RentServers.com

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds domain context (which providers, which effective dates, that renewal rules and stay-vs-switch guidance are included) but does not describe output shape or how results are ordered/limited.

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?

Front-loaded with the providers and effective dates, then closes with the actionable next step. The parenthetical date lists make the opening sentence dense, but nothing is redundant filler.

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, the description should carry more of the return-value burden; it hints that SKU ids are returned and mentions renewal rules and stay-vs-switch content, but never describes the result structure or optionality of the two params (0 required). Adequate but incomplete.

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%: the 'sku' parameter is documented with examples and 'provider' has an enum, so the schema does most of the work. The description reinforces that results are keyed by SKU and enumerates the two providers, which mildly adds meaning but no format or defaulting detail.

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 the specific resource (2026 provider price changes by SKU), the covered providers (Hetzner, OVHcloud) and the exact effective dates, which is far more concrete than the opaque tool name 'audit_...'. It does not explicitly distinguish itself from the sibling get_server_price_index, but the scope is clear enough to select it.

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 gives one routing instruction — use the returned SKU ids with calculate_36_month_tco — which is genuinely useful follow-up guidance. However, it never says when to use this tool versus get_server_price_index or request_blind_counter_quotes, so usage is only implied.

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 cover safety (readOnlyHint=true, openWorldHint=false), so the bar is lower, and the description still adds real behavior: an assumed yearly price rise is applied, and 'anything not stated is flagged and counted as $0' tells the agent how missing inputs are treated. It does not describe the return shape or the units of the result, but for a read-only calculator this is solid added context.

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?

Front-loaded with purpose in the first clause, and every sentence adds information - the mode selection and the $0 default rule are not filler. The second sentence is a dense run-on with nested parentheticals and braces that hurts scanability somewhat, 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?

The tool has 11 parameters, a nested scorecard object with no inline schema, and no output schema, yet the description never says what is returned (a single TCO figure, a per-quote breakdown, a comparison table?). The scorecard shape is described in prose and deferred to an external URL, leaving the agent to guess required fields. Adequate but with a clear gap for a scoring 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 only 18% across 11 parameters, so the description carries most of the burden and largely succeeds: it explains incumbent_sku's id format with examples (ovh-advance-2-2026), the role incumbent|bid choice, and the scorecard sub-fields (units, pricing base/unit/gpusPerUnit/promo, setupFeePerUnit, extraIPv4, egress, sla, deliveryDays). Several parameters (annual_escalation_pct, ipv4_monthly_each_usd, overage_usd_per_tb, included_tb_per_server) are only inferable from their names.

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: 'Normalizes server costs over 36 months', then enumerates exactly which cost components are folded in (rent, setup fees, extra IPv4, egress overage, add-ons). It also names the upstream sibling audit_2026_provider_repricing as the source of incumbent_sku ids. It does not differentiate itself from get_server_price_index or request_blind_counter_quotes, so it stops 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?

Gives an explicit either/or routing rule: pass incumbent_sku with quantity, or pass a full scorecard to compare multiple quotes. That is genuine when-to-use guidance. There are no when-not conditions, prerequisites, or explicit sibling alternatives beyond the incumbent_sku provenance note.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that figures are 'current, dated' and sourced from published quote medians, but says nothing about refresh cadence, the date range covered, staleness, or licensing/provenance limits on the numbers.

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 purpose statement is front-loaded in the opening clause and the category detail is delivered as a tight parallel list. It is information-dense and earns its length, though the middle inventory of SKUs and tiers is slightly crowded for a single sentence.

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, the description does the work of describing the return content, and with all three parameters optional at full schema coverage there is little else required. The remaining gap is freshness semantics — 'dated' implies timestamps but no window or update frequency is stated.

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% and the descriptions for model, region, and category are already explicit, including enumerations and defaults ('Defaults to gpu, or dedicated when model is a server SKU'). The prose largely restates the category breakdown rather than adding format, unit, or interaction details beyond the schema, so the baseline of 3 applies.

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 (rental price benchmarks) and then enumerates exactly what it returns per category: GPU on-demand/reserved medians, dedicated entry floors and SKU prices, VPS cheapest and median by size. That level of specificity lets an agent distinguish it from audit_2026_provider_repricing, calculate_36_month_tco, and request_blind_counter_quotes without opening any 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?

Usage is implied by the content inventory (look up benchmark pricing rather than model TCO or solicit new quotes), but the description never states when to choose this tool over calculate_36_month_tco or request_blind_counter_quotes. No prerequisites, exclusions, or routing conditions are given.

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?

Despite annotations covering the write/safety profile (readOnlyHint=false, openWorldHint=true), the description adds meaningful workflow context: 3+ blind bids, a single 36-month normalization of replies, and a confirmation-link gate before any provider is contacted. It also discloses the fallback path to list prices for small single-VPS requests, which is real behavior no annotation conveys.

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 tight sentences: purpose and mechanism first, then gating conditions, then the exclusion rule. Front-loaded and every clause earns its place with no redundancy against the schema or annotations.

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 16-parameter request tool with no output schema, the description covers the workflow and call conditions well but leaves the parameter set largely undocumented. The agent can decide whether to call it, but assembling a valid 16-field payload relies almost entirely on raw schema rather than description guidance.

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 only 6% across 16 parameters, so the description must carry the burden but largely does not. It obliquely touches monthly_budget_usd (the $100/mo threshold) and category/quantity (single VPS), but leaves required fields like work_email, region, category, and the many optional GPU/incumbent/term fields unexplained beyond their enum values.

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-resource pair ('Opens a counter-quote request with the RentServers.com desk') and immediately describes the distinctive mechanism (3+ providers bidding blind, quotes normalized to a 36-month basis). This clearly separates it from sibling tools like calculate_36_month_tco and get_server_price_index.

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?

Gives an explicit when-to-use condition ('Only call this when the user asks for quotes and provides their work email') plus explicit disqualifying conditions (under $100/mo or a single VPS get self-serve list prices instead). The agent knows both when to call and when not to.

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