TheYtree

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

With no annotations, the description carries the behavioral burden, and it does disclose the key trait: only direct children are returned, not the whole lineage, and limit filters to the largest subclades. It omits output-shape details, but for a read-style getter this is reasonably 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 English text is short, front-loaded, and states the core behavior before the limit tip. The bilingual Chinese repetition adds length without new information, but it is a consistent translation rather than padding.

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

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

The tool is simple, both parameters are fully described, and the description covers the main behavior and the optional limit. It does not mention the return value shape, but 'get children' sufficiently implies a list for an agent to invoke 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 coverage is 100%, so the schema already documents both parameters, including the name-or-hid acceptance and the default-all behavior for limit. The description's mention of 'N largest subclades' reinforces the schema without adding new meaning.

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 and resource: 'Get the direct children of a haplogroup,' and clarifies the intended level-by-level traversal. This distinguishes it from sibling tools like subtree_haplogroups or list_haplogroups, which cover broader or different scopes.

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 frames when to use the tool: for level-by-level traversal, and explicitly calls out the optional limit for restricting to the N largest subclades. It does not name alternatives or state when not to use it, so it stops short of full exclusion 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 provided, the description carries the full burden of behavioral disclosure. It does describe the output (summary, auth, dataset size, tool list) but does not explicitly state whether the operation is read-only, whether authentication is required to call this endpoint, or any side effects. The description is not misleading, but it leaves these behavioral traits implied rather than explicit. Given the lack of annotations, this is a moderate gap, so a 3 is warranted.

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 two concise sentences, with the primary purpose front-loaded in the first sentence. The English version is efficient, and the Chinese translation adds no redundancy. Every element contributes to understanding the tool's function and return value. No filler or unnecessary detail is present.

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 has no parameters, no output schema, and no annotations, the description must convey what the tool returns. It does so by listing the four components of the metadata. It does not mention format or details of the response, but for a metadata endpoint this is adequate. An agent can decide when to call it and what to expect. The description is complete enough for the tool's simplicity.

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 is empty with zero parameters, so schema coverage is 100% by default. The rubric sets a baseline of 4 for tools with 0 parameters. The description does not need to add parameter semantics because there are none. It does not introduce any confusion, and the baseline applies. A score of 4 reflects that the description fully satisfies the parameter dimension for a parameterless tool.

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 ('Get'), a clear resource ('service meta'), and enumerates the exact contents (summary, auth, dataset size, tool list). It is unambiguous and clearly distinct from sibling tools that focus on haplogroup data retrieval, so an agent can immediately understand what this tool does and why it differs.

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?

While the description does not explicitly state 'use this for service metadata and not for haplogroup queries', the purpose is so distinct that context makes the usage clear. There are no exclusions or alternatives mentioned, but the separation from siblings is strong enough that an agent would not confuse it. This qualifies as clear context with no explicit exclusions, so a 4 is appropriate.

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?

There are no annotations, so the description itself must convey the operation's behavior. It does indicate a read-style exact lookup by identifier and mentions the three accepted identifier forms. However, it does not disclose return format, not-found behavior, or whether the identifier matching is exact/case-insensitive, leaving some behavioral ambiguity.

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 very compact: a single English sentence and its Chinese equivalent. It front-loads the core operation and key identifier variants, though the bilingual duplication is somewhat redundant.

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 is mostly adequate, but it omits return-value details, error/not-found handling, and any rationale for when to use this versus related get/list/resolve tools. Since there is no output schema and no annotations, a bit more contextual guidance would improve completeness.

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

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

The input schema only provides the parameter name 'name' with no description, so the schema offers almost no semantic value. The description compensates meaningfully by explaining that the single parameter can accept a haplogroup name, hid, or SNP, which is essential for correct invocation.

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 operation ('Get'), the resource ('a single haplogroup'), and the accepted lookup keys ('name / hid / SNP'). It distinguishes itself from list/tree siblings by emphasizing 'single', though it does not explicitly contrast with get_haplogroup_lineage or get_haplogroup_mutations.

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 guidance about when to choose this tool over the many siblings such as list_haplogroups, children_haplogroups, subtree_haplogroups, resolve_snp, or get_haplogroup_lineage. The word 'single' implies exact lookup, but no when-to-use or when-not-to-use conditions are 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?

The description adds useful behavioral detail beyond the schema by explaining what limit does and clarifying inclusive behavior ('node + its parent'). With no annotations, the full burden falls on the description; it covers core behavior but omits output ordering, return format, or behavior for unknown haplogroups, so it 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?

The core information is front-loaded and expressed in two sentences. The bilingual duplication adds length without new information, slightly reducing conciseness, but the structure remains tight and readable.

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 read tool with no output schema and no annotations, the description gives enough to make a basic call, but it does not fully describe the expected return shape or edge-case behavior. An agent would likely call correctly, but the missing return-format detail leaves some ambiguity.

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 still adds value by illustrating limit semantics with a concrete example. It clarifies that limit=2 means the starting node and its direct parent, which is more precise than the schema's 'most recent N levels'.

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 the exact operation ('Get the lineage chain from a haplogroup up to ROOT') and clearly differentiates this from sibling tools like children_haplogroups or subtree_haplogroups by focusing on the upward path to ROOT. The verb-resource pair is specific and immediately actionable.

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 guidance for the limit parameter ('limit=2 for the node + its parent'), which helps with invocation. However, it does not explicitly state when to choose this tool over siblings or when not to use it, so the selection guidance is mostly implied by the purpose rather than 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It makes the read/list nature and Y-tree scope clear, but it does not disclose pagination behavior, what happens with unknown haplogroup names, or whether results are limited to observed mutations, especially given parameters like include_under_observation and per_page exist.

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 short and front-loaded, but the Chinese sentence is a direct duplicate of the English sentence. While not bloated, it does not strictly earn its place for an automated agent, making it slightly less than optimally concise.

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 six parameters, no output schema, and no annotations, the description is too thin to be complete. It leaves out when to use it, what the returned fields represent, how pagination works, and how compact/fields change the response, so an agent cannot confidently invoke it beyond the trivial default call.

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

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

Schema description coverage is only 33%, so the description must compensate for undocumented parameters like name, page, and include_under_observation. It does not: it only implies 'name' is a haplogroup identifier and gives no guidance on compact, fields, pagination, or the under-observation flag.

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 resource ('haplogroup defining equivalent mutations'), and explicitly scopes it to the paternal/Y tree. This distinguishes it from sibling tools like get_haplogroup_lineage or children_haplogroups and makes its purpose immediately obvious.

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 guidance on when to use this tool versus alternatives such as get_haplogroup, resolve_snp, or get_haplogroup_lineage. The phrase 'paternal / Y tree only' implies an exclusion of mtDNA but does not explain when this is the right choice or when a sibling tool should be used.

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 a useful behavioral trait—stable ordering for full pagination (recommending order=name)—which goes beyond the schema. However, it does not mention other behaviors such as read-only nature, outcome on no matches, or any limits/rates beyond the schema's max per_page. For a listing tool, the critical safety profile is implied but not explicit.

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 two compact sentences (English + Chinese) with zero fluff. The purpose is front-loaded, followed by a concrete pagination tip. Every word contributes to the tool's understanding, making it highly efficient relative to its length.

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?

This tool has 8 parameters, none required, no output schema, and low schema coverage. Yet the description omits explanations for most parameters, default behavior, ordering implications, or how it relates to sibling tools. An agent would face significant uncertainty about invoking it correctly, especially for non-obvious parameters like level and order_dir. The description is far too sparse for this complexity.

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

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

Schema description coverage is only 38% (only name, parent, exclude_mf have descriptions). The tool description does not compensate for the undocumented parameters like page, level, order, per_page, and order_dir; it only recommends order=name for pagination, which is a usage hint rather than an explanation of the parameter's meaning. With this low coverage, the description should have at least outlined the remaining parameters, but it does not.

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 searches or lists paternal haplogroups by fuzzy name and/or parent, with a specific resource and filter criteria. It also mentions stable ordering for full pagination. While it doesn't explicitly name siblings, the verb+resource+filter combination makes the purpose unambiguous and distinct from children_haplogroups or subtree_haplogroups.

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 general search/list of haplogroups with filtering and pagination needs, but it does not explicitly contrast with alternative sibling tools (e.g., children_haplogroups, subtree_haplogroups) or state when NOT to use this tool. The pagination note hints at one scenario, but exclusions and routing are left to 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?

With no annotations, the description carries the full burden. It discloses that merged-name variants are supported and that the tool maps to a haplogroup, but it does not describe behavior on invalid names, naming conventions, or output shape. This is acceptable but lean for a lookup 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 short and front-loaded, with the primary purpose stated first. The bilingual repeat adds a little redundancy but remains compact and does not obscure meaning.

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

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

For a simple one-parameter tool, the description states the core function, but it lacks return-format details and does not situate the tool among its siblings, especially the near-identical plural resolve_snps. An agent may struggle to know when to pick this over resolve_snps.

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 0%, and the description barely adds meaning beyond the schema: 'SNP name' only restates the parameter name 'snpname.' No format examples, accepted naming styles (e.g., rsIDs), or merged-name syntax are provided, so the description does not compensate for the low 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 a specific action — resolving a SNP name to its haplogroup — and mentions returning equivalent names with merged-name variant support. It is distinct enough from siblings by its singular focus, though it does not explicitly contrast with resolve_snps.

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 guidance is given about when to use this tool versus resolve_snps or other sibling tools. The singular 'a SNP name' hints at one-name-only usage, but the plural sibling resolve_snps is never mentioned, nor are any exclusions or conditions described.

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 batch limit (200) but does not mention error handling, behavior on invalid SNP names, or whether it is read-only. For a lookup tool this is acceptable but not rich. It adds the limit constraint, which is useful, but otherwise lacks behavioral detail.

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 compact, with the core action and limit front-loaded. The bilingual duplication is not wasteful since it's a single line, and every word adds value. 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?

Given the tool's simplicity and the rich schema, the description is mostly adequate. However, there is no output schema and the description doesn't specify the return format or error behavior, which an agent might need for batch results. It's not missing critical info for invocation, but could be more complete for downstream handling.

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% for the single parameter, so the schema already defines the array. The description adds a crucial constraint not in the schema: the ≤200 limit per call. This extra semantic guidance pushes it above the baseline of 3.

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 it batch-resolves SNP names to haplogroups, with a specific limit of 200. It distinguishes itself from the sibling resolve_snp (singular) by being a batch operation for reading a whole panel, so an agent can easily tell them apart.

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 provides a usage context ('for reading a whole Y-SNP panel') that implies when to choose this tool over resolve_snp. It doesn't explicitly say 'use resolve_snp for single SNP', but the sibling naming and the batch context make the routing clear. Slight lack of explicit exclusions, hence 4.

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 discloses meaningful execution behavior: default 6 levels, full expansion when root endcounts<=600, max_depth override, and has_children on truncated boundaries. This goes well beyond a generic 'get' and helps predict response shape, though it does not describe full node 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?

The English description is front-loaded and compact, with each behavioral detail earning its place. The bilingual repetition adds redundancy but is not excessive and aids non-English callers.

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 covers the important runtime semantics, but with no output schema it stops short of describing the full return shape; it only mentions the has_children boundary flag. This is adequate for invocation but not fully complete for predicting the entire response.

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 already documents name, default 6, and unlimited expansion when endcounts<=600. The description reinforces these semantics (max_depth overrides, small-branch expansion) 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?

States a specific verb+resource ('Get a haplogroup subtree') and immediately defines its scope via level counts and expansion rules. The subtree concept differentiates it from sibling tools like children_haplogroups (single-level) and get_haplogroup (single node), even without naming them.

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 explicit guidance on when to choose this over sibling alternatives; no exclusions or criteria are given. The behavior (defaults, expansion) is described, but the agent must infer that this is the tool for recursive trees versus children_haplogroups.

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