Jump on the Trend

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds that the payload is full page text rather than structured metadata, but says nothing about truncation, size limits, or what happens with an invalid 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?

One short sentence with the resource and the id-source constraint front-loaded and no filler. 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 one-parameter read tool with rich annotations and no output schema, the description covers what it returns and where the argument comes from. Only edge-case behavior such as oversized pages or invalid ids is left unstated, which 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 0% and the single parameter is just typed as string, so the description carries the burden. It does this by identifying the id as the one returned by search, giving the agent provenance and a way to obtain a valid value.

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?

"Fetch one trend's full page text" gives a specific verb and resource and scopes the result to a single trend, which separates it from list-style siblings like top_trends or search_trends. It does not distinguish itself from get_trend, the closest-sounding sibling, so an agent must still infer which of the two returns metadata versus page text.

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?

"by the id search returned" establishes a clear prerequisite workflow: call search first, then fetch with a returned id. There are no explicit exclusions or comparisons to get_trend, so the guidance is clear but not complete.

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 openWorldHint=false, so the safety profile is covered. The description's real contribution is enumerating response contents (clip, sound, cast, versions/prices, FAQ, preview link), which is valuable because no output schema exists, but it says nothing about behavior when the trend is not found or what errors look like.

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, which is good structure, but the tail drifts into marketing-style padding ('ideas for who to cast, common questions, and the page link where the person adds their photo for a free preview'). The content inventory could be tightened without losing information.

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, the description carries the response-shape burden and does so thoroughly, so an agent knows what it will get back from a known-identifier lookup. Missing pieces are minor: no mention of not-found behavior and no routing against the many sibling tools.

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 schema already explains that 'trend' accepts an id (slug), a name, or a page URL. The description adds no additional meaning about identifier resolution or precedence between the three accepted forms, so it earns only the baseline.

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 opening clause 'Everything about one trend' plus the inventory of contents makes it clear this is a full-detail retrieval for a single trend, which distinguishes it from list/search siblings like list_categories, search_trends, and top_trends. It never names an explicit verb ('retrieve', 'return'), so the action is inferred rather than stated, and the sibling 'fetch' is not differentiated.

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 sibling is named despite having seven alternatives including search_trends, fetch, and top_trends. An agent must infer from 'one trend' that this is the detail lookup for a known trend versus the discovery tools, which is a reasonable but unstated 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is fully covered. The description adds that the content includes the free tier and 'today's prices', hinting the pricing data is current rather than static, which is modest but real added context.

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 lists the three content areas with no filler. Slightly awkward phrasing ('Jump on the Trend' brand insertion) but nothing 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?

For a zero-parameter, no-output-schema informational tool, the description covers what the returned content will address (process, free tier, prices). An agent has enough to decide to call it and what to expect.

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, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description correctly implies no input is needed.

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 clearly: an explainer covering how video creation works, what's free, and current prices. That distinguishes it from the data-fetching siblings (search, top_trends, get_trend), though the verb is implicit rather than stated as 'returns' or 'explains'.

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 — an agent can infer this is the tool for pricing or 'how does this work' questions, but the description never says when to call it versus the sibling tools or that it takes no arguments. No explicit exclusions or alternatives 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive and openWorldHint=false, so the safety profile is covered. The description adds the useful behavioral detail that each entry carries an associated trend count, but says nothing about ordering, pagination, or whether the taxonomy is fixed — minor given the zero-parameter shape.

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 that front-loads the resource before the payload detail, with concrete examples. The phrasing 'seasons in season...' and the trailing ellipsis are slightly muddled, costing a point on polish rather than 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?

With no parameters and no output schema, the description carries the burden of describing the return value, and it does so: a list of categories each with a trend count. For a simple enumeration tool this is close to sufficient, lacking only notes on ordering or stability of the list.

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 no parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description correctly implies no input is required.

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 (categories that trends are filed under) and the payload (each category plus its trend count), with concrete examples like pets, dance, memes. It does not explicitly distinguish itself from siblings such as search_trends or top_trends, though the noun 'categories' versus 'trends' does most of the work implicitly.

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 mention of alternatives. An agent must infer that this is the discovery step to run before filtering by category elsewhere, which is plausible but 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?

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful behavior by stating the return shape (a list of ids), which matters because no output schema exists. It says nothing about result limits, ranking, or empty-result behavior, so it remains a middling score.

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 short sentences with no filler, and the primary purpose is front-loaded ahead of the follow-up chaining hint. 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?

For a one-parameter read-only search with no output schema, the description covers the essentials of what it does and what it returns. It falls short on query formatting and on how results differ from the sibling `search_trends`, which an agent must resolve to invoke it well.

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 `query` parameter is typed only as a string with no explanation. The description does not compensate at all — it never says whether the query is a keyword, a phrase, a category name, or natural language, which is exactly the ambiguity the agent needs resolved.

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 concrete verb+resource: "Search Jump on the Trend's AI video trends." That is more specific than the bare title "Search," though it does not distinguish this tool from the sibling `search_trends`, which reads as an overlapping capability.

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 sentence "Returns ids to pass to fetch" implies a chained workflow and effectively tells the agent to call this before `fetch`. However, there is no guidance on when to prefer this over the similarly named `search_trends`, nor any exclusions or prerequisites.

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 useful behavior beyond that by listing what each result contains (name, scene description, who can star, length, price, page link) and defining the empty-query case. It does not mention ordering, pagination, or how results are ranked, and never mentions the limit cap.

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?

Four compact sentences, front-loaded with the capability, then filters, then return contents, then the empty-query edge case. Every sentence carries information, though the match-surface list mildly duplicates the query parameter's own schema description.

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, the description correctly spends a sentence on return fields, and it documents the zero-required-params edge case (empty query). Only the limit parameter's behavior and result ordering are left implicit, which is a minor gap for a simple search 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 coverage is 75% and the description largely restates the query and who filters rather than extending them. The parenthetical query examples ('locker room', 'dog bartender', 'christmas', 'couple dance') do add real search-intent guidance, but the limit parameter (default 8, max 25) is undocumented in both schema and description. 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?

States a specific verb and resource ('Search ... live AI video trends and templates') and enumerates the match surfaces (name, meme, song, scene, topic) with concrete examples. It is clear what the tool does, but it does not distinguish itself from siblings like top_trends or suggest_trend, despite the 'empty query lists top trends' overlap.

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?

Gives clear usage context: search by keyword with optional category/who filters, and an explicit special case that an empty query returns the current top trends. It stops short of naming alternatives (e.g. top_trends for browsing, list_categories for discovering category ids) or stating when not to use it.

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 the write-ish, non-destructive, idempotent profile, and the description adds context annotations cannot: the submission is human-reviewed and 'nothing is promised,' which sets expectations about delayed, uncertain outcomes. It stops short of saying what the call returns or how the review is communicated back.

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?

Three short sentences, each doing distinct work: action, outcome uncertainty, and usage constraint. The routing rule is front-loaded at the end where it is most actionable, with 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?

For a simple one-param submission tool with no output schema, the description covers what is submitted, who handles it, and when to use it. The only real gap is post-submission behavior (confirmation, rejection), which is minor given the stated no-promise policy.

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 single url parameter is already documented with the same platform list, so the description adds essentially nothing beyond the schema. Baseline 3 is appropriate for a one-parameter tool whose schema does the work.

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 ('Send the team a ... link to a trend that isn't on Jump on the Trend yet') and names the accepted sources (TikTok, Instagram, YouTube). It is clearly distinguishable from siblings like search_trends or get_trend, which retrieve rather than submit.

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?

Explicitly routes the agent: 'Only use it when the person wants a trend that search_trends didn't find.' That is a named alternative plus the condition that selects this tool, so no inference is required.

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 openWorldHint=false, so the safety profile is covered. The description usefully adds ordering ('best first') and the hot/rising/new framing, but never explains what 'best' is measured by, how many items come back, or how the three groupings are returned.

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 compact sentence, front-loaded with the resource and ordering. Slightly redundant phrasing ('right now' against 'this week') but nothing extraneous enough to warrant trimming.

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-only list tool with no output schema, the description should convey the shape of the result — whether 'what's hot, rising and new' are tags on each trend or separate result sections. It leaves that and the meaning of 'best' unresolved, so it is adequate but incomplete.

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 'limit' parameter, and the description says nothing about it — not the default of 10, the cap of 25, or what limiting does to the result set. The description therefore fails to compensate for the schema 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?

States a specific resource (trends on 'Jump on the Trend') and ordering ('best first'), plus a categorization of hot/rising/new. It is distinguishable from siblings like get_trend (single) and search_trends (query-based), though the notion of 'doing best' and the time window ('right now' vs 'this week') remain undefined.

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 use this versus search_trends, list_categories, or search. Usage as a browse/discovery entry point is only implied by 'top trends right now'; there are no exclusions or prerequisites.

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