getTask
Get a task by ID with full details, evidence, activity, and the checklist array (each item: id, text, due_date, completed_at, plus server-stamped attribution). Returns versionTimestamp; pass it to updateTask to modify. Includes percent_complete for progress tracking. Also returns the work hierarc...
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What getTask does on Stable Baseline
AI agents call getTask to retrieve information from Stable Baseline without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
taskId | string | Yes | Accepts either the UUID or the friendly id (e.g. TAS-176); friendly ids are resolved within your organisation. |
projectId | string | — | Optional. Narrows a friendly-id lookup to one project. Only needed when a friendly id is ambiguous — TAS-/IMP-/PLN- ids are numbered per PROJECT, so the same id |
Parameters from the server's own tool schema.
Why getTask is rated Low
Even though getTask only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs getTask safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Stable Baseline, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For getTask, this is the rule to start with:
getTask is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Stable Baseline, apply this rule, and every getTask call is checked against it from then on.
Questions about getTask
Get a task by ID with full details, evidence, activity, and the checklist array (each item: id, text, due_date, completed_at, plus server-stamped attribution). Returns versionTimestamp; pass it to updateTask to modify. Includes percent_complete for progress tracking. Also returns the work hierarchy: parentItem (the item this one belongs to, such as its epic or story: { id, friendlyId, title, type, status, isTask }, or null), children (the items that belong to it, in status order then by id, at most 200: each with ownerId, ownerTeamId and percentComplete) and childProgress { total, done, closed } over every child (closed counts done, rejected and deferred). Set a parent with parentItemId on updateImprovement or updateTask. Also returns linkedRecords: the database rows it links, each { linkId, databaseId, tableId, rowId, state, label, title, autoId, tableName, databaseName, href } read for you. state ok gives the row's title and a link to it; no_access means you cannot read that row, so no title is given; removed means the row, its table or its database was deleted. Change them with linkedRecords on updateImprovement or updateTask. It is categorised as a Read tool in the Stable Baseline MCP Server, which means it retrieves data without modifying state.
getTask accepts 2 parameters: taskId, projectId. Required: taskId. The full parameter table on this page comes from the server's own tool schema.
Register the Stable Baseline MCP server in PolicyLayer and add a rule for getTask: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Stable Baseline. Nothing to install.
getTask is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the getTask rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for getTask. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
getTask is provided by the Stable Baseline MCP server (https://api.stablebaseline.io/functions/v1/cloud-serve/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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