Quotaline Commissions

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: it discloses the mutual-exclusivity rule for sales_total vs deals, the fallback behavior of showing both marginal and retroactive results when the plan is silent, and the returned artifacts (per-deal commission, tier breakdown, draw recovery, payable-now, PDF statement, Excel file). That is substantive behavior an agent cannot infer from structured fields.

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?

Long, but front-loaded with the trigger and the input rule, with exclusions last. The enumerated plan-feature list is somewhat dense yet each item corresponds to a real capability (tiers, draw, cap, SPIFF, clawback, OTE), so little is wasted.

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?

Given a 10-parameter nested-schema tool with an output schema, the description covers the trigger, required input combination, notable defaults (marginal vs retroactive both shown, bonuses outside cap), what is out of scope, and what is returned. Nothing an agent needs to select or call it correctly 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 coverage is 100%, so the baseline is 3. The description earns above baseline by surfacing the input-combination rule ('Give either a sales_total or the deals') and by naming the natural-language plan phrasings (e.g. "5% up to 50k then 8% above", "split commission 60/40") that map onto the tier/split parameters, adding meaning beyond per-field docs.

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 and resource ('calculate sales commission for one rep') and enumerates the plan shapes it handles (flat, tiered, quota attainment, draw, split, SPIFF, clawback, gross-margin, OTE). It explicitly contrasts itself with generate_commission_statements for team/uploaded-file cases, so an agent can distinguish it from siblings without opening any schema.

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?

States when to use it ('when the user wants to calculate sales commission for one rep') and when not ('Do not use for a whole team or an uploaded deals file (use generate_commission_statements)', 'Does not compute taxes or take-home pay', 'not for commission-free trading'). The exclusion plus a named alternative satisfies the highest bar.

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

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

The annotations already state that this is a read-only, idempotent, closed-world, non-destructive computation. The description usefully adds that tiers, accelerators, quota percentages and caps are applied, that results are computed in cents, and that it won't judge fairness. However, it claims "Does not handle draws", but the schema exposes draw_amount and draw_type on both plans, so it contradicts the structured data and could mislead an agent about whether draws are respected.

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?

One long but well-structured sentence with the trigger, the computed outputs and the scope limits, followed by two short exclusion sentences; it is reasonably front-loaded. A small amount of density could be trimmed, and the incorrect draws clause is wasted text, but overall there is little padding.

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 complex nested-schema tool, the description covers the purpose, the outputs and routing, and an output schema exists so return values need not be explained. But the "does not handle draws" statement conflicts with the plan schema and leaves the agent unsure whether draw parameters matter, which is a completeness gap on a non-trivial input field.

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 both the plan objects and the sales_levels/currency parameters are already well documented (defaults, examples and formats included). The description only alludes to "several sales levels" and adds no syntax or default information beyond the schema, so the baseline of 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 gives a specific verb and resource (compare two commission/comp plans) and states exactly what the output contains: payouts at several sales levels, the difference, and the crossover point. It distinguishes itself from the sibling calculate_commission by scoping itself to two plans, so an agent can separate the two without opening the schema.

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?

It includes concrete trigger phrases ("compare these two comp plans", "which plan pays more at 120% of quota"), an explicit exclusion ("Do not use for a single plan's payout"), and names the alternative (calculate_commission). This is the when-to-use / when-not-to-use / alternative pattern done properly.

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

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

With annotations already declaring readOnly/idempotent/non-destructive, the description still adds substantial behavioral context: which pay elements are handled (splits, SPIFFs, clawbacks, caps, draws), what is explicitly out of scope, and which three output artifacts are produced. This is well beyond what the annotations convey.

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?

Information is front-loaded: usage triggers first, then returned artifacts, then exclusions and sibling routing. It is dense but each sentence carries weight; the only cost is that it reads as one long paragraph rather than being segmented.

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 complex 12-parameter tool with nested plan/deal objects and an output schema, the description covers input formats, output artifacts, scope exclusions, and the correct sibling alternative. An agent has everything needed to decide and invoke 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?

Schema coverage is 100%, so the schema already documents all 12 parameters in depth. The description adds only light supplemental meaning (automatic column matching, one plan with per-rep overrides), which is honest but not needed to compensate for any gap.

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 names a specific verb and resource (generate commission statements) and states the scope (several reps, one plan applied to all). It explicitly distinguishes itself from the sibling calculate_commission, so an agent can route without opening either schema.

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?

It gives concrete triggers (multiple reps, 'how much commission did each rep earn this month', attached deals export), names the alternative for a single quick question, and lists explicit exclusions (taxes, withholding, take-home pay, PDF/image files). Nothing is left to inference.

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