TheDiscList Public MCP

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

With no annotations provided, the description carries the full behavioral burden. It does disclose a meaningful behavioral trait: the tool 'computes' deltas and stability spread rather than mutating data, and it establishes a 'primary baseline disc' framing. It does not, however, say what happens with invalid/unknown disc IDs, how the baseline is chosen, or what the response structure will be.

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 tightly packed sentence states the action, the valid count range, the comparison mode, and the computed metrics. Every phrase earns its place, and there is no filler or repetition of the 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 single-parameter tool with full schema coverage and no nested objects, the description is nearly complete: it states the operation, the input cardinality, and the key computed outputs. Since there is no output schema, a slightly more explicit statement of the return shape would close the last gap, but the mention of deltas and stability spread gives adequate context.

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 fully documents disc_ids as an array of 2 to 4 IDs or slugs, so the baseline is 3. The description adds genuine operational meaning by introducing the 'primary baseline disc' concept, which implies ordering significance in disc_ids. This is meaningful context beyond the schema's generic array description.

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 ('Compare') and resource ('discs'), and clearly distinguishes this tool from siblings by adding the scope '2 to 4 discs side-by-side' and the unique output concept of 'flight rating deltas and stability spread'. It is immediately obvious this is not get_disc, search_discs, or find_similar_discs.

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 makes the core use case clear: compare a set of 2–4 discs relative to a primary baseline. However, it does not explicitly state when to prefer this over find_similar_discs or search_discs, and there are no exclusion conditions or alternative routing hints. Usage context is implied rather than prescribed.

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 carry the full burden of behavioral disclosure. It mentions the matching algorithm but does not state whether the operation is read-only, what the output format is (list of discs, details, ordering), or how edge cases (e.g., no matches) are handled. This is a significant gap for a tool with zero annotation coverage.

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 that front-loads the core purpose and algorithm. There is no redundant information or fluff, making it efficient for an agent to parse quickly.

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 has 4 parameters (all documented) and no output schema. The description explains the matching logic but omits critical context such as the return format (whether it returns full disc objects or just IDs), result ordering, and any read-only guarantees. Given the lack of annotations and output schema, the description is only partially complete for safe invocation.

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 all parameters are documented. The description adds minimal new meaning beyond the schema: it clarifies that disc_id refers to the target disc and that the tool uses category/speed/flight profile, but this is largely implicit in the schema. Since the schema does the heavy lifting, the description's contribution is modest.

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 (find alternative replacement discs), the resource (discs), and the matching criteria (category, speed, flight profile) plus the algorithm (weighted Euclidean flight distance). This clearly distinguishes it from siblings like compare_discs, get_disc, and search_discs, which have different purposes.

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 provides no guidance on when to use this tool versus the sibling tools. It does not mention alternative tools, conditions for use, or when to avoid it. An agent would need to infer when similarity-based replacement finding is appropriate, which is not stated.

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

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

With no annotations provided, the description carries the full burden. It transparently indicates a read operation ('Retrieve') and discloses the returned data categories, but it does not mention behavior for invalid IDs, missing discs, response format, or potential errors.

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. It conveys the action, the resource, the identifier forms, and the key return fields efficiently.

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

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

For a simple one-parameter lookup, the description supplies the identifier semantics and the main return categories, which is sufficient for most invocations. It lacks explicit error or not-found behavior, but the tool is simple enough that this is a minor 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 the schema already documents the id parameter with examples. The description adds that the id can be numeric or a slug and clarifies the output fields, but it does not add significant new syntax or format details 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 states a specific verb ('Retrieve'), a specific resource ('a specific disc'), and the two accepted identifier forms ('numeric ID or string slug'). It also lists the data returned, which distinguishes it from siblings like search_discs, compare_discs, and find_similar_discs.

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 tool is for fetching a single known disc by ID/slug, which is distinct from sibling tools for searching, comparing, or finding similar discs. However, it does not explicitly state when NOT to use it or name the 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?

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does contribute some: 'Returns up to 50 bounded results with stable IDs and canonical URLs' discloses output limits, determinism, and URL stability — traits not visible in the schema. However, it omits meaningful behaviors such as default result ordering, how the offset parameter interacts with result boundaries, and what happens when no filters are supplied.

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 27-word sentence that front-loads the verb and resource, then compresses the full filter surface into one clause and closes with output characteristics. Every element earns its place; no redundancy with the schema, 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?

The tool has 10 parameters, no output schema, and no annotations, so the description is the only source of return-value information. It covers result bounds and ID/URL stability, but given the offset and limit parameters, it should also state pagination or ordering semantics for an agent to navigate results correctly; the otherwise thorough schema mitigates this gap only for inputs, not outputs.

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 and the description does not need to re-explain parameters. It adds a small amount of semantic value by grouping speed_min/speed_max and stability_min/stability_max into 'speed range' and 'stability score range', which hints that these pairs are meant to be used together, though it does not address the limit/offset pagination pair.

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 a specific verb ('Search and filter') and resource ('disc golf discs'), then enumerates six distinct filter dimensions — text query, brand, category, speed range, stability score range, and flight class. This scoped enumeration makes the tool clearly distinguishable from siblings like get_disc (single fetch), compare_discs, and find_similar_discs, which are not search operations.

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 context — an agent should use this when it needs to discover or filter discs in the catalog — but it never explicitly states when to prefer it over get_disc, compare_discs, or find_similar_discs, nor does it give any exclusions or alternative routing. The 'search and filter' framing makes the primary use case obvious, so this is above 'no guidance' but below clear when/when-not instruction.

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