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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently states the output format ('One JSON row per series: latest and previous value with dates, % change, signal quality, source URL'), the cost ('$0.005 USDC'), a free preview ('Free 3-row sample at /preview'), and an HTTP twin. It does not mention rate limits or authentication, but the disclosed behaviors are substantial and beyond typical.

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 dense but each sentence adds value: purpose, content categories, output format, cost, preview, and alternate access. It is front-loaded with the primary purpose and structured logically. While not the shortest, it avoids fluff and is appropriately sized for the amount of essential 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?

Since there is no output schema, the description must explain return values, and it does ('One JSON row per series...'). It also covers cost, preview, and an HTTP alternative. It does not address error handling or rate limits, but for a single-call data retrieval tool with no parameters, the description is sufficiently complete for an agent to invoke 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?

There are zero parameters, so the schema coverage is trivially 100%. The rubric sets a baseline of 4 for zero parameters, and the description does not need to add parameter details. It does provide context about the output and usage that indirectly explains what the tool returns, but no parameter semantics are necessary.

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 states a specific verb ('get the current state of AI progress') and a clear resource ('latest reading of 129 public series'), listing concrete categories. It distinguishes itself from siblings by emphasizing 'latest' and 'current state', which contrasts with ai_progress_as_of and ai_progress_what_changed. The purpose is unambiguous and action-oriented.

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 opens with 'Use this when you need the current state of AI progress in one call', providing clear context for when to use it. However, it does not explicitly mention alternatives or when not to use it, such as pointing to ai_progress_as_of for historical data. This is a clear usage context without exclusions, fitting the score 4 criterion.

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