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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered; the description adds real value beyond that by disclosing its data sources (Eurostat, ECB exchange rate, four studies) and its failure mode: inputs lacking a public source are listed rather than assumed. It also clearly bounds the funding-call output (no amounts, no open/closed status).

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?

Four sentences, front-loaded with what the tool produces; the sourcing and missing-input caveats are dense but each sentence carries substantive information. Slightly overlong but no filler.

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?

For a 14-parameter, nested-object, no-output-schema tool, the description does a good job describing the shape of the result (costs shown separately, payback across three scenarios, missing inputs listed) and the data provenance. A few parameter-level gaps remain but the agent can invoke it confidently.

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 only 36% across 14 parameters, and the description compensates partially by grouping fields into conceptual buckets (external, compliance, internal staff, licences, operations) and hinting at study-driven savings and own_savings_share. It adds little meaning for individual cost parameters like internal_it_hourly_cost_eur, maintenance_eur_per_month, or the model_usage tier values.

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 ('Estimates the costs of introducing AI') and enumerates the outputs it produces: external costs, internal staff time, licences, operations, and a payback period in three savings scenarios. It is clearly distinct from the readiness/planning siblings, though it never names an alternative tool explicitly.

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 when the tool is appropriate (cost/payback analysis) and explains data-handling behavior, but gives no explicit when-to-use versus when-not-to-use guidance relative to siblings like assess_ai_readiness or plan_ai_rollout. Usage must be inferred.

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