TheDiscList Public MCP

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

No annotations are provided, so the description carries the full transparency burden. It outlines the computation performed (deltas, stability spread) and implies a read-only operation, but does not explicitly state side-effect-free behavior or return format, though that is less critical for a comparison tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with no unnecessary words. It efficiently communicates the core functionality and the key constraint (2 to 4 discs).

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?

Given there is no output schema, the description sufficiently covers what the tool does and what it computes. It provides enough context for an agent to decide when to invoke it and what to expect in terms of results (deltas and stability spread).

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 schema already describes the disc_ids parameter (array, 2-4 items). The description adds meaningful context by indicating that the primary baseline disc is the first in the array, which is not in the schema. This enhances understanding without redundancy.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: comparing 2 to 4 discs and computing flight rating deltas and stability spread. This is distinct from the sibling tools (get_disc, search_discs, find_similar_discs), making its role unambiguous.

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

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

The description implies usage for comparison scenarios but does not explicitly contrast with sibling tools. It does not specify when to prefer this over find_similar_discs or search_discs, leaving some inference to the agent.

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, and the description does not disclose any behavioral aspects such as whether the operation is read-only, potential side effects, or data source limitations. The name suggests read-only, but that is not stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no redundant words. It is well-structured and front-loaded with the main purpose.

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 is provided, and the description does not specify the return format (e.g., list of discs, ordering, or any additional metadata). Since there is no output schema to fill this gap, the description should have provided some indication of the return value.

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 schema provides descriptions for all four parameters, covering their meaning and default values. However, the description itself does not add additional context beyond the schema, leaving potential ambiguity about how parameters like target_brand or exclude_same_brand interact.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: finding alternative discs similar to a target based on category, speed, and flight profile. It distinguishes this from sibling tools (e.g., search_discs, compare_discs) by focusing on similarity matching.

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 intended use case is implied by the description, but no explicit guidance is given on when to use this tool versus alternatives. It lacks statements like 'use this when you need replacements for a disc' or comparisons with sibling tools.

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

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

Since no annotations are provided, the description carries the burden. The verb 'Retrieve' clearly indicates a read-only operation with no side effects, which is sufficient disclosure for a retrieval tool. It doesn't mention potential limitations like caching or data freshness, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that lists the purpose and the data fields. No unnecessary words or repetition, making it concise and scannable.

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?

Given the tool's simplicity (one input parameter) and that the output fields are enumerated (flight ratings, stability score, etc.), the description provides sufficient context for an agent to know what to expect. It doesn't need an explicit output schema because the description already outlines the return values.

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 schema description for the 'id' parameter already covers the input format with examples and clarification that it accepts stable ID or slug. The tool description adds nothing beyond that, so it meets the baseline for full schema 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?

The description clearly states that the tool retrieves comprehensive details for a specific disc by ID or slug, listing the types of information returned. This distinctly differentiates it from siblings like search_discs (which likely searches) and list_brands.

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 mentions input via numeric ID or string slug, which is a usage guideline. However, it does not explicitly compare with alternatives (e.g., 'use this when you have an exact ID, not when searching'), so guidance is implied rather than explicit.

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

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

No annotations are provided, so the description must disclose behavior. It states the data is current weekly retail sales rank and 4-week momentum, which is useful context. However, it does not mention error behavior for invalid disc_id, whether the operation is read-only, or how 'momentum status' is defined. The description only partially carries the transparency burden.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. Every phrase adds information: specific resource, regions, time frame, and momentum context.

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 one-parameter read tool with no output schema, the description states what is returned (rank per region and momentum status) and names the regions. It omits response shape and error handling, but these are minor for such a simple 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?

The input schema already fully describes disc_id with examples and formats, and schema coverage is 100%. The tool description adds no parameter-level details beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with the verb 'Retrieve' and specifies the exact resource: a single disc's weekly retail sales rank across named regions (Global, Europe, Americas, Oceania, Asia) and its 4-week market momentum status. This clearly differentiates it from siblings like get_weekly_rankings (list-oriented) and get_market_movers (market movers).

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 the tool is for a single disc's ranking/momentum but never explicitly states when to choose it over siblings like compare_discs, find_similar_discs, get_disc, get_market_movers, or get_weekly_rankings. No exclusions or alternatives are mentioned, so usage guidance relies on inference.

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. It discloses the output shape (a 2D grid grouped by stability categories) and the filtering dimensions, but it does not explain edge cases, return format details, or what happens when no filters are provided.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, information-dense sentence. It front-loads the core purpose and packs the filter dimensions and output grouping into one clean statement with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is adequate for a tool with three optional filters and no output schema, but it leaves gaps: the response format is not described, and there is no mention of defaults or constraints. For a medium-complexity tool with no annotations, a bit more context would be expected.

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?

All three parameters already have clear descriptions in the input schema, so schema coverage is 100%. The description essentially restates the same filter concepts without adding new parameter-level meaning, which meets the baseline but adds little 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?

The description uses a specific verb ('Generate') and names the exact resource ('2D Speed vs Stability Flight Grid'), including the stability groupings. This clearly distinguishes it from sibling tools that look up individual discs, compare discs, or provide rankings.

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 gives clear context on when to use the tool: for any brand, category, or specific speed rating. It does not explicitly mention alternatives or when-not-to-use scenarios, so it falls just short of full 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?

No annotations are provided, so the description carries the full burden. It discloses the rolling 4-week window and enumerates the mover categories, but doesn't mention response format, pagination, auth, or other behavioral traits. For a read-only retrieval tool, this is adequate but not rich.

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 that conveys the core action, time window, and all relevant categories without any fluff. Every word 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?

The tool is simple with two well-documented parameters, and the description covers the conceptual scope. It doesn't specify the exact response structure (there is no output schema), but for a list-style movers endpoint this is likely sufficient. Minor gaps like default behavior are already covered in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% because both type and limit have descriptions. The description's mention of disc types mirrors the enum values and adds no extra meaning beyond what the schema already provides. 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?

Description has a clear verb and resource: 'Retrieve rolling 4-week disc golf market movers' and lists specific categories. It is easy to understand what the tool does, but it doesn't explicitly differentiate from sibling tools like get_weekly_rankings, so it falls 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?

The phrase 'rolling 4-week' provides helpful context for when to use this tool, but no alternatives or exclusion criteria are mentioned. An agent must infer that this tool is for market movers rather than weekly rankings, disc comparisons, or searches.

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 of behavioral disclosure. It discloses that the data is aggregated from 40+ retailers and is weekly, but does not clarify whether the operation is read-only (highly likely for a retrieval tool), whether results are limited to the Top 10 by default, or how risers/fallers are computed. The absence of annotations but a plain retrieval description makes a score of 3 appropriate – it is transparent about what it returns but lacks depth on behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the primary purpose and scope, then the region list. Every word earns its place, no redundancy or 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 simple retrieval tool with fully documented parameters, the description covers the essential context: what is returned (rankings, risers/fallers), the regional scope, and the data source. The output schema is absent, so the description does not need to explain return values, but the tool also lacks guidance on how this relates to get_market_movers or get_disc_ranking, which likely overlap. Slight gap in distinguishing from siblings prevents a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description adds context by mentioning 'Top 10' and regional values, which aligns with the limit and region parameters. However, it does not add much semantic nuance beyond the schema – e.g., what happens when limit is reduced, how risers/fallers interact with the limit, or whether region values are case-sensitive. Baseline 3 is correct since the schema already documents both parameters well.

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 provides a specific verb ('Retrieve'), a specific resource (weekly disc golf retail sales rankings), and precise scope (Top 10, top risers/fallers by region). It also names the data source (40+ worldwide retailers), which distinguishes it from sibling disc-related tools that likely focus on individual discs or market movers.

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 is clear about what data the tool returns and specifies the region options, but it does not explicitly state when to use this tool versus the sibling tools like get_disc_ranking or get_market_movers. The context is implied (weekly rankings vs possibly daily rankings or individual disc details), but no exclusions or alternative routing are given.

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

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

With no annotations, the description carries the behavioral burden. It conveys a read-only listing/filtering operation and previews key output fields, but it does not explicitly state that no mutation occurs, how results are ordered, or how filtering behaves for partial matches.

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 efficient sentence that front-loads the action and target resource, then appends the key result details. Every clause 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?

For a list/filter tool with fully documented optional parameters, the description covers the main purpose and output highlights. It could be more complete by noting pagination defaults and the exact result shape, but these are largely covered by the schema and implied by the listed output fields.

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 each parameter already has a clear description with defaults and examples, so the description adds no new parameter semantics. The baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb (list and filter), a clear resource (disc golf manufacturers/brands), and the scope of returned data (mold counts, speed ranges, category breakdowns, and top molds). This clearly differentiates it from the disc-focused sibling tools, since list_brands is the only brand-level tool.

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 clearly implies this is the tool for brand-level overviews and filtering, while all siblings are disc-focused. It does not explicitly provide when-not-to-use guidance or route to alternatives, but the context is clear enough for an agent to select it correctly.

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 behavioral disclosure burden. It adds genuinely useful facts — results are bounded to a 50-cap, IDs are stable, and URLs are canonical — which help an agent reason about pagination and result identity. However, it remains silent on filter combination semantics (AND vs OR), default sort order, and empty-query or no-filter behavior.

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 zero filler. The action and scope are front-loaded in the first sentence, and the second adds the return contract. Every word earns its place; it is efficiently sized given the 18-parameter schema.

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 tool with 18 optional parameters, no annotations, and no output schema, the description covers the essential return contract but omits operational details an agent would need: default sort order, whether combined filters are ANDed, pagination semantics beyond offset/limit, and behavior when no filters are supplied. Adequate but with clear gaps for a tool this complex.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description's filter list merely paraphrases the schema's property descriptions (brand, category, speed/glide range, stability range, flight tag, flight class) without adding any new parameter-level meaning, syntax details, or interaction caveats.

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 action ('Search and filter') on a clear resource ('disc golf discs') and enumerates the filter dimensions (text query, brand, category, speed/glide range, stability score range, flight tag, canonical flight class). The purpose is unmistakable and intuitively distinct from siblings like compare_discs, get_disc, or find_similar_discs, though it never names a sibling 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?

No when-to-use guidance is provided. With 8 siblings including find_similar_discs, compare_discs, and get_disc, an agent receives no direction on which tool fits which intent, nor any exclusions, prerequisites, or conditions for choosing an alternative.

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