Australia NEM Electricity Prices MCP

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

No annotations are provided, so the description carries the full disclosure burden and falls short: it never explains that a subscriber token is required for access, nor anything about data freshness, geographic scope (FuelWatch is WA-only), or rate limits. 'PRO' implies gating but is 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?

Two short fragments with no filler, and the output content is front-loaded. However, 'PRO.' as an unexplained opener spends a word on something cryptic rather than useful, and the extreme brevity leaves real gaps.

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 return shape, units, and scope, but does none of that. For a tool whose entire value is aggregated statistics, not saying what fields come back or over what region/timeframe leaves an agent guessing.

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 access_token parameter is fully documented in the schema, so the description need not repeat it. Baseline 3 applies; the description adds no extra meaning about the token or fallback behavior.

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 and aggregation: average/min/max ULP prices grouped by brand, sourced from FuelWatch. That distinguishes it from siblings like cheapest_fuel (minimum only) and nem_prices (different dataset). It is terse and verb-less, but the payload is unambiguous.

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 pick this over cheapest_fuel or fuel_search, no mention of required inputs or data scope. The only hint is the 'PRO' prefix, which suggests a paid tier but never states a condition for use.

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 exist, so the description carries the full burden, and it does disclose the data source and fixed product (ULP, product 1) and that the result set is capped at five. It says nothing about data freshness, whether station name/address/price are included, or geographic extent beyond 'WA'—gaps that matter for a no-schema tool.

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 fragments, front-loaded with the cost signal ('FREE') and the core scope. Very little waste, though 'FREE' is a bit cryptic without saying free relative to what.

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, no-output-schema tool, the description gives source, product, record count, and region—enough to call correctly. What a returned record contains and how stale the data can be are left unstated.

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?

Zero parameters, so the baseline is 4; the description's mention of 'product 1' usefully signals that the fuel product is hard-coded rather than caller-selectable, which is the only parameter-like information relevant here.

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?

Names a specific resource (ULP stations) plus a precise scope (five cheapest, sourced from WA FuelWatch, product 1), so the agent knows exactly what comes back. It is distinguishable from siblings like fuel_search or brand_prices by the 'five cheapest' framing, though it never explicitly contrasts 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?

Usage is only implied: the 'five cheapest'/'FREE' framing suggests a quick, no-cost lookup when the user wants the lowest price rather than a search or brand breakdown. There is no explicit when-to-use, when-not-to-use, or named alternative among the siblings.

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 bears the full burden, and it discloses almost nothing: 'PRO' hints at a premium/subscriber tier but is never explained, and there is no mention of auth requirements, rate limits, pagination, or result ordering. With zero annotation coverage, the absence of any behavioral detail beyond the parameter mapping is a real gap.

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?

One front-loaded sentence that puts the resource and the product-code mapping first, with no filler. The leading 'PRO.' token is unexplained overhead, but it is the only wasted fragment.

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?

A tool with no annotations, no output schema, and an undocumented access_token/required-parameter situation needs more: the description never says whether the token is mandatory, what fields a result row contains, or how many results to expect. For a paid-tier listing endpoint, that leaves the agent guessing about invocation prerequisites.

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 only 33%, so the description has to compensate, and it largely does for the most important parameter: the product code enum (1=ULP, 2=PULP, 4=Diesel, 5=LPG, 6=98RON, 10=E85) exists nowhere in the schema. It also clarifies that suburb is a free-text keyword filter, though it says nothing about whether matching is partial or how the two filters combine.

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?

Names a specific resource (FuelWatch price list) and the key selection dimension (product code, with the full code mapping supplied inline). The 'list' framing plus optional suburb also separates it from siblings like cheapest_fuel or brand_prices, though it never says so explicitly.

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 / when-not-to-use guidance and no named alternative, even though four sibling tools (cheapest_fuel, brand_prices, region, nem_prices) offer adjacent capabilities. An agent must infer from the verb that this is the general listing tool.

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 full behavioral burden. It does not state whether the call is read-only, what authentication is required (the access_token parameter hints at a subscriber token but the description never mentions it), what the summary table contains, or how results are returned.

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 only two short fragments, so it is concise. However, the leading 'PRO.' is cryptic and does not front-load useful information, making the structure less effective than it could be.

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 has a simple one-parameter schema and no output schema, but the description is too sparse to compensate. It does not explain what the summary table includes, whether the endpoint is premium-only, or what an agent should expect to receive, leaving significant gaps for a data-retrieval 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?

There is one optional parameter (access_token) and schema description coverage is 100%, so the schema already documents it fully. The description adds no parameter-level meaning, which meets the baseline 3 for high schema coverage.

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, the 'Full AEMO NEM summary table', and the word 'Full' implies broader scope than a prices-only sibling like nem_prices. However, the cryptic 'PRO.' prefix is unexplained and there is no explicit verb, so the purpose is clear but not fully polished.

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 nem_all versus siblings such as nem_prices, region, or fuel_search. An agent must infer the choice from the name and description alone, with no stated conditions or exclusions.

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 full burden. It discloses that the tool is free and returns a current snapshot, implying a read-only, point-in-time query, but it omits auth requirements, rate limits, and whether data is cached or live.

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 phrases with zero waste. 'FREE.' is front-loaded and useful, and the rest of the sentence states the resource and scope without padding.

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, no-output-schema snapshot tool, the description gives enough to understand what comes back at a high level (current regional prices). The unexplained 'first look' is a minor gap, but nothing critical is missing for 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?

The tool takes zero parameters, so the schema places no burden on the description. Baseline 4 applies: no parameter semantics are needed or expected.

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 (NEM electricity price snapshot) and scope (by region, current). This is clear enough to distinguish from generic sibling names, though it does not explicitly contrast itself with nem_all or explain what 'first look' means.

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?

Only signals that the tool is free and offers a 'first look' snapshot. It does not say when to choose this over alternatives like nem_all or region, nor does it state any prerequisites or exclusions.

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 behavioral burden, but it discloses very little. It does not explain what 'PRO' means, whether an access token is required and how to obtain it, what the summary row contains, or any rate or permission constraints.

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 short sentence, which is efficient, but the unexplained 'PRO.' fragment and the overall terseness make it under-specified rather than genuinely concise. The useful region examples are front-loaded.

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 tool with no annotations and no output schema, the description should clarify authentication, return content, and how it relates to sibling tools like nem_prices and nem_all. It does not, leaving significant gaps an agent would need to resolve before calling it confidently.

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 50%. The access_token parameter is documented by the schema, while the region parameter is undocumented there but partially compensated for by the description's list of region IDs. The description adds some meaning for region but does not explain the access_token parameter or the required format beyond the schema's own text.

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 a 'NEM summary row' scoped to a region id and gives concrete region values, which is useful. However, it lacks a clear action verb and the cryptic 'PRO.' fragment leaves the operation partly ambiguous. It hints at being different from nem_all and nem_prices but does not explicitly distinguish itself from those siblings.

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 nem_all, nem_prices, or the fuel-related siblings. The region examples are parameter values, not usage conditions. No prerequisites or exclusions are provided.

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