get_dashboard_stats

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

No annotations are provided, so the description carries the full burden. 'Get' plus the enumerated read-only content makes the non-mutating nature clear, but it says nothing about data scope (whose data), freshness/caching, or permissions. Adequate for a pure read, but thin given zero annotation coverage.

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 sentences, front-loaded with the resource and followed by the use case. Every clause earns its place — the enumeration is what makes the aggregate verifiable and the second sentence is a genuine routing hint.

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?

With no output schema and no annotations, the description compensates by enumerating the return categories, which is most of what an agent needs to decide whether to call it. Minor gaps remain on data scope and freshness, but nothing essential is missing for a zero-arg read 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 tool takes zero parameters and the schema has no properties, so there is nothing to disambiguate; the baseline of 4 applies.

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?

States a specific verb and resource ('overview of the user's job search progress') and enumerates the content categories returned: job counts by status, scraping metrics, document counts, feature usage. It is clearly an aggregate/summary tool, which sets it apart contextually from narrower siblings like get_scraping_stats, but it never names those siblings to make the distinction explicit.

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?

Gives a concrete usage scenario — 'Great for answering how is my job search going?' — which tells the agent when a summary is the right call. It stops short of stating when to use a narrower alternative (e.g. get_scraping_stats) or any exclusions, so it lacks the explicit routing of a 5.

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