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

With no annotations, the description carries the full burden and does well: it explicitly discloses that nothing is bought, ordered or paid, that no quote is guaranteed, and that the service is free — exactly the kind of commitment-boundary context an agent needs. It also previews the returned content (recipients, consent wording, confirmation step), adding transparency beyond a bare label.

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?

'Read first' is front-loaded as an imperative, followed by a dense but purposeful sentence covering the outcome and return contents. It is efficiently sized, though the second sentence is long and could be split for scanability.

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 parameterless informational tool with no output schema, the description sufficiently covers what the tool conveys and what it returns (recipients, consent wording, confirmation method). Nothing essential to correct invocation appears to be 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?

The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to clarify on the input side, and it correctly does not invent parameter detail.

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 the tool's function as explaining what an enquiry does on PPC agency Bristol — an information/description tool rather than a transaction. It is distinguishable from submit_enquiry (which acts) and enquiry_fields (which enumerates inputs), though the phrasing 'states plainly what submit_enquiry does' describes a sibling's behavior rather than naming the tool's own output directly.

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 opening 'Read first' is an implicit sequencing instruction telling the agent to consult this before submitting, which is genuine usage guidance. However, it never names enquiry_fields or submit_enquiry as alternatives or states when this tool is unnecessary, leaving the 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?

With no annotations and no output schema, the description carries the full burden and does so reasonably well by enumerating the exact payload it returns (key, label, type, required, help text, options). It discloses the data model the caller needs. It does not state that this is a safe read-only lookup or mention any auth/rate constraints, but for a zero-parameter definition fetch the omissions are minor.

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 with essentially no waste; the resource is front-loaded and the follow-up instruction is compact. The first sentence is a dense comma list, which slightly reduces readability, but every clause carries information.

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 definition tool with no output schema and no annotations, the description supplies both the returned field shape and the workflow link to submit_enquiry. Nothing critical to correct invocation is missing, though a note on read-only behaviour and the enquiry_describe distinction would make it fully complete.

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 there is nothing for the description to compensate for; baseline 4 applies. The closing sentence about keying answers by field key explains how this tool's output feeds a sibling, which adds useful meaning without inventing parameter detail.

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 the exact resource (every field of the PPC agency Bristol enquiry) and enumerates the returned attributes: key, label, type, required, help text, allowed options. It is not a verb+resource phrasing, but an agent can immediately tell this is a field-definition lookup. It references submit_enquiry as the consumer but never distinguishes itself from enquiry_describe, so sibling differentiation is only partial.

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?

'Pass answers to submit_enquiry keyed by field key' establishes the downstream workflow and implies this tool is called before submission. However, there is no explicit when-to-use statement relative to enquiry_describe, and no exclusions or prerequisites are given. 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?

With no annotations, the description carries the full burden and does so well: it discloses that step 1 only validates and returns a summary/consent line/token, that nothing is submitted until step 2, and that the person must click an emailed link before any provider sees the enquiry. It also spells out exactly what consent means, which is the key behavioral constraint.

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?

Front-loads the crucial "not a purchase" framing and then uses clean Step 1 / Step 2 structure. It is fairly long and repeats the consent sentence that also appears in the schema, but that repetition is defensible because the agent must display it verbatim to the person.

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?

There is no output schema, so the description correctly explains what each call returns (summary, consent line, confirmation token) and what happens downstream (email with a click-through link). For a two-phase, nested-object tool with no annotations, this is complete enough 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 coverage is 100%, so the baseline is 3, but the description adds real meaning: answers are keyed by field key from enquiry_fields, consent=true is a hard requirement tied to the quoted statement, and confirmation is explicitly the token returned from step 1 after approval. This clarifies when each parameter is valid across the two calls.

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 ("Submits an enquiry to PPC agency Bristol") and immediately scopes it with "NOT a purchase, NOT a guaranteed quote," which prevents the most likely misclassification. It is clearly distinguishable from the sibling read-only helpers enquiry_describe and enquiry_fields.

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?

Gives an explicit ordered protocol: step 1 with answers + consent=true, then step 2 only "if the person agrees" with the same answers plus the confirmation token. The gating condition and the alternative (do not proceed) are both stated rather than inferred.

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