Trace an entity's dependencies and dependents by direction and depth to map data flow and impact in Kin repositories.
What one entity depends on and what depends on it. Paths: trace_data_flow.
| Name | Required | Description | Default |
|---|---|---|---|
| depth | No | Hops. | |
| limit | No | Max entities. | |
| direction | No | `out` deps, `in` dependents, or `both`. | both |
| entity_id | Yes | UUID | |
| max_chars | No | Soft cap on reply bytes. |
Changes observed during successful MCP inspections.
v0.7.17Input schema / properties / depth / descriptionPrevious value: -"Traversal depth"New value: +"Hops."Input schema / properties / direction / descriptionPrevious value: -"`out` for what the focal depends on, `in` for what depends on it, `both` merges."New value: +"`out` deps, `in` dependents, or `both`."Input schema / properties / entity_id / descriptionPrevious value: -"Entity UUID"New value: +"UUID"Input schema / properties / limit / descriptionPrevious value: -"Max entities to return (default 30)"New value: +"Max entities."Input schema / properties / max_chars / descriptionPrevious value: -"Serialized characters this response may occupy; what was cut is named in `elisions`."New value: +"Soft cap on reply bytes."v0.7.16Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds nothing behavioral beyond that — it does not mention the reply-byte truncation (max_chars soft cap) or how depth/limit affect the returned subgraph.
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?
Two short fragments, zero padding, and the core purpose is front-loaded in the first sentence. The second fragment is arguably too compressed, costing a point rather than the whole.
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?
For a graph traversal tool with 5 parameters, no output schema, and rich annotations, the description is minimally adequate: it conveys the concept but says nothing about the shape of the result (nodes/edges, depth semantics, truncation behavior) that the schema does not already cover.
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 all five parameters (depth, limit, direction, entity_id, max_chars) are already documented in the schema. The description adds no semantics on top of that, which puts it at the baseline of 3.
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 first sentence names the resource (one entity's neighborhood) and specifies both directions of the relationship ('depends on' and 'depends on it'), which is specific enough to distinguish it from generic search tools. It falls short of a 5 only because it omits any verb framing of what is returned (a graph/subgraph) and leans on a cryptic sibling reference for differentiation.
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?
The 'Paths: trace_data_flow' fragment gestures at an alternative for multi-hop path queries, but it is telegraphic rather than explicit — no 'use this when / use that when' condition is stated. An agent can infer the routing, but must guess at it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.