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Read positive, negative, neutral, or net sentiment for scored entities.
get_sentiment. Operation: read. Uses the authorized connection; no project or content changes are made by this tool.
| Name | Type | Required | Default | Meaning and accepted values |
|---|---|---|---|---|
project_id | string | Yes | Required | Project ID from list_projects. Select the project in the intended workspace and environment. |
run_id | string | Yes | Required | Run ID from list_runs for this project. Use the exact returned value and check readiness before reading measurements. |
metric | string | No | 'positive' | positive, negative, or neutral selects that sentiment rate; net selects the signed balance of positive and negative sentiment. |
aggregation_level | string | No | 'entity' | Accepts entity or bundle, but this edition returns entity-level sentiment rows for either value. A bundle request does not combine names. |
group_by | string[] or null | No | null | Split results into rows by the requested dimensions. Check both filters_applied.group_by and each row’s group_by_values before labeling the groups. |
filters | object[] or null | No | null | Select measured answers with objects containing dimension and values. Use labels from list_dimension_options; inspect returned warnings for filters that were not applied. |
subject | string or object or null | No | null | Choose brands with kind: leaderboard, all, self, self_and_competitors, or specified. For specified, provide entities_or_bundles. An unmeasured name is not a measured zero. |
params object for MCP tools/call.
{
"name": "get_sentiment",
"arguments": {
"project_id": "PROJECT_ID",
"run_id": "RUN_ID",
"metric": "net",
"aggregation_level": "entity",
"subject": {
"kind": "self_and_competitors"
}
}
}
subject_summary.unscored_entities and warnings for requested names without sentiment results.
| Field | Meaning and use |
|---|---|
data.metric | Sentiment rate or signed net score requested. |
data.rows[].entity_or_bundle | The name whose sentiment was scored. |
data.rows[].estimate | Returned sentiment value, interval, and row quality. Keep the interval even when the value appears strongly positive or negative. |
data.rows[].n_classified_mentions | Classified mention count attached to the sentiment row. |
data.rows[].n_unclassified_mentions | Unclassified count returned by this response. Do not infer it from the sum of the three exposed sentiment rates. |
{
"data_ready": true,
"data": {
"metric": "net",
"aggregation_level": "entity",
"rows": [
{
"entity_or_bundle": "Color Science",
"group_by_values": {},
"estimate": {
"value": 1,
"ci": {
"lower": -0.96,
"upper": 1,
"level": 0.95
},
"n": 1,
"stability": "insufficient",
"stability_n": 1
},
"n_classified_mentions": 1,
"n_unclassified_mentions": 0
}
]
}
}