predict_batch_failures

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so safety is covered. The description adds real value beyond that: it discloses the scoring approach (recency-weighted), the risk-level scale (LOW/MEDIUM/HIGH/CRITICAL), and that trends and top abend codes come back. It does not mention cost or runtime, which for a 30-day look-back scan would be useful.

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 purpose, then the return contract. No filler, no repetition of parameter details already in the schema.

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, the description correctly enumerates what comes back (risk levels, trends, top abend codes), and the three optional parameters are fully documented in-schema. The only real gap is routing guidance against the several failure-analysis siblings, which the description leaves unaddressed.

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 coverage is 100% and each of the three parameters carries its own default and bounds documentation, so the schema does the heavy lifting. The description only indirectly touches semantics via "recurring failures," which loosely maps to minFailures but adds no new syntax or interpretation. Baseline 3 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 ("Predict batch failure risk") and scopes it to job names with recurring failures, distinguishing it implicitly from retrospective siblings like find_failed_jobs and analyze_job_failure. It also names the mechanism (recency-weighted scoring) and the outputs, so an agent knows what it produces. No sibling is named explicitly, so it stops short of a 5.

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?

There is no explicit statement of when to use this versus find_failed_jobs (historical failures) or analyze_job_failure (single-job deep dive), nor any prerequisites, cadence, or exclusion. The phrase "job names with recurring failures" implies a proactive-risk use case, but the agent must infer it.

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