Loadfactor: business electricity and gas supply, solar and EV charging quotes

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds that each entry carries a one-line summary, which is useful output context, but with no output schema the phrase 'lookups that run instantly, and requirements you can send' stays cryptic about what the two item categories actually are.

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 trailing clause about lookups and requirements is terse to the point of being opaque, but it does not waste words.

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 zero parameters and rich annotations, the main remaining burden is describing the returned list, and the description only partially does so via 'one-line summary'. It is adequate for invoking the tool but leaves the shape and categories of results underspecified.

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 disambiguate and the baseline of 4 applies. No parameter semantics are missing.

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?

Uses a clear verb ('List') and names a resource, but the resource is called 'Loadfactor's services' while the tool name and siblings use 'propositions' — an unexplained terminology shift that forces the agent to guess whether they are the same thing. It conveys that the result is a one-line summary per item, but does not distinguish the tool from describe_proposition.

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 explicit when-to-use or when-not-to-use guidance, and neither sibling is mentioned. The 'one-line summary' phrasing weakly implies this is an overview step before describe_proposition, but that inference is left entirely to the agent.

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 this is not read-only, not idempotent, and closed-world, so safety framing is covered. The description adds genuinely new behavior — that the submission is persisted and returns a reference number — which matters because there is no output schema. It does not address duplicate submissions (relevant given idempotentHint=false), nor retention beyond what the schema says about contact 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, with no redundant wording. The brevity works against it overall, but on this dimension the text is tight and well-ordered.

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 10-parameter, nested-object mutation tool with no output schema and sparse schema descriptions, two sentences are far from sufficient. The reference-number return value is the only extra fact supplied; the meaning of the domain fields and the expected workflow relative to the sibling tools remain unexplained.

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, nested objects, and only 40% schema description coverage, the description contributes nothing about any parameter. It never explains what need versus specifications versus requested_fields mean, how slug must map to a service, or how budget, quantity, timing, and geography interact. Six undocumented parameters rely on bare schema structure alone.

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 verb ("Send") and an object ("a requirement"), so the basic action is discernible. However, "requirement" drifts from the tool name submit_request and the title's wording, and there is no attempt to distinguish this write tool from the read-oriented siblings describe_proposition and list_propositions. An agent gets the gist but not a crisp definition of the payload concept.

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 submit versus when to call describe_proposition or list_propositions first, no mention of prerequisites such as knowing the correct slug, and no exclusions. The only implicit cue is that this sends data outward while the siblings list or describe.

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