GENESIS Machine Decision Intelligence

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the cost and payment rail ($0.005 USDC via x402 on Base mainnet), which implies a paid, likely on-chain transaction with side effects, but it never states what "structurally validate" actually checks, whether payment is charged on failure, or what the result looks like.

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?

Two short, front-loaded sentences with no filler: the purpose first, then the price. It is efficient, though its brevity borders on under-specification rather than true economy.

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 five-parameter tool with no output schema, no annotations, and zero schema documentation, the description is far too thin. It omits what validation criteria apply, what the inputs mean, and what a caller receives, leaving the agent unable to 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 coverage is 0% across five parameters (input, budget, endpoint, candidates, required_fields), some with no type at all. The description mentions none of them, so names like "input," "budget," and "candidates" remain completely undefined.

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+resource ("Structurally validate a machine-service delivery"), which is enough to identify the operation at a high level. However, it offers no differentiation from the sibling service_verify, leaving the agent to guess which of the two validation tools applies.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives among free_diagnostic, service_verify, service_compare, or purchase_decision. The only decision aid is the price, which tells the agent the cost but not when this tool is the right choice.

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?

No annotations are present, so the description carries the full behavioral burden. It does disclose the commercial-upsell nature of the output, but says nothing about whether it mutates state, what permissions or inputs are required, response format, or rate/cost limits for a tool with three free-form parameters.

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?

Two tight sentences, front-loaded with the tool's nature before the recommendation behavior. No filler, though the brevity here comes at the cost of missing detail rather than efficient packaging.

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 annotations, no output schema, and three undocumented parameters, the description should explain what the diagnostic returns (e.g., a diagnosis plus a recommended paid service) and what inputs are expected. It only asserts a purpose, leaving the agent unable to call it with confidence.

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 0% with three parameters (machine, problem, evidence), so the description must compensate. 'Submitted machine evidence' loosely gestures at machine/evidence, but 'problem' is entirely unexplained and no format, structure, or expected content is given for any parameter.

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: it diagnoses machine evidence and recommends a paid GENESIS* service. The 'commercial routing' framing clarifies that its output is a service recommendation, which is more than a tautology of the name. However, it never contrasts itself against siblings like service_compare or purchase_decision.

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 word 'Free' strongly implies this is the entry-point step before committing to a paid service, which gives an agent an implicit when-to-use cue. But it never states when NOT to use it or which sibling (service_compare, purchase_decision) to pick instead, leaving routing to inference.

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?

No annotations are provided, so the description carries the full burden. It does disclose real behavioral context: the call costs $0.025 USDC, is paid via x402, and settles on Base mainnet — material for an agent deciding whether to invoke. Beyond that it says nothing about what the operation reads or computes, latency, idempotency, or failure modes.

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?

Two short sentences, purpose front-loaded before the payment detail. Nothing is padded or repeated, though the payment sentence is the only thing standing in for all missing operational guidance.

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?

A five-parameter, unannotated tool with no output schema and no parameter documentation needs a description that at least sketches the inputs and the decision shape. The description omits both, leaving only the pricing model; an agent cannot construct a valid call from this definition alone.

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?

Five parameters (input, budget, endpoint, candidates, required_fields) with 0% schema description coverage and untyped/empty schemas. The description mentions none of them, so an agent has no idea what 'input', 'candidates', or 'required_fields' should contain. With coverage this low the description had to compensate and does not.

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 artifact: 'produce a machine-readable purchase eligibility decision.' That is clearer than a generic name restatement, and 'purchase eligibility' is distinct from sibling names like service_verify or delivery_verify. It never explicitly contrasts itself with the free siblings, so sibling differentiation is left to inference.

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?

Only guidance is the price line, which implies this is a paid call, but there is no statement of when to use this versus free_diagnostic, service_verify, service_compare, or delivery_verify. No prerequisites, no exclusions, no ordering guidance for an agent choosing among five related tools.

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 no annotations, the description carries the full behavioral burden. It adds valuable context about payment (price, currency, network), which is beyond the schema. But it omits read-only vs mutating nature, side effects, auth requirements, and return behavior, leaving significant gaps.

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?

Two tightly written sentences, front-loaded with the purpose and followed by essential cost information. No waste, and every sentence 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 5 undocumented parameters, no annotations, and no output schema, the description is not complete enough. It provides payment and timing context but leaves an agent guessing about parameter meanings and expected outputs, making correct invocation difficult.

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 0% with 5 parameters, none described in the schema. The description only loosely references 'candidates' and indirectly 'budget' via price, but does not explain input, endpoint, required_fields, or the semantics/format of any parameter. This is a large gap for an agent to invoke correctly.

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 'Compare' and resource 'machine-service candidates', and clarifies timing with 'before purchase'. It does not distinguish itself from sibling tools like purchase_decision or service_verify, so it meets the rubric for a 4 (clear but no sibling differentiation).

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 by 'before purchase', giving a timing context. However, there are no explicit when-to-use vs alternatives, no exclusions, and no mention of sibling tools. This is the minimum viable 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?

With no annotations, the description carries the full burden, and it does add valuable operational context: a per-call cost of $0.005 USDC and the payment rail (x402 on Base mainnet). However, it says nothing about what the verification actually checks, whether the call is read-only, what happens on a failed or unreachable service, or latency/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?

Two short, front-loaded sentences with no filler; the core purpose leads and the cost follows. It is efficient, though arguably under-specified rather than wasteful.

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 5-parameter tool with no annotations and no output schema, the description is materially incomplete: it does not explain parameter roles, the shape of a verification result, or expected failure modes. The payment detail is a useful start but far from sufficient.

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?

There are 5 parameters (input, budget, endpoint, candidates, required_fields) at 0% schema description coverage, so the description must compensate and it does not. It mentions neither the meaning of 'candidates'/'required_fields' nor the units/currency of 'budget', leaving every parameter undocumented.

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 action (preflight/verify) and resource (public machine service) with a clear timing qualifier, 'before purchase'. This implicitly distinguishes it from the post-purchase sibling delivery_verify, but it never names or contrasts any sibling 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 phrase 'before purchase' gives an implied usage window and implies the tool is a gating step, but it offers no explicit when-not guidance or named alternatives (free_diagnostic, service_compare, purchase_decision). Usage must be inferred from context.

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