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Python

Remote

List operations

list_operations

Read-only

Retrieve and filter paginated task operations for your workspace by type, integration, status, external ID, or task run ID. Set time windows to control returned results.

Instructions

Retrieve a paginated list of task operations for the workspace the credential resolves to.

From 2026-10-01 the default changed from the last 7 days to the last 24 hours. Pass time_from and time_to explicitly to control the window.

Use operation filters to narrow results by operation type, integration, external ID, operation status, or task run ID.

Input Schema

TableJSON Schema

Name	Required	Description
`page`	No	Page number. Must be greater than or equal to 1.
`status`	No	Filter by status.
`time_to`	No	End of the time window as an ISO 8601 datetime.
`page_size`	No	Number of items per page. Defaults to 50; maximum 100.
`time_from`	No	Start of the time window as an ISO 8601 datetime.
`external_id`	No	External system identifier to filter by.
`integration`	No	Integration identifier.
`task_run_id`	No	Task run ID.
`operation_type`	No	Filter by operation type. Comma-separated values are supported.
`X-Orchestra-Account-Id`	No	Act on this account rather than the one the credential resolves to. Omit it to use the credential's own account. An API key is issued to a single account, so it may only name that account; an OAuth token may name any account its grant covers.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.1Sep 30, 2026

changedInput schema / properties / integration / anyOf

Previous value: -[
-  {
-    "enum": [
-      "AIRBYTE_CLOUD",
-      "AIRBYTE_SERVER",
-      "AIRFLOW",
-      "ARCH",
-      "ALTERYX_SERVER",
-      "ANTHROPIC",
-      "AWS_EC2",
-      "AWS_ECS",
-      "AWS_EMR",
-      "AWS_EKS",
-      "AWS_FIREHOSE",
-      "AWS_GLUE",
-      "AWS_LAMBDA",
-      "AWS_RDS",
-      "AWS_REDSHIFT",
-      "AWS_S3",
-      "AWS_BEDROCK",
-      "AWS_SAGEMAKER",
-      "AWS_SECRETS_MANAGER",
-      "AWS_SES",
-      "AWS_STEP_FUNCTIONS",
-      "AZURE",
-      "AZURE_CONTAINER_APPS",
-      "AZURE_DATA_FACTORY",
-      "AZURE_DATA_LAKE_STORAGE",
-      "AZURE_KEY_VAULT",
-      "AZURE_KUBERNETES_SERVICE",
-      "AZURE_LOGIC_APPS",
-      "AZURE_SYNAPSE_ANALYTICS",
-      "AZURE_VM",
-      "BAUPLAN",
-      "BOOMI",
-      "CDATA",
-      "CENSUS",
-      "CLICKHOUSE",
-      "COALESCE",
-      "COUNT",
-      "DATADOG",
-      "DATABRICKS",
-      "DATAPROC",
-      "DATAZEN",
-      "DBT",
-      "DBT_CORE",
-      "DLT",
-      "DOMO",
-      "DREMIO",
-      "DUCKDB",
-      "EMAIL",
-      "ESTUARY",
-      "ETLEAP",
-      "FABRIC",
-      "FABRIC_SYNAPSE",
-      "FIVETRAN",
-      "FORTRA",
-      "GCP_BIG_QUERY",
-      "GCP_CLOUD_RUN",
-      "GCP_CLOUD_FUNCTIONS",
-      "GCP_CLOUD_STORAGE",
-      "GCP_DATAFLOW",
-      "GCP_DATAFORM",
-      "GCP_DATASTREAM",
-      "GCP_LOOKER",
-      "GKE",
-      "GITHUB_ACTIONS",
-      "GOOGLE_CLOUD",
-      "HEVO",
-      "HEX",
-      "HIGHTOUCH",
-      "HTTP",
-      "HUBSPOT",
-      "INFORMATICA_IICS",
-      "INFORMATICA_POWERCENTER",
-      "KAFKA",
-      "KEBOOLA",
-      "KLEENE",
-      "LIGHTDASH",
-      "LINUX_SSH",
-      "MATILLION",
-      "MATILLION_ETL",
-      "METAPLANE",
-      "MICROSOFT_TEAMS",
-      "MICROSTRATEGY",
-      "MONGODB",
-      "MOTHERDUCK",
-      "MYSQL",
-      "N8N",
-      "NIMBLE",
-      "NOTION",
-      "OMNI",
-      "OPEN_AI",
-      "ORCHESTRA",
-      "PARADIME",
-      "PAGER_DUTY",
-      "PINECONE",
-      "PORTABLE",
-      "POSTGRES",
-      "POWER_AUTOMATE",
-      "POWER_BI",
-      "PREFECT_CLOUD",
-      "PYTHON",
-      "QLIK",
-      "QLIK_REPLICATE",
-      "QUICKBOOKS",
-      "RENDER",
-      "RIVERY",
-      "RUDDERSTACK",
-      "SALESFORCE",
-      "SAP",
-      "SFTP",
-      "SHAREPOINT",
-      "SIGMA",
-      "SISENSE",
-      "SLACK",
-      "SNOWFLAKE",
-      "SNOWPLOW",
-      "SODA",
-      "SQL_MESH",
-      "SQL_SERVER",
-      "STITCH",
-      "STREAMKAP",
-      "TABLEAU_CLOUD",
-      "TALEND_CLOUD",
-      "THOUGHTSPOT",
-      "TOBIKO_CLOUD",
-      "WEAVIATE",
-      "WEBHOOK",
-      "WELD",
-      "WINDOWS_SSH"
-    ],
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "enum": [
+      "AIRBYTE_CLOUD",
+      "AIRBYTE_SERVER",
+      "AIRFLOW",
+      "ARCH",
+      "ALTERYX_SERVER",
+      "ANTHROPIC",
+      "AWS_EC2",
+      "AWS_ECS",
+      "AWS_EMR",
+      "AWS_EKS",
+      "AWS_FIREHOSE",
+      "AWS_GLUE",
+      "AWS_LAMBDA",
+      "AWS_RDS",
+      "AWS_REDSHIFT",
+      "AWS_S3",
+      "AWS_BEDROCK",
+      "AWS_SAGEMAKER",
+      "AWS_SECRETS_MANAGER",
+      "AWS_SES",
+      "AWS_STEP_FUNCTIONS",
+      "AZURE",
+      "AZURE_CONTAINER_APPS",
+      "AZURE_DATA_FACTORY",
+      "AZURE_DATA_LAKE_STORAGE",
+      "AZURE_KEY_VAULT",
+      "AZURE_KUBERNETES_SERVICE",
+      "AZURE_LOGIC_APPS",
+      "AZURE_SYNAPSE_ANALYTICS",
+      "AZURE_VM",
+      "BAUPLAN",
+      "BOOMI",
+      "CDATA",
+      "CENSUS",
+      "CLICKHOUSE",
+      "COALESCE",
+      "COUNT",
+      "DATADOG",
+      "DATABRICKS",
+      "DATAPROC",
+      "DATAZEN",
+      "DBT",
+      "DBT_CORE",
+      "DLT",
+      "DOMO",
+      "DREMIO",
+      "DUCKDB",
+      "EMAIL",
+      "ESTUARY",
+      "ETLEAP",
+      "FABRIC",
+      "FABRIC_SYNAPSE",
+      "FIVETRAN",
+      "FORTRA",
+      "GCP_BIG_QUERY",
+      "GCP_CLOUD_RUN",
+      "GCP_CLOUD_FUNCTIONS",
+      "GCP_CLOUD_STORAGE",
+      "GCP_DATAFLOW",
+      "GCP_DATAFORM",
+      "GCP_DATASTREAM",
+      "GCP_LOOKER",
+      "GKE",
+      "GITHUB_ACTIONS",
+      "GOOGLE_CLOUD",
+      "HEVO",
+      "HEX",
+      "HIGHTOUCH",
+      "HTTP",
+      "HUBSPOT",
+      "INFORMATICA_IICS",
+      "INFORMATICA_POWERCENTER",
+      "KAFKA",
+      "KEBOOLA",
+      "KLEENE",
+      "LIGHTDASH",
+      "LINUX_SSH",
+      "MARIADB",
+      "MATILLION",
+      "MATILLION_ETL",
+      "METAPLANE",
+      "MICROSOFT_TEAMS",
+      "MICROSTRATEGY",
+      "MONGODB",
+      "MOTHERDUCK",
+      "MYSQL",
+      "N8N",
+      "NIMBLE",
+      "NOTION",
+      "OMNI",
+      "OPEN_AI",
+      "ORCHESTRA",
+      "PARADIME",
+      "PAGER_DUTY",
+      "PINECONE",
+      "PORTABLE",
+      "POSTGRES",
+      "POWER_AUTOMATE",
+      "POWER_BI",
+      "PREFECT_CLOUD",
+      "PYTHON",
+      "QLIK",
+      "QLIK_REPLICATE",
+      "QUICKBOOKS",
+      "RENDER",
+      "RIVERY",
+      "RUDDERSTACK",
+      "SALESFORCE",
+      "SAP",
+      "SFTP",
+      "SHAREPOINT",
+      "SIGMA",
+      "SISENSE",
+      "SLACK",
+      "SNOWFLAKE",
+      "SNOWPLOW",
+      "SODA",
+      "SQL_MESH",
+      "SQL_SERVER",
+      "STITCH",
+      "STREAMKAP",
+      "TABLEAU_CLOUD",
+      "TALEND_CLOUD",
+      "THOUGHTSPOT",
+      "TOBIKO_CLOUD",
+      "WEAVIATE",
+      "WEBHOOK",
+      "WELD",
+      "WINDOWS_SSH"
+    ],
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]

First observedv0.1.0Sep 26, 2026

TDQS

A4.2/5.0

Behavior5/5

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

With readOnlyHint already declaring a safe read, the description adds substantial non-obvious behavior: the 24-hour default window, the 7-day maximum range per request, the 2023-01-01 floor on time_from, and a documented default change effective 2026-10-01. These are exactly the gotchas an agent could not infer from schema or annotations.

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?

The purpose sentence is front-loaded and the note block is well-organized with the time-window rules grouped together. It is slightly long for the amount of information, but every clause (defaults, limits, migration date) earns its place.

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

Completeness4/5

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

Given an output schema exists, return values need not be explained, and the description covers filtering, time-window constraints, credential/account scoping, and pagination. What remains unstated is result ordering and what an 'operation' entity represents, which is minor for a list tool with rich schema support.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds cross-parameter semantics the schema lacks: the interaction between time_from and time_to, the 7-day cap when both are passed, and the default 24-hour window when neither is. That is real added meaning beyond the field-level descriptions.

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?

States a specific verb and resource ('Retrieve a paginated list of task operations') plus the scope ('the workspace the credential resolves to'). It is distinct from siblings like list_task_runs and list_pipeline_runs by naming 'operations', though it does not explicitly contrast itself with the nearest sibling.

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?

Gives clear operational context: when to pass time_from/time_to, what happens when neither is provided, and which filters are available to narrow results. It does not say when to prefer this tool over alternatives such as list_task_runs, so it stops short of full 5-level routing guidance.

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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