The Landing Company of Madison Park

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds content scope but no additional behavioral context such as return format, permissions, or side effects; it does not contradict the annotations.

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 a single front-loaded sentence with no wasted words. It is appropriately sized for a zero-parameter informational tool.

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-only info tool, the description says what content is returned, but it omits selection guidance among sibling informational tools and gives no hint about return format. It is adequate for invocation but incomplete for confident tool selection.

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 has zero parameters and 100% schema description coverage, so there are no parameter semantics to explain. The baseline score for a no-parameter tool is 4.

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 identifies the resource as the firm's engagement process and states its end-to-end scope, from problem understanding to handoff. It is clear but does not explicitly differentiate this from siblings like get_firm_overview or get_guide.

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 guidance on when to use this tool versus get_firm_overview, get_guide, get_faq, or list_services. The agent must infer selection from the name and title alone.

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 declare read-only, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds no behavioral context beyond the content topic, such as return format, freshness, or scope limitations.

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 a single front-loaded sentence with no wasted words. It states the resource and a representative topic efficiently.

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 FAQ tool with rich annotations and no output schema, the description is largely complete: it says what the tool returns and gives an example topic. A minor gap is that it does not clarify how this differs from the guide-oriented siblings.

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 has zero parameters, so there are no parameter semantics to explain. The baseline for a parameterless tool is 4, and the description does not need to compensate for missing schema details.

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: it provides answers to common questions, and it names a concrete topic covered. It is clear what the tool does, though it does not explicitly differentiate itself from siblings like get_guide or get_firm_overview.

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 implies the tool is for common questions, but it gives no explicit guidance on when to use it instead of get_guide, get_approach, or get_firm_overview. There are no exclusions or alternative-routing instructions.

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 declare this as a read-only, idempotent, non-destructive, closed-world operation, so the safety profile is covered. The description adds the content scope but does not describe return format, permissions, or other behavioral traits beyond what the 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 description is a single, front-loaded sentence that efficiently enumerates the key topics. Every phrase contributes to clarifying the tool's scope 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?

For a zero-parameter, read-only overview tool with full annotation coverage and no output schema, the description provides enough content context for an agent to invoke it correctly. It could more explicitly state that it returns narrative firm information, but the topic list is largely 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?

The tool has zero parameters, so parameter semantics are not a concern. The schema has no fields to describe, and the description appropriately does not introduce any parameter-related information.

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 clearly identifies the resource as a firm overview and enumerates the topics covered: what the firm is, who it helps, who does the work, where it is based, and how to start. It is distinct from siblings like get_approach or get_faq, but it does not explicitly contrast itself with them.

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 lists what information the tool provides but gives no explicit guidance on when to use it versus alternatives such as get_approach, get_faq, or request_consultation. Usage is only implied by the content topics.

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 readOnly, idempotent, non-destructive, closed-world behavior, so little is left to add. The description does contribute the useful contrast that this returns the complete text rather than a summary, but says nothing about size, truncation, or failure 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?

A single clause with zero waste, and the key differentiator (full text) comes first. It reads as a fragment rather than a sentence, which is mildly under-specified rather than verbose.

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 one-parameter read tool with rich annotations and no output schema, this is close to sufficient: the agent knows the input source, the returned granularity, and the safety profile. Only edge cases such as invalid slugs or text length are unaddressed.

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%, but the single enum parameter is self-documenting with all six allowed slugs. The description adds the one thing the enum cannot: where the slug values come from, namely list_guides.

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?

Identifies the resource (one guide) and the returned scope (full text), and explicitly ties it to 'slug from list_guides', which separates it from the sibling listing tool. The verb is only implied ('read/retrieve'), which keeps it just 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?

The phrase 'by slug from list_guides' implies the workflow: list first, then fetch the full text of one entry. It never states when to prefer this over the siblings (get_approach, get_faq) or what happens with an invalid slug, so usage is inferred rather than spelled out.

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 readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds genuinely new behavioral context with no output schema present: the response contains a slug and the question each guide answers, which tells the agent exactly what payload shape to expect before fetching details.

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: the first establishes what the resource is, the second states the return shape. Nothing is repeated from the name or annotations, and the most decision-relevant fact (what you get back) is placed second but unhurried.

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-param, read-only listing tool with full annotation coverage, the description supplies the one missing piece — return content — since there is no output schema. It lacks only volume/pagination expectations (whether all guides come back in one call), a minor gap for a small curated catalog.

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 nothing for the description to clarify and it correctly does not waste text on inputs. The schema is an empty object with additionalProperties=false, consistent with the description's parameterless framing.

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 ('list_guides' → 'short practical guides the firm has written') and scopes the content to difficult technology decisions. It implicitly distinguishes itself from the sibling get_guide by saying it returns only each guide's slug and question, i.e. an index rather than full content, though it never names that sibling.

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: returning slugs and questions signals a discovery step before get_guide, but the description never says 'use this first, then call get_guide for the full guide' or set any exclusion. An agent must infer the workflow from the sibling names.

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, idempotentHint, non-destructive and closed-world behavior, so the safety profile is covered. The description adds useful context about the shape of the returned information and the optional audience scoping, though it does not discuss authentication or limits.

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 sentences, front-loaded with the core purpose and then the optional narrowing filter. Every phrase carries information and there is 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?

For a simple read-only listing tool with one optional enum parameter and rich annotations, the description covers what is returned and how filtering works. No output schema exists, but the content summary is sufficient 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 coverage is 100% and the single enum parameter is documented. The description adds meaning by mapping 'companies' to companies and engineering teams and 'local_business' to local small businesses, clarifying the enum values beyond the schema labels.

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: listing the services the firm offers, and it describes the returned content as situations it fits and what the work involves. It does not explicitly distinguish itself from sibling tools such as get_approach or get_firm_overview, but the purpose is clear.

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 optional audience filter implies when to use the narrowed form, but there is no explicit guidance on when to choose this tool over siblings like get_firm_overview or request_consultation. Usage is implied rather than stated.

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 cover the safety profile (readOnly=false, destructive=false, openWorld=true), and the description adds context they don't carry: it transmits the person's data to a third party and the outcome is an email reply within one business day, not a confirmed booking. It could go further and warn that repeated calls create separate requests (idempotent=false), but the key behavioral facts are disclosed.

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 sentences, no waste, and the core action is front-loaded ahead of the important non-booking caveat. Every clause carries information the agent needs.

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 supplies what the agent needs about the outcome (email reply within one business day, no time is held). Combined with full schema coverage and existing annotations, nothing essential to 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%, so the schema already documents every field, including the hints about what to put in problem and availability. The description merely enumerates the same fields (name, email, problem, optionally company and availability) without adding format or quality guidance. 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 and resource ("Sends The Landing Company a request for a free 30-minute call") plus the recipient (Campion Fellin) and the payload fields. It is unmistakably an outbound action rather than a lookup, so it cannot be confused with the get_*/list_* siblings, though it never names them.

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 exclusion "It does not book a time: the reply comes by email within one business day" tells the agent this is a request-submission tool, not a scheduling tool, which is exactly the confusion risk here. It stops short of naming when to prefer get_faq or get_approach instead of submitting a consultation request.

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