SteamDT MCP Server

Server Quality Checklist

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Latest release: v2.1.0
Disambiguation5/5
Each tool targets a distinct aspect of CS2 item data (basics, indices, klines, prices, wear, inspect, search, styles) with no overlap. Even similar tools like price_single and price_batch are clearly differentiated.
Naming Consistency5/5
All tools follow the consistent pattern 'steamdt_verb_noun' in snake_case, making the purpose predictable. Examples: steamdt_get_base_info, steamdt_search_item_by_name.
Tool Count5/5
13 tools is well within the ideal range. Each tool serves a specific need without redundancy, covering the core functionality of a CS2 data server without being overwhelming.
Completeness4/5
The tool set covers essential operations: retrieving base data, indices, klines, prices (single, batch, averages), wear, inspect, and search. Minor gaps exist (e.g., no direct item detail endpoint, no user-specific data), but the core CS2 item analysis workflow is well-supported.
Average 3.7/5 across 13 of 13 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 10 times in the last 30 days.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only notes absence of volume data, but fails to disclose other behavioral traits like data freshness, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff. However, it is almost too terse, but for a simple tool it is adequately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter, no output schema, and no annotations, the description should provide more context about expected output, type mapping, or usage scenarios. It currently only gives a minimal functional description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameter with a description of type (1-3), but the tool description does not add meaning beyond that. No explanation of what each type value represents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it queries CS2 market K-line data without volume, clearly distinguishing it from sibling tools like steamdt_get_item_kline which is item-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., steamdt_get_item_kline for individual items). The description lacks use-context information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses rate limit (120/min) and that volume is excluded, which is useful. But lacks info on error behavior, authentication needs, or other constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words; front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and despite 4 parameters, description is minimal. Does not explain return format or provide examples, but covers key points like volume exclusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. The description adds no extra meaning beyond the schema, earning a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it queries item K-line data and notes volume exclusion. However, it does not explicitly differentiate from sibling tools like steamdt_get_broad_kline, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no prerequisites or when-not-to-use conditions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description discloses it queries with rise/fall and history but omits details like response format, rate limits, or read-only nature. Insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, highly concise, front-loaded with action. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description provides basic context (includes rise/fall and history) but lacks full response specification. Adequate for a simple tool but could be more detailed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; schema coverage is 100%. Description adds context about output (rise/fall, history) but does not detail response structure. Baseline 4 reduced due to lack of output schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries the latest CS2 broad market index with rise/fall values and historical records. It distinguishes itself from siblings like steamdt_get_broad_kline which likely fetches k-line data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies usage for getting the latest index but lacks exclusions or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the rate limit (100/day) and that it's a scarce resource, but does not specify if the operation is read-only or if there are side effects beyond rate limiting.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The first sentence conveys the action and prerequisite, the second adds a critical constraint. Perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should clarify return format. It mentions '2D inspection view' but does not specify whether output is an image URL, image data, etc. Prerequisite is noted but does not link to the specific sibling tool. Adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage for both parameters. Description adds no additional meaning beyond what is in the schema, meeting the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates a 2D inspection view from a CS2 inspect link. It implies a prerequisite (obtain wear data), which differentiates it from siblings like steamdt_get_inspect_by_asmd, but does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a prerequisite (need wear data first) and mentions the rate limit, giving basic guidance. However, it does not explicitly state when to use this tool versus alternatives like steamdt_get_wear_by_inspect_url or steamdt_get_inspect_by_asmd.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only discloses rate limit, not other behavioral traits like authentication needs, data freshness, or read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no unnecessary words, efficiently conveying purpose and constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers basic function and frequency limit, but lacks output description (structure of price data per platform) since no output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. Description adds that marketHashName is the official Steam item name and obtainable from base_info, providing helpful context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries selling/buying prices for a single item across platforms using marketHashName, distinguishing it from batch or average price tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions a frequency limit of 60 times/minute, but provides no guidance on when to use versus alternatives like batch or average price tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions a rate limit and scarcity, but does not disclose the output format (e.g., image URL vs binary), whether the call is synchronous/asynchronous, or authentication requirements. The optional notifyUrl suggests possible async behavior, but this is not clarified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences covering purpose, prerequisite, and rate limit. No fluff or redundant information. The key action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite a 100% schema coverage and a concise description, critical context is missing: no output schema or description of return value (e.g., image URL or binary), no explanation of why all parameters are optional, and no clarification on the notifyUrl parameter's behavior. The tool's complexity (5 optional params) requires more completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions for all 5 parameters. The description adds the context that the ASMD parameters come from a wear data tool (implied by prerequisite), but does not elaborate on individual parameter meaning or how to obtain them beyond the schema. Baseline 3 is appropriate since schema already documents them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb '生成' (generate), the resource '饰品 2D 检视图' (item 2D inspection view), and the method '通过 ASMD 参数' (via ASMD parameters). It also mentions a prerequisite (wear data), which differentiates it from sibling tools like steamdt_get_inspect_by_url that use a URL instead.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states a prerequisite ('需先获取磨损度数据' - need to obtain wear data first), guiding the agent to call another tool beforehand. It also includes a rate limit (100次/天). However, it does not name the specific sibling tool for wear data or provide 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It indicates a read operation ('查询') but omits behavioral details like authentication requirements, rate limits, or data staleness. As a data retrieval tool, it is minimally adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, directly stating the tool's function and parameter flexibility. No redundant words, front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so description must convey return value. It mentions overall and per-platform averages, which suffices. Could specify data format or time range boundaries, but the description is complete enough for an agent to understand the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context that the tool returns overall and per-platform averages, which goes beyond parameter descriptions. However, it does not introduce new parameter-level details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries average prices for accessories over 7 days across all platforms, with per-platform breakdown. It explicitly supports the 'days' parameter for extended periods. This distinguishes it from sibling tools like 'steamdt_get_price_single' (single point price) and 'steamdt_get_price_batch' (batch query).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings. The description implies usage for time-averaged cross-platform prices, but does not mention alternatives like 'steamdt_get_price_single' for current price or 'steamdt_get_item_kline' for detailed candlestick data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses critical behavioral traits: rate limit (1 per minute) and maximum items (100). It does not cover error handling or output format, but it is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences convey purpose and key constraints. No wasted words, but could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output format description. With no output schema, the tool's return value is unclear. Also does not specify which platforms are queried.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and already explains the parameter well. The description adds the batch size constraint but no further parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it batch queries selling/purchasing prices on various platforms. It distinguishes from single-item tool and average price tool among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions rate limit and batch size limit but provides no guidance on when to use this tool versus alternative tools like steamdt_get_price_single.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It only states it 'gets' a table, implying a read operation, but does not disclose behavioral traits like permissions, rate limits, or whether it modifies data. The lack of explicit read-only or safety indication weakens transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action and purpose. Every sentence adds value, no wasted words. It is appropriately concise for a simple parameterless tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description covers the essential purpose and use case. However, it does not describe the return format or structure of the comparison table, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and schema coverage is 100% (vacuously). The description adds value by explaining the table's content and use case, exceeding the baseline of 3 for high coverage. With no parameters, the baseline is raised to 4 as per guidelines.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a CS2 item special style comparison table, listing specific styles like tiers, stages, Doppler phases, gems, etc. It also mentions its use in analyzing paintseed and special style fields, distinguishing it from sibling tools that handle other data like base info, prices, or wear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for analyzing paintseed and special style fields but does not explicitly state when to use this tool versus its 12 siblings. No when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It notes the rate limit, which is a helpful constraint, but does not clarify whether the operation is read-only, requires authentication, or if it has side effects. The safety profile is under-specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that convey the core purpose and an important usage constraint (rate limit). Every word is necessary and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema and no annotations, the description is minimal. It fails to explain the output format (e.g., wear value as a float), possible error conditions, or how the ASMD parameters relate to the result. For a tool with 5 parameters and none required, more guidance is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, with each parameter having a brief label (e.g., 'ASMD 参数 S'). The description does not add any extra meaning beyond what the schema already provides, so it meets the baseline but offers no additional clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries item wear degree via ASMD parameters and explicitly mentions it's an alternative to the inspect link method, distinguishing it from sibling tools like steamdt_get_wear_by_inspect_url.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use (when ASMD parameters are available instead of inspect URL) and mentions the rate limit (36,000 times/hour), providing useful usage context. However, it doesn't explicitly state when not to use or list alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It discloses that the tool is read-only (query), supports async mode, and has a rate limit. It does not detail error handling or authentication needs, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences deliver the core purpose, async support, and rate limit. Every sentence contributes meaningfully, and the most critical information (purpose) is first. No redundant or irrelevant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main functionality and sync/async modes, but lacks details on the exact output structure (no output schema) and error handling. For a simple query tool, it is adequate but leaves gaps for an agent to interpret the return format and failure scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters having clear descriptions. The tool description supplements the schema by explaining the sync/async flow ('不填则等待同步返回') and linking the inspect URL parameter to the tool's purpose. This adds value beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool queries item wear and related data (stickers, charms, float values) via a CS2 inspect URL. The verb '查询' and resource '饰品磨损度及相关数据' are specific. The sibling 'steamdt_get_wear_by_asmd' is implicitly distinguished by the method (inspect URL vs ASMD), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description mentions support for synchronous and asynchronous callbacks and a rate limit of 36000/hour, providing some usage context. However, it does not explicitly state when to use this tool versus alternatives like 'steamdt_get_wear_by_asmd' or 'steamdt_get_inspect_by_url', leaving selection guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 caching requirement and that the tool returns marketHashName and specialStyle values. However, it does not mention error handling, rate limits, or what happens if the cache is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences, front-loading the core purpose and then adding key details about prerequisites and special style recognition. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description clearly states what is returned (marketHashName and specialStyle). It covers the prerequisite and parameter behavior. With two parameters well-described and sibling context, the description is sufficiently complete for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema description covers the query and limit parameters adequately. The description adds value by explaining that the query is processed for automatic style keyword recognition and returns specialStyle, which goes beyond the schema's documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool performs a fuzzy search by Chinese or English name for items, returning matching marketHashName and recognizing special style keywords. It is distinct from sibling tools which are primarily data retrieval or inspection functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly mentions a prerequisite: calling steamdt_get_base_info first to establish a cache. It also notes automatic recognition of special style keywords, guiding when to use this tool for style filtering. However, it does not specify when not to use it or provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully discloses behavior: it calls an API daily limit of 1, caches results locally, and allows forced refresh via the parameter. This is transparent for a read tool with no destructive effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, concise and front-loaded with the main purpose, then adds caching and rate limit details. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description covers all essential aspects: purpose, caching behavior, rate limit, and parameter effect. It is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'forceRefresh' is described in the schema, but the tool description adds context by explaining caching and daily limit, which clarifies the parameter's purpose. Schema coverage is 100%, but the description still adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the full list of CS2 item base info including marketHashName and platform itemIds, with a specific verb '获取' and resource '全量 CS2 饰品基础信息列表'. It distinguishes from sibling tools by focusing on base info list, unlike price or inspect tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining the base item list and notes the daily call limit and caching behavior, but does not explicitly state when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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