accsly.io VPS and accounts price comparison

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 fully covered. The description adds real value beyond that by disclosing the data source ('catalog data', i.e. cached rather than live) and enumerating the comparison dimensions, which partially substitutes for the missing output schema.

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?

Purpose is front-loaded in the first clause, but the rest is a single run-on sentence listing roughly eighteen comma-separated attributes of varying importance. It earns its place content-wise yet is hard to scan; grouping or prioritization would improve parseability.

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 carries the burden of explaining the return content, and it does so thoroughly, including the 'who wins on each' verdict. The only meaningful gap is that no alternative tools or use-case conditions are mentioned, which is captured under usage guidelines rather than completeness.

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 host_a/host_b accepting slug, domain, or exact name and locale explicitly mapping to currency. The description adds nothing about the parameters themselves, so the baseline 3 applies; the RAM-tier list refers to output content, not inputs.

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 (compare), an exact scope ('two VPS hosts'), and enumerates precisely what is compared (cheapest plan per RAM tier, median price, NVMe share, SLA, 'who wins on each'). An agent can immediately tell this apart from single-host lookups like get_vps_host or filtered lists like search_vps 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?

No statement of when to use this versus get_vps_host, search_vps, or vps_rating, and no prerequisites or exclusions. The only contextual cue is 'from catalog data', which hints at data provenance rather than selection guidance. The agent must infer that it should call this only when comparing exactly two known hosts.

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 safety is fully covered. The description adds the return-content inventory (legal entity, payment methods, price ranges, order links), which is genuinely useful, but says nothing about what happens with an unknown host, whether results are cached, or whether links are locale-bound.

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 clause is well front-loaded, but it then becomes one long run-on colon list, with near-repetition between "cheapest plan per RAM size" and "the cheapest plans with order links". Understandable, yet the structure is a wall of nouns rather than organized information.

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 carries the burden of describing the return shape and does so extensively. The remaining gap is edge-case behavior (invalid/ambiguous host, empty result), which matters for a lookup tool with a free-form string key.

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 schema itself explains slug/domain/name inputs and the locale-to-currency mapping. The description contributes no additional parameter meaning, so the baseline 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 verb-scope ("everything the catalog knows about one VPS/hosting provider") and enumerates the payload thoroughly, so it is unmistakably a single-entity detail lookup. It never names a sibling, so an agent must infer the split with search_vps/vps_rating on its own.

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 "everything ... about one provider" framing suggests it is the drill-down after a list/search, but there is no explicit when-to-use vs. compare_hosts or vps_rating, and no precondition such as needing a slug from a prior result (the schema supplies that instead).

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, closed-world behavior, so the safety profile is covered. The description adds genuine value beyond that: a data-provenance guarantee ('promo codes are never invented: only those the host publishes') and a warning that the site promotion is Russian-language text, which tells the agent how to interpret the payload.

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, front-loaded with the primary mode, then the no-host mode, then the trust caveat. No filler, though the fragment-style clauses ('Without a host: ...') read slightly telegraphic.

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 carries the burden of describing returns, and it does list the four signal categories returned. Combined with the already-documented read-only, closed-world annotations, an agent has enough to call it correctly; only the response shape/ordering of the ranking mode is left unspecified.

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%, and the description adds the key semantic the schema cannot: omitting 'host' turns this into a top-hosts ranking rather than an error. The locale→currency mapping and the host slug/domain/name forms are already documented in the schema, and 'limit' is neither explained nor needed beyond its default and bounds.

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 concrete resource — discount signals for a VPS host (site promotion text, prepayment discount computed from period prices, trial length, money-back days) — and states the second mode (ranking hosts by discount strength when no host is given). That is specific enough to tell it apart from price-oriented siblings like list_offers or compare_hosts, though no sibling is named 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?

It clearly splits the two invocation modes: supply a host for that host's discounts, omit it for the strongest-discount leaderboard. There are no explicit exclusions or pointers to alternative tools (e.g. 'use list_offers for raw pricing'), so it stops short of a 5.

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, closed-world, so the safety profile is covered. The description adds that results span multiple shops and names the returned fields, but says nothing about result volume, whether limit caps the response, or what happens when a catalog matches nothing — a meaningful gap for a listing 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 sentences, front-loaded with what the tool returns before the input formats. Dense and mostly waste-free, though the second sentence duplicates schema text that an agent would read anyway.

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 usefully enumerates returned fields, which is the right compensation. However, it omits any mention of the 50-item limit cap, default sorting, or empty-result behavior, leaving the agent without a sense of result size or ordering by default.

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 60% and the schema already documents catalog, locale (including currency mapping), and max_price. The description's catalog guidance largely restates the schema's 'Catalog URL, platform/category or platform slug' with a concrete URL example, which helps slightly, but sort and limit receive no explanation anywhere.

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 (offers of one platform/category from the accounts catalog, across shops) and enumerates what each offer carries: price, stock, seller shop, product page, buy link. That is concrete and distinguishable in substance from search_accounts, though the sibling is never named, so differentiation relies on the agent inferring 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 useful input-form guidance (URL, 'platform/category' slugs, or a platform slug), which tells the agent HOW to call it but not WHEN to choose it over search_accounts or compare_hosts. No exclusions or alternative-routing guidance is present, so usage is implied rather than stated.

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 safety is covered; the description adds real value by disclosing the return shape (platform categories with slugs/URLs, plus most-bought in-stock offers with price, stock, shop, product page and buy link). It does not discuss pagination or result ranking beyond 'most bought in-stock', which keeps it 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?

Two sentences, front-loaded with what the tool searches, then the return payload. The second sentence is long and packs a lot of lists, but every element (field names, sibling pointer) carries information the agent needs.

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 compensates by spelling out the return contents, and 83% schema coverage handles the six parameters. What is missing is only minor: result ordering/count semantics and how limit interacts with the returned platforms.

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 83%, and the locale currency mapping and query/platform/category meanings are all documented in the schema itself. The description adds no syntax or format detail for limit, max_price, or query beyond what is already there, so baseline 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?

States a specific verb and resource ('Search the catalog of ready-made accounts'), names the domain (Telegram, TikTok, Gmail, Steam, ChatGPT and 70+ platforms) and scopes it to comparison across independent shops. It also implicitly separates itself from list_offers, so the agent can pick between them without opening schemas.

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 '(list_offers sorts one platform or category by price)' gives an explicit alternative and the condition that selects it, and the platform param note 'from earlier results' hints at the follow-up flow. There is no explicit when-not guidance, but the routing to the sibling 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 already declare readOnly/idempotent/non-destructive, so the bar is lower, and the description goes beyond them: 10 results per page, default price-ascending order, per-plan payload contents, and that prices are scraped from host sites and refreshed hourly. Only pagination limits and total-count behavior are left unstated.

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 dense sentences, front-loaded with capability then result shape then data freshness; nothing is redundant. The filter list is long but each item maps to a real argument, so it earns its space.

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 23-parameter, no-required-args search tool with no output schema, the description still covers return fields (specs, price, payment methods, host page, order link), page size and sort default. Remaining gaps (total result count, max page depth of 500 is only in schema) are minor.

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 87%, so parameter meaning is already largely documented in the schema; the description merely enumerates a subset of filters (country, RAM/CPU/disk minimums, disk type, budget, payment method, hourly, task presets) without adding syntax or interaction rules. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ("Find VPS/VDS... plans") plus the scope (2,000+ hosts) and the dimensions it can be searched on. It's clearly distinguishable from siblings like compare_hosts or get_vps_host, though it never names an alternative 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?

Usage is implied through the filter catalog and the note that results come back "cheapest first by default", but there is no explicit when-to-use, when-not, or routing to siblings such as compare_hosts or list_offers. An agent can infer this is the discovery tool but gets no stated boundaries.

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 real context beyond that: the score is computed from catalog signals (price per resource, entry price, trust, terms, tech, reach) and the response includes plans count and entry price. It doesn't discuss pagination or whether hosts outside the top N are omitted.

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 dense, front-loaded sentence that leads with what the tool returns and then moves to the category switch. The long parenthetical category list is information-dense rather than wasteful, though the sentence is packed enough to be slightly hard to scan.

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 read-only three-parameter ranking tool with no output schema, the definition says what is scored, how, what fields come back, and how category and empty-string behave. The only gap, the limit maximum, is already enforced in the schema.

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 33% schema coverage, only locale is documented in the schema. The description carries the category semantics very well, spelling out ambiguous values ('abroad (ru only)', 'crypto (not on ru)', 'vpn (corporate VPN)') but says nothing about locale or the limit cap of 25. It compensates for the hardest parameter but leaves two of three thin.

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 precisely what is returned: a ranked top list of VPS hosts from the accsly.io rating, with a 0-10 score, plans count and entry price. It implicitly separates itself from search_vps/get_vps_host by being a ranked-by-score list, but never names those siblings. The purpose is clear and specific even without explicit sibling routing.

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?

Explains the category narrowing and that an empty category yields the overall rating, which is genuine usage guidance for the main selection decision. However, it gives no direction on when to prefer this over search_vps or compare_hosts, so the agent must infer the boundary from the ranking framing alone.

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