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

Annotations already declare a safe, read-only, idempotent, closed-world calculation, so the safety bar is low. The description goes well beyond that by disclosing the exact regulatory model applied (2026 monthly cumulative brackets, minimum-wage exemption, 7.5× minimum-wage SGK cap, BES and employer incentive handling) and what the response contains (itemised items, effective and marginal rates, employer cost, step-by-step workings). It stops short of stating rounding conventions or the currency/FX caveat for euro amounts.

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 in the first clause, followed by a colon-delimited list of covered rules that stays information-dense. The single-sentence block with nested colon and semicolons is slightly harder to scan than a few short sentences, but almost every clause carries substantive content.

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 takes on the job of explaining the return value, and it does so thoroughly: itemised taxes with local names, effective and marginal rates, employer cost, and step-by-step workings. Combined with the stated rule coverage, an agent has enough to call this correctly and to know what to expect back.

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 baseline is 3. The description adds contextual meaning for two optional inputs, noting that BES is a private pension item and that employer SGK varies with or without the incentive, but it does not explain how bonus_annual or fx_per_eur interact with the calculation beyond what the schema already says.

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 opens with a precise verb-and-resource statement: take-home pay from a gross yearly salary in TRY under 2026 rules. It also distinguishes itself implicitly from siblings by stating the direction of the calculation (gross in, net out), the opposite of gross_for_target_net, and by covering the tax/contribution breakdown rather than just a single figure.

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?

Usage is implied rather than stated: an agent can infer this is the tool for converting gross to net. There is no explicit 'use this instead of gross_for_target_net when...' routing, and no note that it also reports employer cost, which overlaps with the employer_cost sibling and could cause ambiguous selection between the two.

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