tigergraph__get_graph_schema

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value beyond that by specifying the return format (structured JSON with vertex/edge types and attributes) and the scope exclusion (not queries or jobs), which clarifies behavior the annotations don't convey.

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?

Well-structured and front-loaded: the core purpose lands in the first sentence, followed by labeled sections (Use When, Quick Start, Tips, Related Tools). Every section earns its place—the quick start is a valid minimal invocation, and the related tool notes are the differentiators an agent needs. Zero filler.

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 read-only tool with two optional params and no nested objects, the description is nearly complete. Since there's no output schema, it compensates by naming what the JSON contains (vertex types, edge types, attributes). The only minor gap is the exact JSON shape/format, but the stated contents and annotations cover what an agent needs to call it correctly.

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% — both profile and graph_name are already well-documented in the schema with default behavior explained. The description adds a concrete Quick Start example (graph_name: 'SocialNetwork'), which is mildly useful but not substantive new semantics, so the baseline 3 is appropriate.

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 opening sentence states a specific verb and resource—'Get the schema of a specific graph — vertex types, edge types, and their attributes — as structured JSON'—and immediately distinguishes it from siblings with 'Returns schema only, not queries or jobs.' An agent can tell it apart from show_graph_details and list_graphs without opening their schemas.

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?

A dedicated 'Use When' section lists concrete trigger conditions (knowing vertex/edge types, building or validating queries, programmatic inspection), and the Tips section explicitly routes to alternatives: 'For a full listing including queries and jobs, use show_graph_details' and 'For just graph names, use list_graphs.' Nothing is left to inference.

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