RBX Invest Roblox Limiteds market data

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 disclosure burden and does reasonably well: it states each result carries a url to cite and that the data-use entry returns licensing terms in full, which govern reuse of everything the tools return. It omits cost/latency/auth details, but for a read-only lookup the key behavioral facts are covered.

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 what the tool covers, then immediately the call syntax and return semantics. The opening enumeration is long but each item earns its place by telling the agent which content is reachable; no filler sentences.

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 assumes responsibility for return values and does so (url per result, full licensing text in the data-use entry). For a single-optional-param read tool, nothing an agent needs to call it 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%, so the baseline is 3, but the description goes further by supplying example query strings ("market data", "dominus", "can I reuse your data") that demonstrate the expected granularity of the single param. It reinforces the omit-for-all behavior without contradicting 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?

Names a specific verb and resource and enumerates exactly the surface it indexes (market pages, Get Started levels/steps, article sections, collections, support, data-use/licensing, developer docs). That enumeration distinguishes it from siblings like find_articles, get_collection, and get_started_guide, which each cover only a slice of what find_page spans.

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 concrete usage guidance: pass a few words, omit the query for the full list. It does not explicitly name an alternative tool or a when-not-to-use condition, but the site-wide indexing scope makes its role as the discovery entry point 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?

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?

With no annotations, the description carries the full behavioral burden and does so substantially: it discloses a semantic trap (stock left does not mean on sale), the meaning of creator_still_selling versus copies_remaining, and what the score breakdown contains. It never explicitly states the operation is read-only or what happens on an invalid/missing id.

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 content is potentially valuable because there is no output schema, but it is delivered as one sprawling run-on sentence that enumerates a dozen output fields in a single breath, making it hard to scan. It front-loads the resource definition, but the structure is poorly segmented for an agent to parse.

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 the returned data (summary, RAP movement, resale book, stock, sales, trend, score breakdown, sales history, related articles), which is necessary here. Remaining gaps are error behavior and the undocumented trend_days parameter, which are minor against the overall 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 coverage is 50%: asset_id is documented in the schema and reinforced by the description's 'needs a numeric Roblox asset id' plus routing hint, but trend_days has no schema description and the text only alludes to it via 'moved over a window,' never naming the parameter or its 7–90 range. Baseline 3 given the partial schema coverage and only partial compensation.

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 and scope — everything tracked about one Roblox Limited, retrieved by asset id — and clearly routes the agent to search_items to obtain the id. It is distinguishable from list-oriented siblings like get_items, though it never explicitly names a contrasting 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 gives concrete usage instructions: obtain a numeric id from search_items first, use the score breakdown to explain results, and read creator_still_selling rather than copies_remaining to answer whether an item can still be bought at original price. It lacks explicit when-not-to-use guidance or named alternatives.

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 provided, so the description carries the full burden; it partially discharges this by disclosing the returned fields, which is valuable given there is no output schema. However, it never states pagination behavior (page/limit exist), sorting semantics, read-only nature, or any auth/rate-limit 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?

A single front-loaded sentence with no filler; the resource and the payload are stated immediately. It is slightly run-on and never states an action verb, but nothing is wasted.

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 listing tool with no annotations and no output schema, the description should cover paging, sort options, and filter semantics. It names only the returned fields and omits everything needed to drive the parameters 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 56%, with four of nine parameters (sort, limit, availability, max_age_days) carrying no schema description at all. The description adds nothing about any parameter, so the undocumented filters and the sort enum values are left unexplained in both places.

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 (UGC Limiteds released recently) and enumerates the fields returned (demand level, stock left, predicted profit), so an agent knows what it gets. It stops short of differentiating from nearby siblings like get_items, search_items, or find_deals, and uses no explicit verb.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance and no mention of alternatives, even though search_items, get_items, and find_deals overlap in domain. Only an implicit read of 'recent releases' hints at the use case.

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?

With no annotations, the description carries the behavioral burden and does reasonably well: it discloses the return format (text with section links), notes paths are relative to https://rbxinvest.com, and defines the default (overview with five levels, three steps, glossary) when no parameter is passed. It doesn't state read-only/auth-free status, but for a content-retrieval tool the disclosure is solid.

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 content is dense but the most operationally important sentence — how to invoke it and what it returns — sits at the very end, after a long curriculum narrative. Several sentences read as promotional copy about Roblox Plus and affiliate shares rather than invocation guidance, so size is not fully justified.

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 compensates well: it explains parameter behavior, the omission default, and the return shape (text plus section links with a known base URL). Nothing essential to calling it correctly is missing, though it could note that content is purely informational/read-only.

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 enums are self-described, so the baseline is 3. The description goes further by spelling out what each level and step actually contains (e.g. Level 3 covers screening a release, break-even, holding period, exit pricing), giving the agent real disambiguation value beyond the terse schema 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 makes clear this returns RBX Invest's tutorial content on earning Robux with Roblox Limiteds, organized one guide per experience level, and the closing sentence states the operation ('Returns the text with section links'). The verb is somewhat implicit and buried under curriculum detail, and it never contrasts itself with the sibling find_articles, 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?

It explicitly tells the agent how to select content: 'Pass level or step; omit both for the overview,' and maps each enum value to a reader profile. What's missing is any guidance on when to reach for this tool versus find_articles or the market-data siblings, so it's context without 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 discloses meaningful behavioral constraints: certain sort modes filter out creators with insufficient data (profitability and growth), which is real invocation-relevant context. However, it says nothing about read-only nature, result size defaults, pagination behavior, or what a result row contains.

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, each earning its place: scope, sibling routing, and a caveat on sort-mode behavior. Front-loaded with the primary purpose and no 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?

For a paginated ranking tool with five parameters, no annotations, and no output schema, the description covers scope and sort caveats but omits result shape, pagination guidance, and default behavior. It is adequate but leaves gaps an agent would have to infer.

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%. The description adds real meaning for the 'growth' sort, clarifying it is lifetime appreciation versus the windowed measure used by item sorts, and distinguishes chance as profitability frequency. That said, it doesn't clarify the remaining under-documented parameters and the schema already documents limit, offset, query, and direction.

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 (rank) and resource (creators) with explicit scope: 'ranked across the whole Roblox Limited market.' It directly distinguishes itself from the sibling get_creator with 'get_creator answers about one creator you can already name; this finds them,' letting an agent route correctly 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?

Explicitly names the alternative (get_creator) and the condition that selects between them, plus states when some sort modes return results (profitability needs settled releases, growth needs 3+ items). It does not cover when to pick rank_creators over rank_players beyond the obvious resource difference, so it falls short of a full 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 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.