lineage_examples

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

With no annotations provided, the description carries the burden. It discloses the parameter behavior (pass one to filter, omit to get all) and the structure of each example (question, graphql, variables, notes). It also indicates the categories available, which adds behavioral context beyond the bare schema. There is no contradiction with annotations since none exist.

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?

The description is compact and well-structured, with the main purpose in the first sentence, followed by category list and example structure. Every sentence adds value, and there is no redundant information.

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?

Given the tool has only one optional parameter and an output schema exists (which defines the returned structure), the description covers all essential aspects: what it returns, how to filter, and what each example contains. It is sufficiently complete for an agent to invoke correctly without further clarification.

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 0%, so the description must compensate for the category parameter. It does so thoroughly by listing all valid categories (impact, provenance, calc, datasource, search, inventory, governance, ownership) and explaining that passing one filters while omitting returns all. This fully explains both the meaning and usage of the parameter.

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 uses a clear verb 'Return' and specifies the resource: a schema cheat-sheet and a curated library of lineage questions with GraphQL queries and variables. It distinguishes itself from sibling tools like graphql_query, which executes queries, and where_used/impact_analysis, which are specific lineage analysis 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?

The description explicitly says 'Read this before composing a `graphql_query`', providing clear when-to-use guidance. It also explains the optional category filter and the ability to omit it, giving clear usage context. However, it does not explicitly mention when not to use it or contrast with other siblings beyond graphql_query.

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