Identify Deteriorating Dataset Trends

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful behavioral detail beyond the annotations: results are ranked by staleness slope, they include pipeline-computed trend and reliability evidence, and callers should not recompute that evidence. This gives an agent meaningful expectations about output content and cost.

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 two sentences, starts with the core verb and resource, and contains no filler. Every clause contributes: the ranking criterion, the optional filter, and the note about avoiding recomputation. It is efficiently front-loaded for an agent scanning sibling tools.

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 only two optional parameters, a present output schema, and strong annotations (readOnly, idempotent, non-destructive), the description is complete for selection and invocation. It covers what the tool returns, how it ranks, and an important behavioral caveat about not recomputing evidence. Nothing critical is missing.

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%, so the schema already documents both limit and min_anomaly_rate in detail. The description adds only slight semantic color ('staleness slope', 'historical anomaly rate') that mostly rephrases the schema. Under the baseline rule for high schema coverage, a 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 description clearly states the specific action: return datasets whose published freshness trend is deteriorating, and it adds a distinct ranking criterion ('staleness slope') that separates it from siblings like find_stale or find_recovering. The resource and condition are unambiguous, and the mention of trend-based deterioration distinguishes this from snapshot staleness tools.

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 conveys when to use the tool: when an agent needs deteriorating freshness trends and wants pipeline-computed trend/evidence rather than recomputing it. It does not explicitly name alternatives or state exclusion conditions, but the 'so agents do not recompute it' note is practical guidance. Clear context without formal when-not-to-use guidance keeps this at a 4.

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