Trace a study's impact by retrieving all features it touched, including commit-stamped provenance details.
One study and every feature it touched — the provenance view.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| cwd | No | Directory identifying the project and the tree. Defaults to this session's working directory, which in a git worktree is that worktree. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It reveals that the tool shows provenance relationships, but says nothing about side effects, permissions, output format, pagination, or error behavior.
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?
One tight, memorable sentence with no redundant filler. It is appropriately front-loaded, though it reads as a tagline rather than a complete definition.
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?
The description is incomplete for a caller: it lacks any statement about how to identify the study, what the result looks like, and which sibling should be used instead. With no output schema and no annotations, the sole sentence is insufficient.
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 only 50%: cwd is described but the required id property is not. The description only weakly implies that the id identifies the study; it adds no detail about either parameter or how they interact.
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?
The description communicates a specific resource scope: one study plus every feature it touched, framed as a provenance view. This makes it distinguishable from list-style siblings in intent, though it lacks an explicit verb like 'return' or 'display'.
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?
There is no guidance about when to use this tool versus close siblings like study_status, study_list, or feature_history. The description provides context but no exclusions or alternative selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.