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

With no annotations, the description carries the full burden and does disclose meaningful behavior: data comes live from the Hub API and falls back to a nightly top-25 list when offline. It does not cover auth requirements, rate limits, or what happens at the limit boundary, so it is partial but genuinely informative.

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

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

Front-loaded with the core purpose, then layers in the sort option, relation filter, data-source behavior, and an example. Every sentence carries information and there is no 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?

For a four-parameter tool with no annotations and no output schema, the description covers purpose, relation, sort, and data fallback reasonably well. It still omits limit semantics and any indication of the return shape, which the absent output schema means the description could have supplied.

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%, so the description must compensate. It enumerates the accepted relation values (finetune, adapter, quantized, merge) and hints at sort alternatives via sort="likes", but leaves the id and limit parameters unexplained and never states the default sort.

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: 'Direct descendants of a model', which is concrete and distinguishable from a generic listing. However, it does not explicitly differentiate itself from close siblings like 'family' or 'lineage', leaving the agent to infer the boundary.

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

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

Usage is implied through the example invocation and the relation filter, giving the agent a reasonable sense of when to call it. There is no explicit when-to-use/when-not guidance or comparison against the siblings family, lineage, or search.

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 response content fairly well (totals, relation breakdown, organizations), but says nothing about read-only semantics, cost, pagination, or error behavior for an unknown family name.

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 leads with the resource and its concrete examples before listing returned content. No filler, though the sentence-fragment form (no verb) and the dense trailing list slightly reduce crispness.

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

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

With no output schema and no annotations, the description must cover both scope and behavior. It adequately conveys what data comes back, but leaves the read-only assumption, identifier-matching rules, and the relationship to sibling tools unstated.

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

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

Schema description coverage is 0% for the single 'name' parameter, so the description must compensate. It partially does by giving concrete examples ('Qwen2.5', 'Llama 3.1', 'FLUX.1'), which conveys the expected identifier format, but it never states matching rules (exact string, case sensitivity, alias handling).

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

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

The description names a specific resource (a single model family) and enumerates the payload it returns: totals, relation breakdown, roots, organizations, and top models by descendants. That is concrete enough for an agent to know what it gets, but the verb is only implied and there is no differentiation from siblings like 'lineage' or 'children', which overlap with the 'roots'/'descendants' content.

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

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

There is no when-to-use guidance and no exclusions. Siblings 'lineage', 'children', 'stats' and 'leaderboard' all plausibly cover model families, yet the description never states when to pick this tool over them.

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 behavioral burden. It never states that this is a read-only query, how results are ordered, whether pagination is needed for large result sets, or any auth/rate constraints; the only behavioral hint is the filtering semantics implied by 'finetune (filters out LoRA and quantization noise)'.

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

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

The purpose is front-loaded in the first sentence, followed by a compact enumeration of kind values. It is dense but every clause carries information, with no filler or repetition.

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?

An output schema exists, so return values need not be described, and the dominant parameter (kind) is fully covered. What is missing is routing guidance relative to the five siblings and any note on ordering or result-size behavior, which leaves the agent to guess when this tool is the right pick.

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 0%, so the description must compensate, and it does so thoroughly for the key parameter: every kind value is defined with concrete meaning (all_time, 90d, finetune, families, orgs). limit and offset are left unexplained, but their standard pagination meaning is largely self-evident from the names.

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

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

The description names a specific resource (base models on the Hub) and a specific ranking criterion (most-descended), so an agent can tell this is a ranked-listing tool rather than a lookup. It does not, however, distinguish itself from close siblings such as stats, family, or lineage, which an agent must infer from name alone.

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 statement of when to use this tool versus the alternatives (stats, family, lineage, search). The kind enumeration describes modes of the tool itself, not selection criteria against siblings, and no prerequisites or exclusions 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 load and does well: it discloses a live walk of `base_model` metadata from the Hub, first-parent-at-each-step semantics, that merges expose all parents in `parents`, that each hop carries a relation type (finetune, adapter, quantized, merge), and that descendant counts come from a nightly build. Auth requirements and rate limits remain undisclosed.

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

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

Front-loaded with the one-line purpose, followed by mechanics and a concrete example in three short blocks. Little waste, though the merge/parents parenthetical is dense.

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

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

For a two-parameter read tool with no annotations and no output schema, the description covers what the return chain contains (hops with relation and descendant counts) and where the data comes from. The only real gap is the undocumented `max_depth` behavior.

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 0%, so the description must compensate. It illustrates `id` with a concrete example, which is useful, but `max_depth` (default 12) is never explained in the description even though it governs how far up the chain the walk goes.

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

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

The description names a specific resource and scope: the ancestry chain of a Hugging Face model plus its own descendant count. An agent can tell this is about upward lineage rather than listing children, though sibling names (children, family) are never cited to sharpen the boundary.

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

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

Usage is only implied via the example call `lineage(id="...")`. There is no statement of when to prefer this over `children` or `family`, nor any prerequisite or exclusion, so the agent must infer routing.

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

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

With no annotations, the description carries the full burden and does disclose three real behavioral traits: case-insensitive substring matching, result ordering ('most descended first'), and a scope limitation ('covers the 88k models that have at least one declared child'), which tells the agent childless models are excluded. It does not cover pagination or the limit cap, but the disclosures it does make are meaningful.

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 tight sentences, front-loaded with the core search semantics followed by the scope caveat. Nothing is redundant and no sentence is 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?

An output schema exists, so return values need not be described, and the search semantics are adequately covered. However, for a bare read-search with no annotations, the absence of any routing guidance against the five related sibling tools leaves a real 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 description coverage is 0%, so the description must compensate. It explains what 'query' matches against (ids, case-insensitive substring) but says nothing about 'limit' — the schema shows only a bare integer with default 15, and the description never states that it caps the number of returned models.

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 concrete verb ('Find') and a precisely scoped resource ('models with descendants whose id contains the query'), including the match and ordering semantics. It is clear in isolation, but never distinguishes itself from siblings like family, lineage, or children, which is the one thing that would separate it from the closest alternatives.

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 no when-to-use or when-not-to-use guidance and does not mention any of the sibling tools (family, lineage, children, leaderboard, stats). An agent must infer from the name alone whether this is the right tool versus lineage or children.

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 supplied, so the description carries the full behavioral burden. It lists the metric categories but does not disclose read-only status, permissions, what 'current build' resolves to, or any execution constraints.

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 names the output and enumerates the metrics with no wasted words. Structure is efficient 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?

For a zero-parameter tool with no output schema or annotations, the description covers what is returned at a high level. However, it leaves open what 'current build' means and omits behavioral basics such as read-only nature, making it adequate but with clear gaps.

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

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

The tool takes zero parameters and the input schema is empty, so the baseline is 4. The description neither adds nor contradicts parameter information, which is appropriate given there are no parameters.

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

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

States a clear purpose: returning headline numbers for the current build, with enumerated metrics (models tracked, links, parents, roots, families, dates). It does not explicitly distinguish itself from siblings such as leaderboard, so it falls short of a 5.

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

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

No when-to-use guidance, prerequisites, or alternatives are provided. The phrase 'headline numbers' implies a summary use case, but the description never states when this tool should be chosen over siblings.

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