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Start Pipeline Session

dcl_pipeline_start

Start a pipeline session to run a series of checks. Configure scope, payment, and TTL via the agent ID to begin the audit.

Instructions

SESSION Management ($0.05). Opens a pipeline session for a series of checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoScope label for the session.default
agent_idYesIdentifier of the agent that owns this session.
payment_idNoOptional payment identifier returned by a previous call when payment is required
ttl_secondsNoSession time-to-live, in seconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeYesScope label for the session.
agent_idYesIdentifier of the agent that owns this session.
drift_modeYesDrift status at session start (always NORMAL for a new session).
expires_atYesUnix timestamp when the session expires.
pipeline_idYesUnique identifier for the newly opened pipeline session.
Behavior3/5

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

Annotations already indicate a non-read-only, non-idempotent operation. The description adds the '$0.05' cost and the notion of a session for multiple checks, which is useful. However, it does not disclose behaviors like whether sessions replace existing ones, how payment_id relates, or lifecycle details beyond what ttl_seconds suggests. The added value is modest.

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 description is very brief—one substantive sentence plus a cost annotation. It is front-loaded with the 'SESSION Management' label and cost. Slightly less polished because 'SESSION Management ($0.05).' reads more like a heading than a sentence, but there is no wasted wording.

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 the surrounding context—sibling tools are all evaluate/audit operations, the schema fully documents parameters, annotations provide safety hints, and an output schema exists—the description is mostly complete. It conveys the session's purpose and cost. It could be more explicit about being a prerequisite for evaluators, but the overall package is sufficient for correct invocation.

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%, with each parameter individually described. The description does not add parameter-specific semantics beyond the schema, so the baseline of 3 applies. The session purpose ('for a series of checks') provides some context but does not explain individual parameters.

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

Purpose5/5

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

The description clearly states the tool's function with a specific verb ('Opens') and resource ('pipeline session'), and adds the purpose ('for a series of checks'). This distinguishes it from sibling evaluation and audit tools, which are checks themselves rather than session management.

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

Usage Guidelines3/5

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

Usage is implied by the name and description: it opens a session for a series of checks, suggesting it precedes evaluation tools. However, there is no explicit guidance on when to use it, prerequisites, or alternatives. The context is clear enough for a capable agent to infer, but no exclusions or comparisons are given.

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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