ElectricityFinder

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: exact ranking order, the tie-break rule for conditional-price plans, that links never expire, funding disclosure (PUCT BR260062), and the caveat that a null price_conditions does not rule out conditions. It also flags the paid-plan upsell surfaced inside interval_data, which an agent needs to know before relaying results.

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 lead sentence front-loads the function, and with no output schema every return-field gloss earns its place. It is still a single dense run-on paragraph with semicolon-chained clauses, which hurts scannability for a description this long.

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 a rich structured return, the description carries the full burden and does so: it defines price_conditions, efl_url, link, revisit, cheapest_any_term, utility_note, rate_type, and interval_data. Nothing an agent needs to interpret or relay a result is left 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?

Schema coverage is 100% and each parameter is already documented, so the baseline applies. The description adds the rationale for usage-over-average ('not the 1,000 kWh figure plan ads quote'), but it refers to 'term_filter' when the actual parameter is named 'term', which could send an agent looking for a field that does not exist.

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?

Opens with a specific verb and resource: 'ranks the Texas electricity plans at a ZIP code', and immediately scopes the metric ('by what each would cost over a year at the person's own monthly kWh'). This is unmistakably distinct from the only siblings, how_to_get_my_usage and send_feedback.

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?

Establishes the entry conditions (a Texas ZIP, actual monthly kWh), removes friction ('Free, no account'), and explicitly routes usage-data questions to the how_to_get_my_usage sibling. It does not state a when-not-to-use case, but with only two unrelated siblings there is little to exclude.

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=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. Beyond that, the description adds genuine value by disclosing what the guidance covers and the fallback case (one typical month, when monthly numbers suffice). It does not describe output format, but the annotations carry the behavioral burden here.

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, zero waste, and front-loaded with the concrete methods before the caveat about monthly numbers. Efficient and readable, though the phrasing is slightly dense 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?

With no parameters and no output schema, the description's job is to convey what the tool provides, and it does: methods for obtaining usage data plus a sufficiency heuristic. For a zero-param informational tool this is complete enough for an agent to invoke it 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?

The tool takes zero parameters, so per the rubric the baseline is 4. There is no parameter semantics to add or clarify, and the schema is empty and fully consistent.

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 content scope (12 months of kWh data, sources: Smart Meter Texas download, bills, or a typical month) and ties it to the sibling tool compare_texas_electricity_plans, so an agent can tell it apart. The only mild ambiguity is that it reads as content description rather than stating outright that the tool returns instructional guidance, but 'How to get...' in both name and title resolves this.

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 description gives clear context: use it in service of compare_texas_electricity_plans, and it covers the decision point of 'when monthly numbers are enough.' It does not spell out explicit exclusions or name a competing method-tool, so it falls just short of a 5, but the when-to-use context is clear.

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 cover safety (readOnlyHint=false, destructiveHint=false, idempotentHint=false), so the bar is lower. The description adds a genuinely non-annotated behavioral constraint: the message must contain the person's own words, not the conversation, and must exclude PII. It does not say whether the send is confirmed or how failure is surfaced, so it stops short of a 5.

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?

Three front-loaded sentences with no filler: what it does, when to use it, and how to populate the message. Each clause carries new information (categories, trigger, content rules).

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 moderate annotations, the description covers purpose, trigger, and content rules well. It omits any indication of what happens after sending (confirmation, delivery, retry on a non-idempotent call), which would complete the picture for an agent reporting outcome to the user.

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 baseline is 3. The description goes beyond the schema by clarifying what belongs in the required 'message' field — the person's own words about the problem rather than the surrounding conversation — a distinction the schema does not make.

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 ('Sends feedback to the people who run ElectricityFinder') and enumerates the concrete kinds of feedback it carries. The domain is unmistakably distinct from the query-oriented siblings, so an agent can select it without opening the schema.

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?

Explicit trigger given: 'It is for when the person asks to send feedback.' That is clear usage context, but there is no when-not guidance and no named alternative for cases where the user wants plan comparison or usage info.

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