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

Annotations already declare readOnly/openWorld/idempotent, and the description adds meaningful behavior beyond that: it tolerates source failures ('noted, not fatal'), emits an INSUFFICIENT DATA category, and discloses data caveats (federally-aided students only, earnings lag by years). This matches and enriches the annotations; no contradiction.

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 core purpose is front-loaded, and every sentence adds substantive content: data sources, output categories, fault tolerance, caveats, and disclaimer. The only marginal phrase is 'Premium cross-source synthesis,' and the paragraph is dense but not bloated.

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?

Even without an output schema, the description itemizes the four possible verdicts, the evidence structure, and source-failure behavior. Combined with full schema documentation, an agent has enough to call and interpret the result 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?

The schema already documents all three parameters at 100% coverage, so the baseline is 3. The description adds value by explaining that naming a program adds program-level median debt and 1-year earnings, which provides semantic meaning beyond the schema's field names.

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?

Opens with a specific verb/resource: a one-call 'is this degree worth the cost' read for a US college, optionally a named program. It clearly distinguishes itself from siblings like college_search, college_compare, and college_metrics by describing a graded verdict output (STRONG VALUE / FAIR / WEAK VALUE / INSUFFICIENT DATA) and cross-source synthesis.

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 implies the use case—quick value assessment for one college—and warns 'Informational only, not admissions, financial, or career advice.' However, it never names sibling tools or states when to choose this over college_compare, college_metrics, or college_outcomes_by_program, so usage guidance is only implied, not explicit.

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