AIT Advisory — Enterprise Execution Diagnostic

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

With no annotations, the description carries the full burden of behavioral disclosure, and it falls short. It does not say what the assessment returns (a pass/fail, a score, a rationale), whether it is purely read-only and side-effect free, or whether it requires any account context. Only the topic of the check is conveyed, not how it behaves.

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?

A single front-loaded sentence with zero filler; the verb and the decision it produces are stated immediately. Every word 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?

The tool has 5 parameters, four required, and no output schema or annotations, so the description must supply more than it does. It never explains the return value (the entire point of a fit assessment) or the funnel context in which the result should drive the next step. Adequate but with clear gaps.

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 80%, so the schema already documents the four boolean gates and the friction_signals enum. The description adds no parameter-level meaning (no thresholds, no guidance on which signals matter or how executive_sponsor interacts with the required fields). Baseline 3 applies when the 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 description names a specific verb (assess) and a specific judgement target (whether an organisation's execution and AI-adoption situation fits AIT Advisory's Diagnostic). It is clearly a qualification/eligibility check, distinguishable in spirit from the transactional siblings. It does not, however, explicitly differentiate itself from start_diagnostic_purchase or get_diagnostic_details, so it stops short of a 5.

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 only implied: the name and framing suggest this is a pre-qualification gate before book_executive_call or start_diagnostic_purchase. But the description never states when to call it, when not to, or which sibling it precedes. No alternatives or preconditions are named.

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. It hints that the tool returns a "route" rather than booking directly, but says nothing about whether retrieval is read-only, requires authentication, or has side effects, leaving the safety profile undefined.

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?

It is a single front-loaded sentence with no filler, but its brevity reflects under-specification rather than efficiency. The statement is too thin to stand alone as a usable definition.

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 zero-parameter tool with no output schema, the description should at least characterize the returned route. It gestures at the return value but does not say what form it takes, leaving an agent minimally informed.

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?

The tool takes zero parameters, so the schema is empty and the baseline of 4 applies. There is nothing for the description to clarify beyond what the empty schema already communicates.

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 pairs the verb "Return" with a resource, but "AIT Advisory's executive conversation booking route" is vague jargon. It is unclear whether this yields a URL, a scheduling endpoint, or a booking action, and no sibling tool is referenced for contrast.

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 indication of when to call this versus siblings like get_ait_offerings or start_diagnostic_purchase, nor any prerequisite or exclusion. The agent must guess at the triggering condition.

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 bears the full burden. It implies a safe, static read by saying it 'returns' data, and it names the payload contents. It does not state whether the data is static or refreshed, whether auth is required, or how large the result is, so gaps remain.

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?

A single front-loaded sentence with no filler. Every word ('complete offer ladder', 'canonical public URLs') carries meaning about the payload.

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 zero-argument read tool with no output schema, the description is adequate but thin: it does not describe the shape of the offer ladder or what the canonical URLs point to, so the agent cannot anticipate the response structure.

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?

The tool takes zero parameters, which is the baseline-4 case. There is nothing for the description to clarify, and the empty schema is unambiguous.

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 (Return) and a specific resource (AIT Advisory's complete offer ladder and canonical public URLs). An agent immediately understands the payload. It does not, however, differentiate itself from siblings such as get_diagnostic_details, which also appear to return catalog-style data.

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 gives no indication of when to call this versus assess_company_fit, get_diagnostic_details, or start_diagnostic_purchase, nor any prerequisites. Usage must be inferred purely from the name and the returned artifact.

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 disclose the returned content set including 'next step', which is useful behavioral context. However, it says nothing about permissions, whether the data is cached or live, rate limits, or how 'authoritative' is sourced, leaving meaningful gaps for a tool with zero annotation coverage.

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?

A single front-loaded sentence with no filler — the verb and the full list of returned fields appear immediately, and every word 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?

For a zero-parameter read tool with no output schema, the description must stand in for the return contract, and it does so by enumerating price, duration, scope, outputs and next step. It falls just short of complete because it omits any note on data freshness, permissions, or intended call sequence relative to the purchase sibling.

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?

The tool takes zero parameters, so the baseline is 4; there is no parameter semantics to clarify and the description does not need to compensate for any schema 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 gives a specific verb ('Return') and enumerates the resource contents (price, duration, scope, outputs, next step), so an agent knows exactly what it gets back. It is distinguishable from the purchase-oriented sibling start_diagnostic_purchase, but it never names or contrasts a 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?

There is no when-to-use guidance, no prerequisites, and no mention of when to prefer this over start_diagnostic_purchase or the other siblings. Usage is only weakly implied by the fact that it exposes pricing and scope, presumably ahead of a purchase decision.

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, so the description carries the full behavioral burden. "Return" hints at a read, but the name suggests starting a transaction, and the description says nothing about side effects, whether a purchase is actually initiated, permissions, or what happens after selection.

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?

A single compact sentence with the options front-loaded and no filler. The phrasing "speak first" is slightly informal but maps cleanly to the enum.

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?

No output schema and no annotations, and with a name/verb mismatch the agent cannot tell whether this initiates a purchase or returns informational options. That unresolved ambiguity is a significant completeness gap for a tool whose output shape is undeclared.

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%, so the description must compensate. It does map the three enum values to human terms (card, invoice, speak first vs. book_first), which helps, but it never names the parameter, explains the default of "card", or says what differing values change.

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?

"Return approved ways to purchase the Diagnostic" gives a verb+resource, and the three options (card, invoice, speak first) mirror the enum. But the tool name "start_diagnostic_purchase" implies initiating a purchase while the description's verb "Return" implies merely listing options; this tension leaves the core action ambiguous.

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?

No when-to-use guidance, prerequisites, or routing to alternatives. With siblings like get_diagnostic_details and book_executive_call in scope, an agent gets no signal on when this tool is the right choice versus those.

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