UK Electricity Price Slots MCP

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

With no annotations, the description carries the full burden; it does disclose real behavioral facts — PRO/subscriber gating, half-hourly granularity, and the today/tomorrow time horizon — which are genuinely useful. It does not say whether tomorrow's prices are always available, what the units are, whether results are ordered, or anything about rate limits or pagination.

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 tier marker, resource, granularity, time window, and scoping key all appear immediately. Nothing in it is redundant with the schema.

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 is simple and read-only, and the description covers data type, granularity, time range, and region scoping. But with no output schema and no annotations, an agent still lacks the return shape (list of slots with timestamps and prices?), units, and ordering, which is a meaningful gap for the primary data-fetch tool.

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 both parameters are already documented in the schema, and the description only echoes that the postcode determines the region. No additional syntax, format, or token-handling guidance is added beyond the schema baseline.

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 resource (half-hourly import prices), scope (all published, today/tomorrow, postcode region), which lets an agent distinguish it from siblings like cheapest_slots or daily_average that return subsets or aggregates. Sibling names are never mentioned explicitly, so the contrast is inferred from 'All published' rather than stated.

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: 'All published' suggests using this when the full price curve is needed rather than a filtered/derived view, but the description never says when to prefer cheapest_slots, best_window, or daily_average. The 'PRO.' prefix hints at an entitlement gate but does not spell out what happens without it.

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 are provided, so the description carries the burden. It discloses that the operation is a price query returning an average price and computed cost, and 'PRO' plus the access_token parameter signal a subscription gate, but it does not state that this is read-only/no-side-effect, how ties or insufficient future prices are handled, or the currency/timezone of prices.

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 sentence that front-loads the core behavior ('Cheapest continuous window of N hours in the upcoming prices'), followed by use cases and outputs. The unexplained 'PRO.' and long parenthetical cost some efficiency but nothing is redundant.

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 annotations and no output schema, the description must cover behavior and returns; it only partially does, mentioning average price and cost but omitting price units/currency, time window semantics (does it include the current hour?), and what happens when no full N-hour window exists.

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 50%: postcode and access_token are documented in the schema, while hours and kwh are not. The description partially compensates by tying 'N hours' to the hours parameter and 'cost for a kWh amount' to kwh, but adds no units, defaults, or constraints for either.

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: finds the cheapest continuous N-hour window in upcoming prices, which distinguishes it from the slot-based sibling cheapest_slots. However, the 'PRO.' prefix is unexplained and the description never names which sibling to pick instead.

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 parenthetical use cases (EV charging, heat pumps, batteries, industrial jobs) imply when the tool is useful, but there is no explicit guidance on when to use this versus cheapest_slots or all_slots, and no stated prerequisites beyond the implicit token requirement.

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 usefully discloses that the data is FREE and priced in p/kWh inc VAT under Agile Octopus, but it does not define the 'upcoming' horizon, update cadence, or behavior when no slots are available.

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 definition is a single, front-loaded sentence with the key cost signal 'FREE' first. Every element earns its place by specifying tariff, unit, VAT inclusion, count, and region scope.

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 one-parameter read tool with no output schema, the description supplies enough context to invoke it correctly. It could be more complete by specifying the return fields or the time horizon for 'upcoming', but the core invocation requirements are clear.

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 100%, so the single postcode parameter is already documented as setting the electricity region. The description reinforces that the postcode determines region, but adds no syntax or format detail beyond the schema.

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 resource and scope: the cheapest 3 upcoming half-hour electricity slots for a UK postcode region. It implicitly distinguishes itself from siblings like all_slots and daily_average by returning only the cheapest upcoming slots, but it does not explicitly name alternatives.

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: call this when you want the cheapest imminent half-hour slots rather than all slots or averages. However, there is no explicit guidance on when to choose this over best_window, all_slots, daily_average, or export_rates.

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 add some behavioral context: 'PRO' signals subscriber-tier access and 'max 30' bounds the lookback window. However, it does not explicitly confirm read-only behavior, mention rate limits, or describe return units, leaving meaningful gaps.

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 tightly packed sentence, front-loads the core resource and aggregation, and includes only the useful 'PRO' marker and max-days constraint. There is no wasted text.

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 no-output-schema tool, the description explains the returned aggregates but not the exact return shape, price units, time zone, or behavior when the optional days parameter is omitted. These are modest but real completeness 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 coverage is 67%: postcode and access_token are already documented in the schema, while the description adds crucial meaning for the undocumented days parameter via 'last N days (max 30)'. That extra constraint meaningfully improves parameter understanding beyond the schema.

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 resource (Agile import price) and aggregation (daily average/min/max) over a defined range (last N days), which is clearly distinct from slot-level or window-finding siblings. Sibling differentiation is implicit rather than explicit, so it falls 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?

It provides a use context ('for budgeting and tariff comparison') but does not state when to choose this tool over all_slots, cheapest_slots, best_window, or export_rates. The usage guidance is therefore implied rather than explicit.

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 burden; it implies a read-only lookup but never says so. It discloses no time horizon, number of slots returned, price units, rate limits, or auth error behavior for a paid-tier endpoint.

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 waste. The 'PRO.' fragment is efficient shorthand for tier gating, though slightly opaque.

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 and no annotations, the description should explain what comes back (slot list, price unit, window length) and how this differs from all_slots or best_window. It leaves an agent unable to predict the response shape for a data-returning pricing tool.

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 100%, with postcode and access_token both documented inline, so the baseline is 3. The description adds nothing about how postcode affects region or how the subscriber token is obtained.

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 resource (Agile Outgoing export prices) and scope (best upcoming slots to sell solar/battery power), which distinguishes it from cheapest_slots and daily_average well enough. The 'PRO.' prefix implies a paid tier but is otherwise cryptic.

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 guidance on when to use this versus siblings like best_window, cheapest_slots, or all_slots, and no stated prerequisites beyond the token being mentioned in the schema. The agent must infer selection from the tool name alone.

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