get_ai_tracking_runFetch a project-scoped AI tracking run by project and run ID to inspect original provenance, partial states, and cost uncertainty.
Read project-scoped AI tracking evidence with original provenance, partial states, and cost uncertainty.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes | Public tracking run ID scoped to this project. | |
| project_id | Yes | Public project ID; membership and token scope are enforced. |
Changes observed during successful MCP inspections.
v0.17.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnly, non-destructive, non-open-world). The description adds data-quality context—partial states and cost uncertainty—which is useful beyond the annotations. However, it omits other behavioral details like return format, pagination, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no wasted words. It efficiently states the core action and key data characteristics, though the list-like quality of the trailing attributes keeps it from being a perfect 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With annotations covering safety and schema covering parameters, the description need not explain return values. It provides enough context for a read-only retrieval tool, though it could be slightly more explicit about retrieving a single run by ID.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (run_id, project_id) are documented in the schema. The description adds no additional meaning about parameter formats or constraints beyond what the schema provides, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Read') and resource ('AI tracking evidence') with a project scope. The added attributes (original provenance, partial states, cost uncertainty) hint at what distinguishes it, but it does not explicitly differentiate from sibling list or history tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like list_ai_tracking_runs or get_ai_tracking_history. Usage is only implied by the verb and resource, leaving the agent to infer context from the name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.