get_planning_graph

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds meaningful context by explaining that the graph is dependency-aware and focuses on entry points and blocking nodes, which goes beyond the structured annotations.

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 a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's core purpose and output.

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 output schema covers return values, so lack of return-value description is acceptable. However, with 7 optional parameters and low schema coverage, the description leaves significant gaps about parameter usage and when to invoke this tool, making it only partially complete for reliable invocation.

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 43%, and the description does not compensate by explaining the key parameters: depth, max_nodes, include_review, and include_related. These remain ambiguous, and the description provides no additional semantic guidance beyond the sparse schema descriptions.

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 clearly states the tool gets dependency-aware entry points and blocking nodes, naming the specific resource (planning graph) and its purpose (work selection). This differentiates it from siblings like get_issue_graph and get_work_context, which focus on different aspects.

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 phrase 'for work selection' implies a use case but does not explicitly state when to use this tool over alternatives, nor does it provide exclusions. The agent must infer the appropriate context from the tool name and description alone.

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