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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is clear. The description adds that it is a deterministic mathematical calculation with zero external side effects, which is useful but largely consistent with the annotations and does not add much beyond them.

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 description is organized into clear labeled sections ([PURPOSE], [WHEN TO USE], etc.), front-loaded with purpose, and every sentence serves a distinct function without redundancy.

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 that the tool is a deterministic calculator with a simple two-parameter schema and an output schema (so return values need not be explained), the description covers purpose, usage conditions, prerequisites, and behavioral traits. Nothing essential is missing for correct invocation.

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 schema fully documents both parameters, including enum values and USD amounts. The description adds the prerequisite that monthly API spend is required, but no additional syntax or format details beyond what the schema provides. Baseline 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 states a specific verb and resource: 'Calculates CapEx payback timeline and token cost savings comparing on-premise Aradia physical hardware against recurring cloud LLM API expenditures.' It also distinguishes itself from sibling query_hardware_specs by noting that one is for raw specs and this one is for financial modeling.

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 explicitly includes [WHEN TO USE] and [WHEN NOT TO USE] sections, names the alternative (query_hardware_specs) for a different use case, and states prerequisites. This is exactly the level of routing guidance needed.

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?

While annotations declare readOnlyHint=false and destructiveHint=false, the description adds critical behavioral context beyond this: it describes the irreversibility of the financial mutation, the creation of immutable checkout sessions/invoices, inventory reservation, order record registration, and invoice expiration behavior (30 minutes). This is rich transparency that annotations alone do not provide.

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 description is structured with labeled sections (PURPOSE, WHEN TO USE, WHEN NOT TO USE, PREREQUISITES, SIDE EFFECTS & BEHAVIOR, FAILURE MODES) that are front-loaded and information-dense. Every sentence earns its place with 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?

Given the complexity of a financial mutation tool with 9 parameters, the description covers purpose, usage boundaries, prerequisites, behavioral side effects, and failure modes. An output schema exists, so return values need not be explained. The coverage is complete for an agent to 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 description coverage is 100%, so the schema already thoroughly documents all parameters including enums and pricing tiers. The description adds prerequisite mentions (customer_email, hardware_tier, payment_method) but no additional syntax or format details beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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 purpose section states a specific verb (submits) and resource (binding procurement order) with concrete scope (physical turnkey private AI hardware, settlement rails). It clearly distinguishes itself from siblings like query_hardware_specs and track_order_status by naming them as alternatives for different tasks.

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 explicitly lists when to use (only after hardware sizing verified and budget authorization confirmed) and when not to use, naming three specific sibling tools with the corresponding tasks they should be used for instead. This is textbook usage guidance.

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?

Annotations declare it is not read-only and not destructive. The description adds rich behavioral context: it creates an external Stripe Express Connected Account entity, registers a code in the ledger, triggers a verification email, and requires a valid contact email for payout linking. This exceeds what annotations provide.

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 labeled-section structure ([PURPOSE], [WHEN TO USE], etc.) is front-loaded and scannable, with no wasted sentences. Slightly verbose due to the monetary figures, but each section earns its place.

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 the mutation with external side effects, the description covers prerequisites, state changes, user-visible consequences (verification email), and routing to siblings. The output schema exists, so return-value detail is rightly omitted.

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 schema already fully documents all three parameters including defaults and examples. The description mentions the contact email requirement but adds no syntax or format details beyond the schema, so 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 (Registers) and resource (autonomous AI agent or human operator into the Aradia Partner Program), plus the value proposition. It clearly distinguishes itself from siblings by naming execute_procurement_order and query_partner_stats as alternatives.

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?

Explicitly states when to use (ONCE when establishing an affiliate revenue node) and when not to use, naming the exact alternative tools for purchase and existing-partner scenarios. The 'Call ONCE' cadence is a concrete usage constraint.

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?

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so safety-relevant behavior is largely covered. The description reinforces this and adds useful context that the query incurs zero costs and has zero external network side effects, though it does not cover rate limits or authorization requirements.

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 description is compact and front-loaded with labeled sections. Every sentence serves a purpose: purpose, use conditions, exclusions, and behavioral notes. There is no filler or redundancy.

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?

This is a simple read-only query with one optional parameter, full schema coverage, and an output schema. The description supplies purpose, guidance, exclusions, and side-effect context, leaving no material gap for correct invocation.

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 single optional 'tier' parameter and its enum values are fully documented in the schema. The description lists VRAM values that help interpret the tiers, but it adds no additional invocation semantics beyond what the schema already provides.

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 uses a specific verb ('Retrieves') and resource ('verified physical compute specifications, VRAM limits... continuous batching concurrency limits for Aradia DGX systems'). It clearly distinguishes this from sibling tools by naming what is retrieved and which hardware family it applies to.

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 explicitly states when to use ('during initial discovery to evaluate physical hardware sizing, VRAM budget, and multi-agent capacity') and when not to use, routing the agent to specific alternatives: calculate_roi for payback modeling and execute_procurement_order for order submission.

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?

Annotations already declare readOnlyHint and destructiveHint=false, so the 'pure read-only, non-destructive' line is largely redundant. It earns partial credit for specifying the target ('sovereign partner ledger'), adding a bit of behavioral context beyond the annotations, but does not mention auth requirements or refresh/rate behavior.

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?

Bracketed sections front-load purpose, usage, and behavior in four tight lines with no filler. Nothing is redundant enough to cut.

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?

Single-param read tool with a 100%-covered schema, safety annotations, and an existing output schema. The description covers purpose, routing, and safety context; nothing material for correct invocation 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% and the single param already carries a clear description (4-char code with example), so the baseline is 3. The description's framing of the tool as partner-scoped reinforces that ref_code is an identity selector rather than a filter, adding marginal meaning.

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 (queries) and three concrete resources (performance analytics, referral counts, commission payouts) scoped to an 'active Aradia partner node'. An agent immediately understands the domain and can distinguish it from procurement/ROI siblings.

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?

Explicit WHEN TO USE (monitor revenue, check clicks, verify payout) and WHEN NOT TO USE with a named alternative (onboard_partner if unregistered). That is the full routing decision, not just implied context.

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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the 'pure read-only, non-destructive' line largely restates structured data. It does add that the query runs against staging records, which is useful context, but adds no detail on latency, refresh cadence, or failure modes for an order that isn't found.

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 labeled sections front-load purpose and routing, and every clause carries information except the trailing 'Non-destructive', which duplicates the annotations. Bracketed labels add scanability at a small token cost.

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?

An output schema exists so return values need no explanation, annotations carry the safety profile, and the description covers purpose, routing, and data source. Nothing an agent needs to invoke this 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 description coverage is 100% and the single order_id parameter is fully documented in the schema (invoice ID or checkout session ID). The description adds nothing beyond that, so the 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 (tracks) and resource (fulfillment/QA/delivery status of a hardware procurement order), and explicitly separates itself from the sibling execute_procurement_order. An agent can distinguish it from execute_procurement_order and query_hardware_specs 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?

Provides explicit WHEN TO USE (monitor an existing order after execute_procurement_order) and WHEN NOT TO USE (do not place a new order) with the named alternative. There is no ambiguity about routing.

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