RBX Invest Roblox Limiteds market data

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

With no annotations or output schema, the description carries the full burden and does substantial work: it discloses the return components (meaning, how it is worked out, analogy, caveat), the scope of coverage, and the non-advice framing. It does not mention permissions, rate limits, or error behavior, but those are low-risk for a read-only glossary lookup.

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 and scope are front-loaded in the opening clause, and the query behavior follows immediately. The long parenthetical enumeration of terms is dense but earns its place by communicating coverage; otherwise the description is efficient.

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 lookup with a fully documented schema and no output schema, the description supplies enough: what the tool covers, what it returns, how to invoke it, and a clear non-advice caveat. The remaining gap is not naming sibling alternatives, which is minor at this complexity.

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 the single optional query parameter is already fully documented in the schema, including examples and the omit-for-index behavior. The description adds the phrasing 'words of the question' and repeats the omit instruction, but does not introduce syntax or format detail beyond the schema, 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 resource — the glossary of every figure, column, label, and badge on rbxinvest.com — and specifies what it returns: plain-word meaning, derivation, analogy, and caveat. That is far more precise than a restated title and clearly distinguishes it from guide-style or article-search 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?

It gives explicit invocation guidance: pass the words of the question as query, or omit it to get the list of terms by page. It also draws a scope boundary by stating the tool is not advice. It stops short of naming alternatives such as find_articles or get_started_guide, so it is clear context without explicit 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, so the description carries the burden. It discloses the return shape ('titles, summaries and links'), warns that full detail requires reading the article, and explains the semantics of an empty result set — useful behavioral context beyond the 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?

Front-loaded with the core action, then structured into coverage, return value, and a practical tip. The long em-dash topic list is informative but slightly verbose; every clause still earns its place.

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 explains what is returned and defers detail to the article itself. Combined with the empty-result guidance, an agent has enough to call the tool correctly, though limit/pagination behavior is unaddressed.

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%, so the schema documents most parameters. The description hints that queries should use the site's own vocabulary and references the 'site' section matching the category enum, but adds no syntax, limit behavior, or default details. Baseline 3 is appropriate.

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?

Specific verb+resource: 'Search RBX Invest's published guides.' The description scopes the corpus into market content and a named 'site' section, which cleanly separates it from sibling tools like search_items or get_started_guide.

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 clear context (searching published guides, browsing sections) and even advises re-querying with site vocabulary when a search returns nothing. It does not name a specific alternative sibling tool, so it falls 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?

No annotations, so the description carries the full disclosure burden. It usefully adds that this is the live resale market refreshed continuously, which matters because RAP-relative deals can go stale, but it says nothing about read-only nature, auth, rate limits, or the reply's shape beyond the discount fields.

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 short sentences, front-loaded with the definition, then freshness, then the use case. The final sentence slightly restates the first ("underpriced" vs "below RAP"), a minor redundancy in an otherwise tight description.

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 an 8-parameter, no-required-arg tool with no annotations and no output schema, the description adequately frames the result set and the live nature of the data, and it hints at the returned discount/savings fields. It leaves filter semantics entirely to the schema, which is acceptable at 88% coverage.

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 88%, so the schema already documents page, sort, type, min_rap, price bounds and min_discount_pct. The description's mention of "discount and the absolute saving" loosely maps to the deal/savings sort semantics 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?

States a precise criterion (Limiteds whose lowest resale listing is below RAP) plus what is returned (discount and absolute saving). This is inherently distinct from siblings like get_new_limiteds (novelty) and search_items (query-based), so an agent can route to 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?

"Use it for what is underpriced right now" gives a clear when-to-use context tied to the live market. It does not name an alternative or state when not to use it (e.g. vs. get_new_limiteds), so it stops short of full routing guidance.

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 disclose useful traits: each result carries a citable url, the data-use entry returns licensing terms in full, and the tool summarizes badge catalog, socials, and sponsorship content. It is silent on match semantics (substring vs natural-language), result caps, and whether the omitted query returns a paginated dump, which matters for a list-returning 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?

The purpose and query mechanics are front-loaded, which is good, but the middle is two dense enumerations of content categories that partially repeat each other and crowd out the routing information that would actually help. Several clauses could be consolidated without losing meaning.

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 must describe the return shape, and it does: a result set of pages each with a url, plus full licensing text for the data-use entry. For a single-optional-param lookup tool this is nearly sufficient; only result counts and matching behavior 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?

Schema coverage is 100% so the baseline is 3, and the description adds real value beyond the schema: concrete example queries ('market data', 'dominus', 'can I reuse your data') that show the query behaves as natural-language intent matching rather than exact title matching. It also reinforces the omit-for-everything behavior already in 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 clearly states a specific verb+resource: locate any page on rbxinvest.com by keyword, returning its url. It enumerates the page categories (market pages, guide levels, article sections, collections, support, licensing, developer docs), which makes the scope concrete, but it never distinguishes itself from overlapping siblings like find_articles, get_collection, or get_started_guide, whose content it explicitly claims to cover.

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 a usage pattern ('Pass a few words of what you are looking for'; 'omit the query for the full list') and names additional question types it serves, but offers no when-not guidance and no routing against the siblings that cover the same content. The agent must infer whether to call this or find_articles for article content.

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 disclose meaningful behavior: results come back 'in the same order the collection page shows them' and include RAP, lowest listing and copies. It also pins down the citation format, which is unusual and useful. It does not mention pagination behavior, rate limits, or auth requirements, so it falls short of full disclosure.

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 sentences, front-loaded with the resource and its output fields, then slug discovery, then citation format. Each sentence earns its place, though the citation sentence is dense with two URL templates that could be tightened.

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?

There is no output schema, so the description correctly steps in to name the returned fields and their ordering. Combined with the schema's page/limit constraints, an agent has enough to call this correctly. It is only slightly short on pagination expectations (default 10, max 25) which the schema does cover.

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%: slug and sort are documented in the schema, while page and limit have no descriptions at all. The description reinforces the default ordering semantics ('same order the collection page shows them') but says nothing about what page/limit do or how deep paging works. Baseline 3 is appropriate since the schema does half the work and the description only marginally compensates.

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 ('the items in one of RBX Invest's curated collections'), gives four concrete slug examples, and specifies the returned fields (RAP, lowest listing, copies). An agent can distinguish this from get_items/search_items immediately, since those are generic item lookups while this is scoped to a curated collection.

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 explicitly routes the agent to the alternative when the slug is unknown: 'find_page with a word from the collection name returns its slug.' That is a real prerequisite handled well. It stops short of stating when NOT to use this tool (e.g. use get_items for ad-hoc asset IDs), so it is clear context without explicit 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 burden. It does add real semantic context — that the ranking reflects copies held vs distinct owners, with a concrete example (33 copies in one collection vs one copy across 400 people) — but it says nothing about data freshness, scope of 'tracked' portfolios, or result shape.

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 resource and its scope, then the differentiating signal, then the ranking semantics. Three sentences with no filler, though the closing example is illustrative flourish that is useful but not strictly required.

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 6-parameter list tool with no annotations and no output schema, the description covers the metric well but omits how results are returned (fields, whether owner counts are included), pagination behavior, and the relationship to the sibling holdings tool. Adequate but with clear 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%, so the enum parameters (kind, sort, direction) are already documented in the schema. The description re-explains the sort distinction in prose, which reinforces but does not extend the schema; query filtering and pagination are left entirely to 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 clearly that this returns the Limiteds and creators most held across tracked portfolios, and it frames the returned signal (aggregate holding behavior, not price or sales). It distinguishes itself from price/volume tools conceptually, though it never names the near-sibling get_player_holdings, so the boundary is inferable rather than explicit.

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?

'A different signal from price or sales volume' gives implicit guidance on when to pick this over market-cap/sales tools, and the sort explanation clarifies the two ranking modes. However, there is no explicit when-to-use/when-not, no mention of get_player_holdings as the alternative for individual collector data, and no prerequisites.

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 disclose two things structured fields cannot: the data-source population limit and the methodological caveat that a delta can reflect members joining rather than prices moving, with a concrete instruction to compare members_at_start with members. It does not state auth requirements, rate limits, or return format, 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 data is, then the caveat. The first sentence is dense with scope qualifiers but every clause adds real meaning; no filler or restatement of the title.

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 an aggregation tool with no output schema, the description usefully names key return fields and the interpretive caveat, but it omits any explanation of the 'days' window (including the 9999 value), pagination, and the shape of the time series. An agent can call it, but not confidently reason about what it gets back.

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 parameter, 'days', with 0% schema description coverage, and the description never mentions it. The enum includes a non-obvious 9999 all-time sentinel that goes unexplained, so the description fails to compensate for the coverage gap. The output-field names it references (members_at_start, members) are returns, not parameters.

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: combined Classic and UGC value at RAP plus copies held across all public portfolios on the RBX Invest players board, tracked over time. The 'history' framing implicitly separates it from snapshot siblings like get_community_holdings and get_player_holdings, though it never names them 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?

Scope is clarified ('RBX Invest members who linked a Roblox account, not all of Roblox'), which tells the agent what population the data represents. However, there is no explicit when-to-use guidance and no named alternative for snapshot-vs-trend queries, so the routing is left to inference from the name.

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 the low-data behavior (unrated results) and explains that covers_this_creator flags linking articles, which is real behavioral value. It says nothing about permissions, whether the lookup is cached or live, or what a failed name resolution looks like.

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 the substantive output content, with the parenthetical clarifying a field name inline. Dense but every clause earns its place; the only slight drag is the mid-sentence pivot to article provenance.

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 does the heavy lifting by naming the returned signals, which is a solid effort. Missing pieces remain: how name/creator_id resolve or conflict, and what an unrated payload looks like structurally.

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 both parameters are documented there, so the baseline is 3. The description adds no syntax or precedence guidance — notably it does not say which of name vs creator_id wins if both are supplied, even though name's schema text implies omission when creator_id is given.

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 enumerates what the resource yields — profitability frequency, typical time to profit, biggest items, and related articles — which tells an agent this is a creator track-record lookup. It never states the retrieval verb explicitly and is written as a noun phrase, but the subject (a Roblox UGC creator) is unambiguous and distinct from siblings like rank_creators and get_player_holdings.

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 listing, and the unrated clause gives genuine interpretive guidance ('treat that as unknown, not as bad'). However, it never says when to prefer this over rank_creators for creator comparisons, nor what to do when both name and creator_id are omitted.

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 load and does so well: it defines est_demand precisely (release-time sell-out-speed quartile, explicitly not a buy signal), declares its null behavior when unrated, and warns that stock left does not imply availability. It omits error/invalid-id behavior and any sense of cost or rate limits for a single-item lookup.

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 front-loaded correctly and the two closing cautions earn their place, but the middle is a single sprawling sentence enumerating every returned field, which is heavy to parse. The information is mostly load-bearing, so this is over-dense rather than padded.

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 must describe the return payload, and it does so thoroughly enough that an agent knows what to expect field by field, including nested history and article attribution. The only real hole is trend_days, which is never explained.

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%: asset_id is documented in the schema and the description adds sourcing guidance (get it from search_items). trend_days is documented only by the schema's min/max/default, and the description refers to 'a window' without naming the parameter, its 7–90 range, or its default of 30.

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+resource+scope: 'Everything tracked about one Roblox Limited.' It implicitly distinguishes itself from the list-oriented siblings by telling the agent to get an id from search_items first. The purpose is clear, though it is then buried under an exhaustive field enumeration rather than staying crisp.

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 real routing and interpretation rules: needs a numeric asset id sourced from search_items, use the score breakdown to explain scoring, and prefer creator_still_selling over copies_remaining when answering 'can I buy at original price.' It does not say when a sibling like get_market_activity or get_items would be the better call, so it stops short of full alternative coverage.

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 behavioral burden, and it does disclose two useful traits: a hard cap of 200 asset ids per call and the batch error semantics ('ids that are not tracked Limiteds come back in not_found'). It does not mention authentication, rate limits, or whether results are guaranteed to be ordered/complete, 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?

Front-loaded with the action and the returned fields, followed by routing guidance and the batch constraint. Three sentences, each doing distinct work, with no filler or restatement of the title.

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 enumerating the returned fields, and it covers the batch limit, the not_found outcome, and sibling routing. Nothing an agent needs to call this one-call batch lookup correctly is missing.

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 there is only one parameter, so the schema already carries the numeric-id format and 1-200 bounds. The description adds value by clarifying the batch semantics of that array — up to 200 per call and what happens to ids that are not tracked Limiteds.

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+resource ('Look up a known list of Roblox Limiteds in one call') and enumerates the exact fields returned (name, classic or UGC, asset type, creator, RAP, lowest resale listing, stock, original price, favorites, 30/90/180-day sale price). It explicitly distinguishes itself from the sibling get_item_details, so an agent can separate them without opening either 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?

States both when to use it ('compare items or refresh a watchlist instead of calling get_item_details once per item') and when to prefer the alternative ('use get_item_details when one item needs its full history and score'). The selection condition against the closest sibling is explicit, no inference required.

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 does deliver real behavioral detail: the period is compared against 'the same length of time just before it,' Classic and UGC Limiteds are broken out separately, free claims are defined as zero-Robux, and item-for-item trades are explicitly excluded. It omits auth/permission needs, pagination, and any error behavior, keeping it below 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?

The purpose is front-loaded and the three sentences each carry information (metrics, use cases, scoping, exclusion) with little filler. The opening sentence is dense and slightly run-on, but overall it is appropriately sized.

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 two-parameter read tool with no output schema, the description defines what is measured, the comparison baseline, and the scope exclusions, which is nearly enough to call it correctly. It does not describe the response shape (e.g., how Classic vs UGC results are returned) or auth requirements, so a small gap remains.

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 both parameters are documented with their own semantics (including the enum meaning for days=9999), so the schema already does the heavy lifting. The description only restates creator_id scoping ('Pass creator_id for one creator's items') and adds nothing about the days enum, matching the baseline 3 for high 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?

States a specific verb+resource (marketplace sales/free claims over a period) and enumerates the exact metrics returned (distinct items sold, copies sold, Robux spent, free claims), which lets an agent know what it produces. However, it never differentiates itself from close siblings like get_market_stats, get_market_cap, or get_community_market_history, so the 5-tier bar for sibling distinction is not met.

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?

Explicitly names three use cases ('how much was spent, whether the market is busier than before, or how many free UGC copies were claimed') and tells the agent when to scope with creator_id. It is clear context, but no alternative tool is named and no when-not condition is given, 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?

With no annotations provided, the description carries the full burden, and it does well: it defines market cap (RAP × existing copies), discloses the exclusion of item-for-item trades, and explains that figures are for the latest measured day plus a sampled daily series. It omits auth/rate-limit or data-latency caveats, so not 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?

Front-loaded with the headline purpose, then metrics, then usage, then the creator_id note. Dense and mostly waste-free, though the metric enumeration sentence is long and runs on across several clauses.

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?

No output schema exists, so the description must describe returns itself, and it does: market cap, items, copies in circulation, sales volume, Robux spent, mean/median resale price, and the daily series. Combined with the usage and exclusion notes, an agent has everything needed to call 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?

Schema description coverage is 100%, so both parameters are already documented (including the 9999 whole-series nuance). The description only restates creator_id scoping ('same figures over one creator's items') and adds negligible meaning beyond the schema, 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?

States a specific verb+resource ('how big the Roblox Limited market is over any date range') and immediately scopes it as split between Classic and UGC Limiteds. This clearly separates it from adjacent tools like get_market_stats and get_market_activity without needing 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?

Explicitly enumerates when to use it: market size, growth, marketplace-sales comparison, and Classic-vs-UGC differences, plus a note that item-for-item trades are excluded. It doesn't name a sibling alternative or state when NOT to use it, 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?

With no annotations, the description carries the full behavioral burden. It usefully discloses the data exclusion rules (Roblox, unsold originals) and enumerates the covered metrics, but says nothing about access requirements, freshness/caching, or pagination behavior for a stats 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?

Three sentences, front-loaded with the resource location, then the output inventory, then the routing hint. The middle enumeration list is dense but each item is informative rather than 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?

No output schema exists, so the description compensates by listing the returned metrics and the exclusion rules. That is enough for an agent to call a zero-parameter read tool correctly, though data-freshness expectations remain 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?

The tool takes zero parameters, so the schema has nothing to document and the baseline of 4 applies; there is no parameter nomenclature the description could add or omit.

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 (UGC creator market statistics) with its UI location (/market-data Creators tab) and enumerates exactly what is reported, letting an agent distinguish it from sibling stats tools like get_market_stats or get_creator.

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?

Explicitly routes the agent to rank_creators for searching or sorting individual creators, and the exclusion note ('Roblox and unsold original copies are excluded') scopes when the aggregate numbers apply. It stops short of a full when-not-to-use statement but the alternative is named.

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 burden and does meaningful work: it explicitly discloses that holdings figures only cover RBX Invest users who linked a Roblox account, not all of Roblox. It does not describe output format, rate limits, or auth, but introduces no contradictions.

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 with no wasted words. The primary totals are front-loaded, and the important population-scope caveat is cleanly separated in the second 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?

For a parameterless, low-complexity tool, the description covers what is returned and who is included in the holdings figures. It does not specify exact field names or response structure, but that is a minor gap given no output schema and no parameters.

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 has zero parameters, so the baseline is 4. The description appropriately focuses on what the returned totals represent rather than input details, since there is nothing for the agent to configure.

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 clear resource ('Roblox Limiteds market as RBX Invest tracks it') and enumerates the specific totals returned: number of Limiteds followed, copies held, and Robux held. This distinguishes it from sibling tools like get_market_cap or per-player holdings tools.

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 implies use for market-wide aggregate statistics, but it never explicitly contrasts this with siblings such as get_market_cap, get_community_holdings, or get_player_holdings. The caveat about account-linking gives useful context but not explicit when-to-use or when-not-to-use guidance.

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 does meaningful work: it discloses that free_right_now is read live rather than static, and it prescribes conditional output behavior (surface free status first, note prices apply only after the free period). It omits auth requirements, caching/refresh behavior, and error conditions.

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 resource and its contents in one sentence, followed by a short conditional directive. Dense but every clause carries content; slight length comes from packing return contents and presentation rules together.

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 read tool, the description covers what is returned and how to interpret the live free_right_now state. Missing details are minor: no indication of auth/account prerequisites or whether prices can be stale.

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 baseline is 4; there is no parameter surface for the description to clarify. Nothing in the description misrepresents the empty input 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?

Names a specific resource (RBX Invest membership tiers) and enumerates exactly what is returned: regular prices, inclusions, how a paid tier is obtained, and the live free_right_now flag. No sibling tool covers pricing/membership, so the agent can route here without ambiguity.

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 (use when the user asks about cost, tiers, or whether the site is free) but never stated, and no alternatives or exclusions are given. The only directive concerns presentation order once called, not when to call 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 supplied, so the description must carry behavioral context; it usefully explains that demand_level is a release-time sell-out estimate ranked against the last 90 days and is not a buy signal or guarantee. It still does not disclose permissions, pagination behavior, or broader response semantics for the nine-parameter read.

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 opening is front-loaded with the core scope, but the single long sentence packs in multiple nested explanations and repeats demand_level context, making it denser than necessary. It is not bloated with irrelevant text, but structure could be clearer.

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 nine-parameter tool with no annotations and no output schema, the description covers only the high-level feed and demand_level meaning. It omits enough parameter and response detail that an agent would need to rely heavily on the schema and still lack 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 only 56%, and the description does not explain sort, limit, availability, or max_age_days semantics beyond broad phrases like 'recently' and 'stock left'. It therefore leaves several parameters to be inferred from the schema rather than compensating for the coverage gap.

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 the resource (recent UGC Limiteds with remaining stock) and the return content (predicted profit and demand_level), so the core purpose is clear. It does not explicitly contrast itself with sibling tools like search_items or get_items, 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?

The recency and stock constraints imply the use case, and the caveat that demand_level is sell-out speed only clarifies interpretation. However, there is no explicit when-to-use or when-not guidance and no named alternative among the many sibling tools.

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 delivers real behavioral detail: it explains the private-inventory case ('comes back marked private rather than empty'), the nullability of total_items, and what the payload conceptually contains. It stops short of auth requirements, rate limits, or how limit paginates the positions.

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?

Four compact sentences, front-loaded with what the tool returns, then the follow-on prerequisite, then the privacy edge case. Every sentence carries information; only the 'total_copies counts copies' clause is mildly redundant with the field name.

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?

There is no output schema, so the description correctly shoulders the job of explaining the returned totals and their nullability, plus the private-account outcome. The one material gap is the undocumented limit parameter, but for a 2-param read tool the coverage is otherwise solid.

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 50%: roblox_user_id is documented in the schema, but limit (1-100, default 10) is described nowhere in the schema or the description. The sentences about total_copies/total_items describe return values, not parameters, so the description does not compensate for the coverage gap.

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 the resource precisely ('What a tracked player holds: their most valuable positions plus the totals the leaderboard ranks them on'), which is more specific than the title alone. It implicitly separates itself from get_community_holdings by scoping to a single tracked player, though it never names that sibling or any other to disambiguate.

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 a clear prerequisite workflow: 'Follows rank_players, which returns the Roblox user id this needs,' telling the agent where the required parameter comes from. There is no explicit when-not-to-use or alternative-tool guidance, but the sequencing context is strong.

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 behavioral burden. It discloses what the output measures (copies listed, share claimed at each age) which is genuinely useful, but says nothing about return format, pagination, or access constraints. Adequate but incomplete for a no-annotation 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?

Three sentences, front-loaded with the cohort definition, then usage guidance, then the parameter hint. No filler, though the opening sentence is dense and could be split.

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 moderately complex aggregation tool with no output schema and no annotations, the description conveys the grouping unit, the metrics, and the 'at each age' framing an agent needs to interpret results. It leaves output shape and limits unspecified but is sufficient to invoke 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?

Schema description coverage is 100%, so grain, months, and creator_id are already documented. The description's 'Pass creator_id for one creator's releases' merely restates the schema's 'Omit for the whole market' scoping note. Baseline 3 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?

The description defines the resource precisely: cohorts of finite UGC Limited releases grouped by week or month, with copies on sale and claimed share. It is a specific aggregation/reporting tool rather than a generic list. It does not explicitly name or contrast a sibling, 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 gives clear when-to-use context ('compare how fast recent drops sell through against earlier ones') and a methodological caveat ('compare cohorts at the same age_days'). It does not name alternative tools or state when not to use it, so no explicit routing.

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 discloses the return format (text with section links), the base URL for relative paths, and the authoritative naming constraint about subscription and product names. It does not mention permissions or side-effect profile, but for a guide tool this is substantial 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?

The description is long but front-loaded and structured, moving from purpose to level definitions to step definitions to invocation and return details. Most sentences carry useful selection or content information. It could be trimmed slightly, but it is not repetitive or misleading.

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 does the necessary work: it explains what the tool returns, how to select level, step, or overview, and the base URL for the returned links. It also states an important naming constraint. Nothing essential for calling or interpreting this guide tool is missing.

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 baseline would be 3. The description greatly elaborates the meaning of each level and step, including what each level's guide covers and how the three beginner steps relate to levels 1 and 2. This adds meaningful selection guidance beyond the schema's brief enum descriptions.

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: RBX Invest's guide to making Robux with Roblox Limiteds, with one guide per experience level. It clearly enumerates levels and steps, so an agent can tell what content it returns. It does not, however, distinguish this tool from siblings such as resell_guide, so it falls short of a full 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?

The description implies usage by explaining that callers should pass a level or step, or omit both for the overview. It does not say when to choose this tool over alternatives, nor does it name any sibling tool or exclusion condition. The guidance is therefore only 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?

With no annotations, the description carries the full burden and does disclose a non-obvious behavioral trait: the ranked population changes with the sort (only creators with settled releases for 'chance', 3+ items for 'growth'). It does not cover pagination limits or whether ranking is deterministic, so it is strong but not complete.

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 sentences, front-loaded with the core purpose, then the sibling routing, then the sort caveats. No filler; the final clause ('an average over one release is noise') explains the rationale rather than 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?

All five parameters are optional and the description plus schema cover how to call it correctly. With no output schema, however, it never says what a ranked row contains (name, rating, metrics), leaving the agent to infer the response shape.

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?

Adds real meaning beyond the 60%-covered schema, notably clarifying that 'growth' here is the lifetime appreciation measure, not the windowed move used by item sorts — a cross-tool disambiguation the enum text alone does not make. 'limit', 'direction' and 'query' are left to the schema, which mostly covers them.

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 ('Creators ranked across the whole Roblox Limited market') plus the two axes of interest (size and profitability). It explicitly distinguishes itself from the sibling get_creator, so an agent can route without opening either 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?

Names the alternative tool and the exact condition that selects it: 'get_creator answers about one creator you can already name; this finds them.' It also warns which creators drop out of the result set under the 'chance' and 'growth' sorts, which is practical when-to-use guidance.

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. It does disclose a meaningful trait beyond the schema: the board covers only RBX Invest sign-ups with linked Roblox accounts, so ranks are board-local, not global. It says nothing about return format, pagination behavior, or the 'status: unavailable' state that the schema enum mentions.

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, with the core ranking statement front-loaded before the scope caveat. It is efficient, though the second sentence is somewhat discursive and could have been tightened.

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?

No annotations and no output schema, so the description should ideally describe the shape of a result row (rank, holdings, robux_donated). The scope caveat is valuable, but without any description of return values or paging semantics, the definition is only minimally complete for a ranking endpoint.

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%, so the baseline is 3. The description loosely maps the metrics to plain language (total RAP held, copies held, distinct items, Robux donated), which helps interpret 'value' and 'sponsor', but the schema's enum description already spells these out more precisely, so the description is largely redundant rather than additive.

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 verb (rank) and resource (Roblox Limited portfolios tracked by RBX Invest), and enumerates the four ranking metrics, so an agent can distinguish it from rank_creators at a glance. It also scopes the population being ranked, which sharpens the purpose rather than restating the title.

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 implies usage (get a leaderboard of tracked portfolios) and importantly clarifies the eligible population, which affects whether a result is worth using. However, it never says when to choose this over rank_creators or how limit/offset interact with paging, so no explicit when/when-not guidance or alternative routing is 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?

No annotations are provided, so the description carries the full burden. It discloses the retrieval behavior (topic narrows to matching entries, omission returns the whole guide), but says nothing about the return shape or size of the guide entries, which for a documentation tool is the main behavioral question left open.

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 is and the URL, followed by the parameter behavior. The topic enumeration is dense but every item helps an agent decide whether a user's question is covered.

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 single-optional-parameter, no-output-schema, unannotated help tool, the description covers identity, coverage scope, and invocation semantics. Only the return format remains unstated, and the absence of a return contract is the one remaining gap.

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 already supplies example values, but the description goes beyond it by explaining the matching semantics ('the words a question uses as topic') and the omit-for-everything default — meaning the schema alone would not convey.

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 Reseller Terminal's help text) with its URL and enumerates exactly what topics it covers — counters, card numbers, search/sort, filters, saved views, statuses. It is conceptually distinguishable from get_started_guide, though it never explicitly contrasts itself with that sibling.

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 states how to invoke: pass the question's words as 'topic' to get matching entries, or omit it for the whole guide. What is missing is an explicit when-to-use-vs-alternatives rule, e.g. when to reach for resell_guide instead of get_started_guide or find_page.

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 does well: it discloses currency (Robux), page size (100 rows), a hard paging ceiling (offset 10,000), and metric caveats such as metrics being absent for items that did not sell in the window and moving averages excluding free claims. It does not cover auth or rate-limit behavior, but for a read-only catalog search this is strong disclosure.

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, then return fields, then ranking/filtering, then paging constraints. Dense and mostly waste-free, though the long enumeration of return fields makes it heavier than strictly necessary given that the schema already documents the sortable metrics.

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 an 11-parameter tool with no output schema and no annotations, the description compensates by enumerating the returned fields and spelling out paging limits and the bulk-download alternative. It is close to complete; only auth/permission context is left unaddressed, which is minor for a read 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 already 82%, so the baseline is 3, but the description adds genuine meaning: it explains that filters are ANDed, that each bound is in the metric's own unit (Robux/percent/count), and that items lacking a bounded metric are excluded. These are semantic clarifications 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?

States a specific verb and resource with scope: 'Search the Roblox Limited catalog by name, or screen the whole market when no query is given.' The dual mode (name search vs. whole-market screening/ranking) is made explicit. It does not explicitly differentiate itself from siblings like get_items or find_deals, which keeps it just 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 clear when-to-use context: screen the whole market when no query is given, rank via sort, narrow via filters for multi-condition questions, and download catalog.json 'instead of paging' for the full set. It names an alternative for the complete-dataset case but does not route the agent among other sibling tools (e.g., get_item_details), so it falls short of full 5-level routing.

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