result was produced: which providers ran and how long each took."

removedOutput schema / properties / provenance / properties

Removed value: -{
-  "attempts": {
-    "description": "Provider attempts made, including retries and failovers.",
-    "examples": [
-      1
-    ],
-    "type": "integer"
-  },
-  "elapsed_ms": {
-    "description": "Wall-clock milliseconds for the whole job.",
-    "examples": [
-      340
-    ],
-    "type": "integer"
-  },
-  "providers_used": {
-    "description": "Providers that served the job.",
-    "examples": [
-      [
-        "coinbase-advanced-trade-public"
-      ]
-    ],
-    "items": {
-      "description": "Provider name.",
-      "examples": [
-        "coinbase-advanced-trade-public"
-      ],
-      "type": "string"
-    },
-    "type": "array"
-  },
-  "steps": {
-    "description": "Every step the job ran, in order.",
-    "items": {
-      "description": "One step of the job.",
-      "properties": {
-        "ms": {
-          "description": "Milliseconds the step took.",
-          "examples": [
-            312
-          ],
-          "type": "integer"
-        },
-        "ok": {
-          "description": "Whether the step succeeded.",
-          "examples": [
-            true
-          ],
-          "type": "boolean"
-        },
-        "provider": {
-          "description": "Provider that served the step.",
-          "examples": [
-            "coinbase-advanced-trade-public"
-          ],
-          "type": "string"
-        },
-        "reason": {
-          "description": "Failure reason, on a failed step.",
-          "examples": [
-            "provider_timeout"
-          ],
-          "type": "string"
-        },
-        "step": {
-          "description": "Step name inside the worker.",
-          "examples": [
-            "quote"
-          ],
-          "type": "string"
-        }
-      },
-      "required": [
-        "step",
-        "ok",
-        "ms"
-      ],
-      "type": "object"
-    },
-    "type": "array"
-  }
-}

removedOutput schema / properties / provenance / required

Removed value: -[
-  "steps",
-  "providers_used",
-  "attempts",
-  "elapsed_ms"
-]

removedOutput schema / properties / receipt_id / description
```
Removed value: -"Receipt id for this job."
```
removedOutput schema / properties / receipt_id / examples
```
Removed value: -[
-  "rcpt_9f1c2b3a4d5e6f70"
-]
```

removedOutput schema / properties / receipt_url / description

Removed value: -"Where to fetch the machine-readable receipt (free, no payment)."

removedOutput schema / properties / receipt_url / examples

Removed value: -[
-  "/work/receipts/rcpt_9f1c2b3a4d5e6f70"
-]

removedOutput schema / properties / result / properties

Removed value: -{
-  "alpha": {
-    "description": "Significance level used.",
-    "examples": [
-      0.05
-    ],
-    "type": "number"
-  },
-  "confidence_level": {
-    "description": "1 - alpha: the level of every interval.",
-    "examples": [
-      0.95
-    ],
-    "type": "number"
-  },
-  "linear_regression": {
-    "description": "Ordinary least squares fit of y on x; null when not requested.",
-    "properties": {
-      "adjusted_r_squared": {
-        "description": "R^2 adjusted for degrees of freedom.",
-        "examples": [
-          0.995
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "degrees_of_freedom": {
-        "description": "n - 2.",
-        "examples": [
-          3
-        ],
-        "type": "integer"
-      },
-      "f_statistic": {
-        "description": "F statistic of the regression (t^2); null when undefined.",
-        "examples": [
-          773
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "intercept": {
-        "description": "OLS intercept.",
-        "examples": [
-          0.08
-        ],
-        "type": "number"
-      },
-      "intercept_ci": {
-        "description": "Lower and upper bound at the confidence level.",
-        "examples": [
-          [
-            1.43,
-            2.53
-          ]
-        ],
-        "items": {
-          "description": "Bound.",
-          "examples": [
-            0
-          ],
-          "type": "number"
-        },
-        "type": "array"
-      },
-      "intercept_std_error": {
-        "description": "Standard error of the intercept.",
-        "examples": [
-          0.236
-        ],
-        "type": "number"
-      },
-      "intercept_t": {
-        "description": "t statistic of the intercept; null when undefined.",
-        "examples": [
-          0.34
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "r": {
-        "description": "Pearson correlation; null when y is constant.",
-        "examples": [
-          0.998
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "r_squared": {
-        "description": "Coefficient of determination; null when y is constant.",
-        "examples": [
-          0.996
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "residual_std_error": {
-        "description": "Standard error of the residuals, sqrt(SSE / df).",
-        "examples": [
-          0.225
-        ],
-        "type": "number"
-      },
-      "slope": {
-        "description": "OLS slope.",
-        "examples": [
-          1.98
-        ],
-        "type": "number"
-      },
-      "slope_ci": {
-        "description": "Lower and upper bound at the confidence level.",
-        "examples": [
-          [
-            1.43,
-            2.53
-          ]
-        ],
-        "items": {
-          "description": "Bound.",
-          "examples": [
-            0
-          ],
-          "type": "number"
-        },
-        "type": "array"
-      },
-      "slope_std_error": {
-        "description": "Standard error of the slope.",
-        "examples": [
-          0.071
-        ],
-        "type": "number"
-      },
-      "slope_t": {
-        "description": "t statistic of the slope; null when undefined.",
-        "examples": [
-          27.8
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "sse": {
-        "description": "Sum of squared residuals.",
-        "examples": [
-          0.152
-        ],
-        "type": "number"
-      },
-      "sst": {
-        "description": "Total sum of squares of y.",
-        "examples": [
-          39.4
-        ],
-        "type": "number"
-      },
-      "t_critical": {
-        "description": "Two-sided t critical value at alpha with df degrees of freedom.",
-        "examples": [
-          3.18
-        ],
-        "type": "number"
-      },
-      "x_mean": {
-        "description": "Mean of x.",
-        "examples": [
-          3
-        ],
-        "type": "number"
-      },
-      "y_mean": {
-        "description": "Mean of y.",
-        "examples": [
-          6.02
-        ],
-        "type": "number"
-      }
-    },
-    "required": [
-      "slope",
-      "intercept",
-      "r",
-      "r_squared",
-      "adjusted_r_squared",
-      "slope_std_error",
-      "intercept_std_error",
-      "residual_std_error",
-      "degrees_of_freedom",
-      "slope_t",
-      "intercept_t",
-      "t_critical",
-      "slope_ci",
-      "intercept_ci",
-      "f_statistic",
-      "sse",
-      "sst",
-      "x_mean",
-      "y_mean"
-    ],
-    "type": [
-      "object",
-      "null"
-    ]
-  },
-  "method": {
-    "description": "How the numbers were produced.",
-    "examples": [
-      "Ordinary least squares (closed form). Student t p-values from the regularised incomplete beta function..."
-    ],
-    "type": "string"
-  },
-  "metrics": {
-    "description": "Metrics computed, in canonical order.",
-    "examples": [
-      [
-        "linear_regression",
-        "normal_distribution",
-        "p_values",
-        "prediction"
-      ]
-    ],
-    "items": {
-      "description": "Metric name.",
-      "enum": [
-        "linear_regression",
-        "normal_distribution",
-        "p_values",
-        "prediction"
-      ],
-      "examples": [
-        "linear_regression"
-      ],
-      "type": "string"
-    },
-    "type": "array"
-  },
-  "n": {
-    "description": "Number of points.",
-    "examples": [
-      5
-    ],
-    "type": "integer"
-  },
-  "normal_distribution": {
-    "description": "Normal model of the chosen values; null when not requested.",
-    "properties": {
-      "excess_kurtosis": {
-        "description": "Excess kurtosis; null when the values are constant.",
-        "examples": [
-          -1.3
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "max": {
-        "description": "Largest value.",
-        "examples": [
-          10.1
-        ],
-        "type": "number"
-      },
-      "mean": {
-        "description": "Sample mean.",
-        "examples": [
-          6.02
-        ],
-        "type": "number"
-      },
-      "median": {
-        "description": "Median of the values.",
-        "examples": [
-          6.2
-        ],
-        "type": "number"
-      },
-      "min": {
-        "description": "Smallest value.",
-        "examples": [
-          2.1
-        ],
-        "type": "number"
-      },
-      "normality": {
-        "description": "Jarque-Bera normality test; null when the values are constant.",
-        "properties": {
-          "null_hypothesis": {
-            "description": "What the test rejects.",
-            "examples": [
-              "the values are normally distributed"
-            ],
-            "type": "string"
-          },
-          "p_value": {
-            "description": "Chi-square(2) p-value, exp(-JB/2).",
-            "examples": [
-              0.81
-            ],
-            "type": "number"
-          },
-          "reject_at_alpha": {
-            "description": "p_value < alpha: not normal at this alpha.",
-            "examples": [
-              false
-            ],
-            "type": "boolean"
-          },
-          "statistic": {
-            "description": "Jarque-Bera statistic.",
-            "examples": [
-              0.42
-            ],
-            "type": "number"
-          },
-          "test": {
-            "const": "jarque_bera",
-            "description": "The test.",
-            "type": "string"
-          }
-        },
-        "required": [
-          "test",
-          "statistic",
-          "p_value",
-          "null_hypothesis",
-          "reject_at_alpha"
-        ],
-        "type": [
-          "object",
-          "null"
-        ]
-      },
-      "of": {
-        "description": "Which values the model fits.",
-        "enum": [
-          "y",
-          "x",
-          "residuals"
-        ],
-        "examples": [
-          "y"
-        ],
-        "type": "string"
-      },
-      "probabilities": {
-        "description": "Answers to probability_queries, in order.",
-        "examples": [
-          [
-            {
-              "probability": 0.736,
-              "query": {
-                "below": 8
-              }
-            }
-          ]
-        ],
-        "items": {
-          "properties": {
-            "probability": {
-              "description": "Probability under the fitted normal.",
-              "examples": [
-                0.736
-              ],
-              "type": "number"
-            },
-            "query": {
-              "description": "The query as sent.",
-              "examples": [
-                {
-                  "below": 8
-                }
-              ],
-              "type": [
-                "object"
-              ]
-            }
-          },
-          "required": [
-            "query",
-            "probability"
-          ],
-          "type": "object"
-        },
-        "type": "array"
-      },
-      "quantiles": {
-        "description": "Quantiles of the fitted normal; null when degenerate.",
-        "items": {
-          "properties": {
-            "p": {
-              "description": "Probability.",
-              "examples": [
-                0.95
-              ],
-              "type": "number"
-            },
-            "value": {
-              "description": "Value at that quantile.",
-              "examples": [
-                11.19
-              ],
-              "type": "number"
-            }
-          },
-          "required": [
-            "p",
-            "value"
-          ],
-          "type": "object"
-        },
-        "type": [
-          "array",
-          "null"
-        ]
-      },
-      "skewness": {
-        "description": "Sample skewness; null when the values are constant.",
-        "examples": [
-          0.05
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "std_dev": {
-        "description": "Sample standard deviation (n - 1).",
-        "examples": [
-          3.14
-        ],
-        "type": "number"
-      },
-      "variance": {
-        "description": "Sample variance (n - 1).",
-        "examples": [
-          9.86
-        ],
-        "type": "number"
-      }
-    },
-    "required": [
-      "of",
-      "mean",
-      "std_dev",
-      "variance",
-      "min",
-      "max",
-      "median",
-      "skewness",
-      "excess_kurtosis",
-      "quantiles",
-      "probabilities",
-      "normality"
-    ],
-    "type": [
-      "object",
-      "null"
-    ]
-  },
-  "notes": {
-    "description": "Caveats about the input; empty when there are none.",
-    "examples": [
-      []
-    ],
-    "items": {
-      "description": "A caveat about a degenerate input.",
-      "examples": [
-        "The points lie exactly on a line."
-      ],
-      "type": "string"
-    },
-    "type": "array"
-  },
-  "p_values": {
-    "description": "Hypothesis tests validated at alpha; null when not requested.",
-    "properties": {
-      "intercept": {
-        "description": "One two-sided Student t test.",
-        "properties": {
-          "null_hypothesis": {
-            "description": "What the test rejects.",
-            "examples": [
-              "slope = 0 (no linear relationship)"
-            ],
-            "type": "string"
-          },
-          "p_value": {
-            "description": "Two-sided p-value; null when undefined.",
-            "examples": [
-              0.0015
-            ],
-            "type": [
-              "number",
-              "null"
-            ]
-          },
-          "significant_at_alpha": {
-            "description": "p_value < alpha.",
-            "examples": [
-              true
-            ],
-            "type": [
-              "boolean",
-              "null"
-            ]
-          },
-          "t": {
-            "description": "Student t statistic; null when undefined (a perfect fit).",
-            "examples": [
-              11.4
-            ],
-            "type": [
-              "number",
-              "null"
-            ]
-          }
-        },
-        "required": [
-          "null_hypothesis",
-          "t",
-          "p_value",
-          "significant_at_alpha"
-        ],
-        "type": "object"
-      },
-      "normality_of_residuals": {
-        "description": "Jarque-Bera normality test; null when the values are constant.",
-        "properties": {
-          "null_hypothesis": {
-            "description": "What the test rejects.",
-            "examples": [
-              "the values are normally distributed"
-            ],
-            "type": "string"
-          },
-          "p_value": {
-            "description": "Chi-square(2) p-value, exp(-JB/2).",
-            "examples": [
-              0.81
-            ],
-            "type": "number"
-          },
-          "reject_at_alpha": {
-            "description": "p_value < alpha: not normal at this alpha.",
-            "examples": [
-              false
-            ],
-            "type": "boolean"
-          },
-          "statistic": {
-            "description": "Jarque-Bera statistic.",
-            "examples": [
-              0.42
-            ],
-            "type": "number"
-          },
-          "test": {
-            "const": "jarque_bera",
-            "description": "The test.",
-            "type": "string"
-          }
-        },
-        "required": [
-          "test",
-          "statistic",
-          "p_value",
-          "null_hypothesis",
-          "reject_at_alpha"
-        ],
-        "type": [
-          "object",
-          "null"
-        ]
-      },
-      "slope": {
-        "description": "One two-sided Student t test.",
-        "properties": {
-          "null_hypothesis": {
-            "description": "What the test rejects.",
-            "examples": [
-              "slope = 0 (no linear relationship)"
-            ],
-            "type": "string"
-          },
-          "p_value": {
-            "description": "Two-sided p-value; null when undefined.",
-            "examples": [
-              0.0015
-            ],
-            "type": [
-              "number",
-              "null"
-            ]
-          },
-          "significant_at_alpha": {
-            "description": "p_value < alpha.",
-            "examples": [
-              true
-            ],
-            "type": [
-              "boolean",
-              "null"
-            ]
-          },
-          "t": {
-            "description": "Student t statistic; null when undefined (a perfect fit).",
-            "examples": [
-              11.4
-            ],
-            "type": [
-              "number",
-              "null"
-            ]
-          }
-        },
-        "required": [
-          "null_hypothesis",
-          "t",
-          "p_value",
-          "significant_at_alpha"
-        ],
-        "type": "object"
-      }
-    },
-    "required": [
-      "slope",
-      "intercept",
-      "normality_of_residuals"
-    ],
-    "type": [
-      "object",
-      "null"
-    ]
-  },
-  "prediction": {
-    "description": "One entry per predict_x; null when not requested.",
-    "items": {
-      "properties": {
-        "mean_ci": {
-          "description": "Lower and upper bound at the confidence level.",
-          "examples": [
-            [
-              1.43,
-              2.53
-            ]
-          ],
-          "items": {
-            "description": "Bound.",
-            "examples": [
-              0
-            ],
-            "type": "number"
-          },
-          "type": "array"
-        },
-        "prediction_interval": {
-          "description": "Lower and upper bound at the confidence level.",
-          "examples": [
-            [
-              1.43,
-              2.53
-            ]
-          ],
-          "items": {
-            "description": "Bound.",
-            "examples": [
-              0
-            ],
-            "type": "number"
-          },
-          "type": "array"
-        },
-        "x": {
-          "description": "The x asked for.",
-          "examples": [
-            6
-          ],
-          "type": "number"
-        },
-        "y_hat": {
-          "description": "Predicted y.",
-          "examples": [
-            11.96
-          ],
-          "type": "number"
-        }
-      },
-      "required": [
-        "x",
-        "y_hat",
-        "mean_ci",
-        "prediction_interval"
-      ],
-      "type": "object"
-    },
-    "type": [
-      "array",
-      "null"
-    ]
-  },
-  "source": {
-    "description": "Where the data came from and how much of it was used.",
-    "properties": {
-      "gib_processed": {
-        "description": "Gibibytes BigQuery scanned; null for inline points.",
-        "examples": [
-          null
-        ],
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "rows_available": {
-        "description": "Rows with finite x and y in the table; null for inline points.",
-        "examples": [
-          null
-        ],
-        "type": [
-          "integer",
-          "null"
-        ]
-      },
-      "rows_used": {
-        "description": "Points the statistics were computed from.",
-        "examples": [
-          5
-        ],
-        "type": "integer"
-      },
-      "sampled": {
-        "description": "True when the table had more usable rows than were read.",
-        "examples": [
-          false
-        ],
-        "type": "boolean"
-      },
-      "sql": {
-        "description": "The read-only SQL that ran, when source is bigquery.",
-        "examples": [
-          null
-        ],
-        "type": [
-          "string",
-          "null"
-        ]
-      },
-      "table": {
-        "description": "BigQuery table read, when source is bigquery.",
-        "examples": [
-          null
-        ],
-        "type": [
-          "string",
-          "null"
-        ]
-      },
-      "type": {
-        "description": "Where the points came from.",
-        "enum": [
-          "points",
-          "bigquery"
-        ],
-        "examples": [
-          "points"
-        ],
-        "type": "string"
-      },
-      "x_column": {
-        "description": "Column used for x, when source is bigquery.",
-        "examples": [
-          null
-        ],
-        "type": [
-          "string",
-          "null"
-        ]
-      },
-      "y_column": {
-        "description": "Column used for y, when source is bigquery.",
-        "examples": [
-          null
-        ],
-        "type": [
-          "string",
-          "null"
-        ]
-      }
-    },
-    "required": [
-      "type",
-      "table",
-      "x_column",
-      "y_column",
-      "sql",
-      "rows_available",
-      "rows_used",
-      "sampled",
-      "gib_processed"
-    ],
-    "type": "object"
-  }
-}

removedOutput schema / properties / result / required

Removed value: -[
-  "source",
-  "n",
-  "alpha",
-  "confidence_level",
-  "metrics",
-  "linear_regression",
-  "normal_distribution",
-  "p_values",
-  "prediction",
-  "notes",
-  "method"
-]

removedOutput schema / properties / status / description

Removed value: -"Present only on a delivered result."

removedOutput schema / properties / worker / description

Removed value: -"Catalog name of the worker that ran."

removedOutput schema / properties / worker / examples
```
Removed value: -[
-  "market.quote"
-]
```

removedOutput schema / title

Removed value: -"stats.probability response"

Changed1 schema field changedSep 28, 2026

addedOutput schema / properties / attribution

Added value: +{
+  "description": "Present only when the result's text was machine-translated: the credit to show with it.",
+  "items": {
+    "description": "A credit.",
+    "properties": {
+      "text": {
+        "description": "Credit.",
+        "examples": [
+          "Translated by Google"
+        ],
+        "type": "string"
+      },
+      "url": {
+        "description": "Link.",
+        "examples": [
+          "https://translate.google.com"
+        ],
+        "type": "string"
+      }
+    },
+    "required": [
+      "text",
+      "url"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}

Changed1 schema field changedSep 27, 2026

addedInput schema / properties / language

Added value: +{
+  "description": "Optional BCP-47 language tag (en, ja, ko, pt-BR): the human-readable strings of the result (notes, details, reasons) are translated into this language; data, codes, numbers and URLs are untouched. Default: as produced.",
+  "maxLength": 35,
+  "pattern": "^[A-Za-z]{2,3}(-[A-Za-z0-9]{2,8})*$",
+  "type": "string"
+}

Changed1 schema field changedSep 27, 2026

changedOutput schema / description

Previous value: -"The 200 body of every paid /work call. `result` is the worker's own output (its schema is per route); everything else is the same on all 38 routes. A receipt for the job is at `receipt_url`."New value: +"The 200 body of every paid /work call. `result` is the worker's own output (its schema is per route); everything else is the same on every /work route. A receipt for the job is at `receipt_url`."

AddedSep 23, 2026

TDQS

A4.1/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent and non-destructive, and the description adds genuinely new operational facts: the $0.50 per-call cost, the BigQuery service-account readability requirement for table sources, and the determinism guarantee. It also notes that max_rows sampling is fingerprinted so the same table yields the same rows — a non-obvious behavior that no annotation conveys.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and capability are front-loaded before the operational details (determinism, input/output inventory, price), and no sentence is filler. The 'Input: … Returns: …' inventory is somewhat list-like and partially redundant with an output schema that already exists, which keeps it below a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter analytical tool with no required fields, the description covers the data sources, optional knobs, determinism, cost, auth expectations and result shape. An output schema exists, so the explicit return-field list is extra assurance rather than a gap-filler, and nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and every parameter (alpha, table, points, metrics, language, max_rows, x_column, y_column, predict_x, distribution_of, probability_queries) is documented in the schema itself. The description only restates the parameter names in an 'Input:' list without adding semantics such as defaults, ranges, or format detail, so the schema is doing the real work and the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names exactly what is computed: least-squares linear regression with standard errors and intervals, a fitted normal distribution with quantiles, and exact Student t / Jarque-Bera p-values. The line 'Deterministic arithmetic, no LLM: the same input always returns the same numbers' usefully separates it from the LLM-backed siblings. It stops short of naming which sibling to use instead (e.g. hubvibe_data_forecast or hubvibe_market_prediction), so the differentiation is partial.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear context for invocation — supply points inline or a BigQuery table, choose metrics, add predict_x for predictions — and the mutual exclusivity of points vs table is stated. There are no explicit exclusions or 'do not use this when' guidance pointing at competing tools such as the forecast or market prediction siblings, so it is clear but not fully routed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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