Chamfer: CNC machining, molding, sheet metal and PCB RFQs; MRO parts by part number

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 fully covered by structured data. The description adds only that the payload is comprehensive in scope, without saying what happens for an unknown slug, whether an error is raised, or how large the response is. It neither contradicts nor meaningfully extends 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?

It is a single front-loaded sentence with a colon-delimited list, which is structurally sound and short. But several list items are vague ('what you get', 'any operations'), so brevity comes at the cost of specificity rather than being purely efficient.

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 is the only source of return-value information, and it does gesture at the main content categories. Against the simplicity of a one-parameter read tool with rich annotations, that is roughly adequate, but the undefined slug and absent error/edge-case behavior leave 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?

The single parameter, slug, has 0% schema description coverage, so the description carries the full burden and does not meet it — 'slug' is never explained as the service identifier, its expected format, or where to obtain it. The items listed ('request fields', 'operations') describe response content, not the input, so they do not compensate for the 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 conveys that this is a detail-lookup for a single service and enumerates the kinds of content returned (request flow, response, scope/limits, fields, operations). However, it never states an explicit verb and shifts terminology from the tool name's 'proposition' to 'service', which leaves the agent to infer that these are the same entity. The singular framing loosely implies a contrast with list_propositions, but no explicit differentiation is made.

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 at all: nothing says to call this instead of list_propositions when the agent already has a slug, and nothing mentions the sibling tools. The description also never hints at what precondition must hold (a valid slug) before calling.

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds useful framing by explaining that entries come back as one-line summaries split into two categories, but says nothing about ordering, total count, or what a caller should do with each category, which is the only behavior left unexplained.

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, and the most important disambiguation (what a "proposition" is) arrives immediately. The colon-plus-list construction is slightly dense but still parses on one read.

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 parameters, no output schema, and full annotation coverage, the only gap the description must fill is what comes back and why, and the one-line-summary plus two-category framing does that. It falls short of complete only because it never tells the caller how this listing relates to the two sibling tools.

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 document. Baseline 4 applies; the description neither adds nor omits parameter meaning because none exists.

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?

Description gives a specific verb ("List") and resource ("Chamfer's services"), and crucially disambiguates the non-obvious name "propositions" by defining it as services split into instant lookups and sendable requirements. It does not, however, distinguish the tool from the sibling describe_proposition or submit_request, so the reader must infer the boundary.

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 explicit when-to-use statement and no mention of the alternatives describe_proposition or submit_request, despite them being the clear next steps for the two item types named. The reader can infer this is an entry-point catalogue call, but the description never says so.

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 establish a non-idempotent write to a closed-world system, so the bar is lower. The single added behavioral fact, "It is kept with a reference number," is genuinely useful because there is no output schema and it tells the agent what to expect back. It says nothing about validation failures, duplicate submissions (non-idempotent but no de-duplication guidance), or that contact data is stored separately and purged after 180 days, which is the kind of side effect an agent should disclose before sending personal data.

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, front-loaded with the action and ending with the useful retention detail; nothing is padded. The brevity is efficient rather than bloated, though it shades into under-specification for a 10-parameter 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?

This is a mutation with ten parameters, four nested objects, an enum, and no output schema, yet the description covers only the barest outline. It omits required-field meaning (slug, need), how specifications relate to the service's request schema, and the contact-data retention policy, so the definition is not complete enough for correct invocation without reading the schema closely.

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?

With 10 parameters at only 40% schema description coverage, the description carries the burden of explaining meaning and contributes nothing about any parameter. The undocumented ones are the consequential ones: the 'action' enum, the 'requested_fields' array (max 30), the 'specifications' bag of fields drawn from the service's request schema, and the budget/timing/quantity/geography nested objects. The crucial hint that slug accepts 'anything-else' appears only in the schema, not the description.

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 and resource ("Send a requirement to one of Chamfer's services"), which is distinct from the read-oriented siblings list_propositions and describe_proposition. However, it introduces 'requirement'/'service' terminology that does not match the sibling vocabulary of 'proposition', and it never explains what a 'requirement' actually is, so the agent must infer the domain.

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 beyond the implied write action, no mention of preconditions (must the service slug exist first? is describe_proposition needed first to learn the request schema?), and no exclusions against alternatives. The agent is left to infer that this is the submission counterpart to the two read tools.

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