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ddflow_session_start

Start a provenance logging session and receive a unique session ID to track AI agent actions and workflow context.

Instructions

Open a session for provenance logging. Returns the session id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolNoYour harness, e.g. 'claude-code'.
modelNoYour model id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It mentions that a session is opened and that an id is returned, but it does not state whether this mutates persistent state, whether the call is idempotent, what side effects occur, or whether a corresponding session_end is required. For a state-changing tool, this is a notable gap.

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

Conciseness5/5

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

Two short sentences deliver the core purpose and return value with no wasted words. The description is efficiently front-loaded and easy to scan.

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

Completeness3/5

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

For a simple 2-parameter tool with no output schema, the description covers the basic call and return, but omits important context such as the session lifecycle, whether setup is required, and how the returned id is used by other ddflow tools. It is minimally viable but has clear gaps.

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 both 'tool' and 'model' already described in the input schema. The description adds no additional meaning about these parameters, so the baseline of 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 states a specific verb and resource: 'Open a session for provenance logging' and identifies the return value ('Returns the session id'). It distinguishes from session_end, session_note, and session_prompt by signaling the start of a session, though it does not explicitly name or contrast with siblings.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool, what prerequisites exist, or how it relates to sibling tools like ddflow_setup, ddflow_session_end, or ddflow_recover. The description implies a session-opening role but gives no explicit when-to-use or when-not-to-use guidance.

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