get_project_details

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

With no annotations provided, the description fully bears the burden of behavioral disclosure. It clearly conveys the tool's non-destructive, read-only nature by stating it retrieves records. However, it does not disclose potential side effects like logging, or rate limits, which slightly limits transparency. The indication that matching is forgiving and alias-aware adds valuable behavioral context, justifying a 4.

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 efficiently structured, front-loading the tool's purpose in the first sentence, then elaborating on behavioral nuance (flagship vs lighter items) in a natural flow. Every sentence adds value, and the Args section is clearly separated and self-contained. There is no wasted text.

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 parameter, no annotations, and no output schema, the description provides sufficient context for an AI agent to select and invoke the tool correctly. It covers input semantics, matching behavior, variation in returned data, and even suggests a complementary sibling tool (list_projects). The description is complete for this single-param retrieval tool.

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?

The schema has 0% description coverage and only one parameter ('name'), so the description must fully compensate. It excels by describing acceptable inputs (project name, id, alias, or competition name), provides concrete examples, and explains matching behavior (case-insensitive, partial, alias-aware). This adds rich semantics far beyond the schema's bare type declaration.

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 explicitly states the tool retrieves the full record for one portfolio item, differentiating between flagship projects (returns detailed fields like role, tech stack, outcomes) and lighter items (returns description and links). This clear verb+resource+variation makes the purpose highly specific and distinct from siblings like list_projects.

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 provides explicit guidance on when to use this tool (to get full details of a single portfolio item) and includes a clear when-not alternative: it advises calling list_projects first to select the right item when unsure about the name. This pre-emptive guidance prevents misuse and clarifies the tool's role in a workflow.

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