ByteTrail

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds that the record includes 'every funding round' and external presence (GitHub, Hugging Face), which conveys data depth, but it does not disclose behavior on a missing/ambiguous company or any name-vs-slug resolution rules. Much of the content overlaps what the output schema already reveals.

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 with no filler, structured as a resource followed by a field inventory. It is slightly list-heavy in a way that duplicates the output schema, but nothing is wasted.

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?

Because an output schema exists, the description did not need to enumerate return fields, yet that is where most of its budget went. The genuinely missing pieces for a one-parameter lookup with 0% schema coverage are input format and not-found behavior, leaving it only minimally sufficient.

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%: the single parameter name_or_slug carries only length bounds and no explanation. The description does not clarify whether a display name, a slug, or a partial match is accepted, nor case sensitivity or collision behavior when multiple companies share a name — exactly the meaning the schema fails to supply.

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 startup profile on ByteTrail Market — and enumerates its contents (description, website, location, founders, funding rounds, GitHub/Hugging Face). An agent can tell this is a single-entity lookup rather than a list or search. It stops short of differentiating itself from siblings like search or funding_rounds, which likely return overlapping data.

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 explicit when-to-use or when-not-to-use guidance. Nothing says whether to call search first to discover the slug, or whether funding_rounds is the better choice for cross-company funding analysis, even though both siblings clearly overlap with this tool's scope.

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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive behavior, and a closed-world scope, so the safety profile is covered. The description adds useful context about the data returned (downloads, stars, growth), but it does not mention sorting defaults, pagination, or rate limits.

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 wasted wording. It is efficient, though its terseness contributes to gaps covered under other dimensions rather than being a conciseness flaw.

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 only three optional parameters, an output schema, and full annotations, so the description is minimally sufficient to identify the resource. However, it omits how sorting and limiting work and provides no usage context relative to siblings, leaving clear gaps for a filtered listing 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?

Schema description coverage is only 33%, with only the category parameter documented in the schema. The description mentions metrics that loosely map to sort enum values but does not explain the sort parameter, limit behavior, or default sorting, so it fails to 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 identifies the resource clearly: AI developer tools including frameworks, libraries, and databases, along with the metrics weekly downloads, stars, and growth. It does not explicitly state the operation (list/rank/retrieve) and does not differentiate itself from siblings such as get_tool or trending, which keeps it below 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?

There is no guidance on when to use this tool versus alternatives like get_tool, trending, or search. The description gives no exclusions, prerequisites, or context for selecting this tool over its siblings.

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?

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so safety adds nothing. The description does contribute real behavioral context by mentioning the SEC Form D filing and that `flags` indicate what to verify before trusting a round, which signals data provenance and quality caveats. It says nothing about pagination, caching, or freshness guarantees.

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, front-loaded with the resource and scope, with no filler. The second sentence about `flags` is compact and adds value rather than repeating the title.

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 an output schema present and safety covered by annotations, the description needn't explain return values, and it doesn't. But for a seven-parameter filtering tool with near-zero schema descriptions, the definition leaves the agent guessing about time window, sorting, and amount filtering semantics.

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 14%: only `investor` is documented in the schema, while days, sort, limit, stage, sector and min_amount_usd are bare. The description adds no meaning for any of them (no window semantics, no sort behavior, no amount units), so it fails to compensate for the coverage gap.

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 resource precisely (recent funding rounds of AI and developer-tool startups) and enumerates the payload fields, so an agent knows exactly what it gets back. It does not explicitly say 'list/query' or contrast itself with siblings like latest_news or company, so it stops 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?

There is no statement of when to call this versus latest_news, company, or search, and no exclusions or prerequisites. Only the word 'Recent' hints at a default window, leaving the routing decision 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?

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds little beyond that: it restates what the record contains (which the output schema already defines) and says nothing about behavior on an unknown or malformed id.

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 fragment with no filler, and the payload list is ordered usefully. It is efficient but is a noun phrase rather than a sentence, so the action is never phrased.

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?

Because an output schema exists, the description needn't enumerate return fields, yet that is almost all it does. For a simple one-param lookup this is adequate, but it leaves out the one useful addition: that the arxiv_id should come from a prior search/list 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 coverage is 100% with a single documented arxiv_id (format example, maxLength), so the schema carries the parameter semantics entirely. The description never mentions the id, adding no meaning beyond the schema; 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?

"One paper" plus the enumerated payload (abstract, authors, fields, code/model flag, links) makes clear this fetches a single paper record, which is distinguishable from list-oriented siblings like latest_papers and search. It lacks an explicit verb (fetch/retrieve), so the action is inferred rather than stated.

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 versus search, latest_papers, or trending, and no mention that it requires a known arXiv id. The agent must infer routing from the name alone.

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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed world, so the safety profile is fully covered. What the description adds is only a restatement of the returned field set — which the output schema already supplies — and it says nothing about what happens on a missing or ambiguous name/slug, case sensitivity, or freshness of the metrics.

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?

It is a single short sentence with no filler, so it is concise. However, the front-loaded content is a field list rather than the core action, and the fragmentary syntax makes it read like a schema comment rather than an instruction for an agent.

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 lookup tool with a full output schema, the description spends its only sentence on return fields that the output schema already documents, while omitting the lookup semantics and the not-found behavior an agent needs in order to call 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 description coverage is 0% for the single parameter 'name_or_slug'; the schema gives only type and length bounds. The description never explains that the parameter identifies the tool, that slug and display name are both accepted, or how to obtain a valid slug, so the coverage gap is unmitigated.

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 identifies the resource — a single developer tool — and enumerates the fields it carries (repo, packages, stars, downloads, releases, Rising rank). But it is a bare noun phrase with no verb, so the agent must infer that this is a lookup/retrieval tool, and it never distinguishes itself from the sibling 'dev_tools', which presumably lists many tools.

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 explicit when-to-use guidance. The word 'One' hints at single-record retrieval versus a list, but the description never says to use this instead of 'dev_tools', 'search', or 'trending', nor does it state any preconditions such as the tool needing to already exist in the index.

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?

Annotations already declare readOnly, idempotent, non-destructive, and openWorldHint=false, so the safety profile needs no restating. The description's one real addition is the content-depth caveat ('headline, short excerpt and link (never the full article)'), which usefully sets expectations, but it says nothing about freshness window, result ordering, or empty-result 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?

A single front-loaded sentence with no filler; the source list and output shape are packed efficiently. It is a noun phrase rather than a full statement of action, but nothing is 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?

Rich annotations and an output schema mean the description need not explain return structure or safety, and it does cover content depth. However, for a feed tool with three unlabeled filter parameters, the absence of any guidance on type/region/limit semantics leaves a meaningful 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 carries the burden for type, region, and limit — yet it never mentions filtering by source category, region, or result count. The enum values are visible in the schema, but their meaning (e.g. what 'platforms' or 'mea' cover, whether type filters or expands the source list) is left entirely to inference.

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?

Names the concrete resource (newest posts from AI labs, universities, news sites, engineering blogs, newsletters) and what each item contains, so it is clearly a news/aggregation feed rather than a paper or tool lookup. It does not explicitly contrast itself with siblings like latest_papers, trending, or search, so it stops 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?

Usage is only implied by 'newest' and the source list; there is no statement of when to call this instead of latest_papers, trending, or search. An agent can infer it is the general news feed, but must guess at the boundary with paper/tool feeds.

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?

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds the ordering semantics ('newest first or by ByteTrail's relevance score') and what each result contains, but says nothing about default windowing, result caps, or rate/auth considerations. With an output schema present, the return-value detail is largely redundant.

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 naming source, ordering, and payload with no filler. It is dense but every clause carries information; slightly more structure around the two sort modes would help.

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 filter-list tool with an output schema and full annotation coverage, the definition is adequate but thin: it omits how the time window defaults behave, what 'relevance' is scored on, and when to prefer this over search or trending. Those gaps are small individually but leave the agent guessing on routing.

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 50% and the schema already documents field, category, and has_code. The description only clarifies the sort parameter's two meanings and hints at recency, leaving days, limit, and the ByteTrail field slug concept unelaborated 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 ('New AI papers from arXiv') plus the returned payload (excerpt, authors, links) and the two sort modes. It reads clearly as a listing tool, implicitly distinct from the singular get_paper sibling, though it never names that alternative.

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: 'new AI papers' suggests browsing recent items, while get_paper, search, or trending would cover other intents. No when-to-use or when-not-to-use guidance is given, nor any mention of prerequisites such as a field slug source.

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?

Annotations already declare a safe, idempotent, closed-world read, so the description need not restate that. It does add the useful behavioral detail of which fields are matched (title/abstract vs. name), but leaves out matching semantics (substring, fuzzy, ranking), result ordering, and the 25-item cap 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?

A single front-loaded sentence with no filler, and the searchable scope comes before the field-level detail. The only blemish is the "repos" wording, which introduces a naming mismatch with the schema's `tools` enum value.

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-value description is not required, and the core scope statement is present. What is missing for a three-parameter multi-entity search is the choice between this tool and its siblings plus the meaning of `limit`/`kind` beyond the enum.

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% (only `query` is documented as "words to look for"), so the description must carry more weight. It does implicitly explain the `kind` dimension by listing the searchable entity types, though it says "repos" where the enum says "tools" and gives no meaning for `limit` or the default "all".

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 gives a specific verb ("Search") plus the resources searched (arXiv papers, companies, tools, repos) and the fields matched (title/abstract for papers, name for the rest). That is far more informative than the bare name/title, but it never distinguishes this tool from siblings such as latest_papers, company, or dev_tools.

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 reach for this tool versus the many sibling lookups (get_paper, get_tool, latest_papers, trending). It also never states that the `kind` parameter should be used to narrow scope or when to leave it at the default "all".

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?

Annotations already state readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile needs no restating. The description adds only the vague qualifier "right now" for recency; it does not define the ranking window, what metric "rising" is based on, or sort behavior — so it contributes almost nothing beyond the structured metadata.

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?

It is a single front-loaded sentence with zero filler, which is structurally clean. However, the brevity reads as under-specification rather than discipline, since key qualifiers like timeframe and ranking basis are simply absent.

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 shape needn't be explained, but the definition still leaves the recency window, ranking metric, and the undocumented limit parameter unaddressed. For a tool with five distinct modes and sibling overlap, that is not enough to invoke confidently.

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 50%: the kind enum is richly documented in the schema itself, while limit has no description anywhere. "By kind" merely restates the required enum parameter and adds no new meaning, and the undocumented limit (default 10, max 30) is left entirely to inference.

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?

"What's rising in AI right now, by kind" communicates the resource (trending AI items) and that results are partitioned by a kind selector, so the purpose is inferable. But the verb is implicit (list/get) and it never distinguishes itself from overlapping siblings like latest_news, latest_papers, dev_tools, or search, leaving the agent to guess which trending-adjacent surface applies.

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 or when-not-to-use guidance, and no alternative is named even though latest_news, latest_papers, and dev_tools clearly overlap with several of the supported kinds. The agent gets no rule for choosing this tool over those siblings.

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