HotRepo

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety and scope profile is covered. The description adds useful composition details about what the report contains, but it does not mention data freshness, pagination, or other operational caveats; the output schema covers the return 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?

The description is a single front-loaded sentence that states the purpose first and then enumerates the report sections without filler. Every phrase contributes to identifying what the monthly report includes.

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 read-only, two-parameter report tool with full schema coverage and an output schema, the description is largely complete: it says what the report contains and where the data comes from. It could do slightly more to distinguish itself operationally from daily trending, but no critical information is missing.

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 both parameters ('lang' and 'month') are fully documented in the schema. The description only implies date-range scoping with 'during a month' and adds no format or behavior detail beyond what the schema already provides, so 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?

The description uses a specific verb ('Get') and resource ('HotRepo monthly report'), then enumerates the report contents: top star gainers on the daily trending board, notable new repositories, per-topic leaders, and an editorial introduction. This clearly distinguishes the monthly aggregate from sibling tools like get_trending and get_topic.

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 phrase 'during a month' implies this tool is for monthly aggregated reports rather than daily trending, but the description never explicitly names alternatives or states when not to use it. The agent must infer the comparison with get_trending and get_topic.

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?

While annotations confirm it is a read-only operation, the description adds specific behavioral details about the data content, such as defining what `best_github_rank_that_day` represents and its null period (before 2026-10-24). This helps the agent interpret specific data structures.

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 dense and highly detailed. While every word is functionally useful in providing context, the single, lengthy paragraph is less concise than an enumerated list might be.

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 deals with complex, multi-part data (Markdown, historical rankings, external threads). The description successfully covers the scope, content, and inherent limitations of this complex resource, making it highly complete.

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?

Since schema coverage is 100%, the baseline is high. The description adds semantic value by defining the scope of the review—it pertains to the 'all-languages board' and defines how the `fork_root` field functions, providing context not fully captured by the schema definitions.

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 defines the purpose: reading the full HotRepo review of a repository. It goes beyond a generic retrieval by specifying the complex set of data included (Markdown review, stats, daily trending history, HN threads).

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

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

The description provides a critical usage constraint: 'Only repositories that have trended and been reviewed are available.' This informs the user about the limitations of the dataset without listing alternatives, which is sufficient 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context that results are reviewed repositories ordered by recent trending, but it does not explain pagination, what 'reviewed' means, or how lang affects results.

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 wasted language. It communicates scope and ordering efficiently.

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

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

The tool is simple, has annotations, and has an output schema, so the description does not need to explain return values. It is nearly complete for a filtered-list tool, though it could say more about topic lookup or language 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 coverage is 67%, with slug and lang described in the schema while limit is undocumented. The description reinforces the topic scoping via slug but adds little beyond the schema for lang or limit.

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 and resource: it lists reviewed repositories within one topic, ordered by recent trending. It is clear enough to distinguish from get_trending or search_repos, though it does not explicitly name those siblings.

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 by 'in one topic' and the ordering behavior, but the description gives no explicit when-to-use guidance or exclusions versus list_topics, get_trending, or search_repos.

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 only declare readOnlyHint and openWorldHint; the description goes far beyond by disclosing data-availability rules (boards from 2026-11-01 list only reviewed repos; earlier archived days may include unreviewed items), null semantics for rank fields, and the caveat that GitHub's own ordering differs from the returned rank. It also explains exactly how derived metrics are computed (stars_gained as an increment between timestamps, stars_per_hour over actual window hours, avg_stars_per_day for legacy records) and what previous_rank compares against per board type.

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 purpose is correctly front-loaded in the first sentence, but the remainder is a dense, unstructured block that mixes input semantics, output-field semantics, and edge cases in one paragraph. Since an output schema already exists, several sentences explaining return fields are longer than needed and would read better as a short list of caveats.

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 annotations, a 100% covered schema, and an output schema, the description covers the remaining burden well: board availability windows, ranking caveats, null cases, and metric derivations. The only material gap is guidance on choosing this tool over siblings such as search_repos or get_repo, which an agent must still infer.

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 both enums are documented, so the schema already carries the parameter burden — baseline 3 applies. The description reinforces date/period meaning ('for one UTC day', board-specific behavior for 'new'), but the bulk of its extra detail concerns output fields (best_github_rank_that_day vs best_github_daily_rank, previous_board_at, stars_per_hour) rather than adding input-parameter 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 opening sentence names a specific verb and resource ('Get a HotRepo trending board'), states the exact scope (repositories on GitHub Trending or the new-repository board for one UTC day), the ranking basis (stars gained, or measured Stars/hour), and the payload (each with a one-line review). No sibling tool (get_repo, search_repos, get_topic, get_monthly_report) returns ranked daily boards, so the distinction is unambiguous without naming an 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 implied by the scope statement rather than stated: an agent can infer this is the tool for 'what is trending on day X / in language Y', and the period semantics (daily/weekly/monthly/new) are explained. But there is no explicit when-to-use or when-not-to-use guidance, and no routing to search_repos or get_repo for non-board lookups.

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=true and openWorldHint=false, so safety is covered. The description adds real behavioral context beyond them: result ordering (most recent first), inclusion of a one-line review only when published, and the constraint that favorites cannot be created via this server.

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 tight sentences, front-loaded with the core operation, then the differentiation pointer, then the scope caveat. No sentence is redundant and none of it repeats the schema or annotations.

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 explained; the description still notes the review snippet is conditional on publication. With only two optional parameters and clear read-only annotations, an agent has everything needed to call this 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 only 50% (lang is documented, limit is not described beyond its default/bounds), and the description adds nothing about either parameter's effect. The 'en/zh' enum is only implicitly hinted at by 'one-line review'; an agent gets no clarification of how lang changes output or how limit interacts with pagination.

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 ('List the repositories...favorited'), plus ordering ('most recently favorited first') and returned content ('one-line review when published'). It also distinguishes itself from the sibling get_repo by naming the alternative for full reviews, so an agent can choose without opening schemas.

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 to get_repo for the full review and clarifies a scope boundary: favorites are added on the website, not through this server (so the agent shouldn't look for a write path). It lacks explicit guidance on when to prefer search_repos/list_topics over enumerating favorites, but the context is clear.

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=true and openWorldHint=false, so the safety profile is clear. The description adds useful context beyond them: results include project counts, and every reviewed project maps to exactly one topic, which tells the agent the counts partition the corpus. It says nothing about ordering, pagination, or whether empty topics appear.

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, front-loaded with the verb and resource. The parenthetical definition of a topic is dense but does real work by explaining the taxonomy; it could have been split out for readability.

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 needn't be explained, and the description is sufficient for a simple read-only enumeration with one optional param. Only the ordering and pagination behavior of the list are left 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?

There is a single optional parameter, and the schema documents it fully at 100% coverage ('Language of reviews and topic names') with an enum of en/zh. The description adds no further meaning about localization scope, so the baseline of 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?

States a specific verb and resource ('List HotRepo's topics') and defines what a topic is in domain terms, including that the result carries per-topic project counts. It never names the nearest sibling, get_topic, so an agent must infer that this returns the collection while get_topic returns one entry.

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 listing semantics imply usage — call this to enumerate topics before drilling in with get_topic — but the description never states when to choose it over get_topic or get_trending. There are no exclusions, prerequisites, or guidance about when this call is worthwhile.

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=true and openWorldHint=false, so safety is covered. The description adds two things beyond them: the corpus is limited to HotRepo-reviewed repos (a real coverage constraint), and results are ordered newest-review-first. It leaves pagination/cursor behavior unstated, but the tool has an output schema to carry return 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?

Two short sentences, zero filler, with the what/scope/ordering front-loaded before the sibling hand-off. Every clause carries 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 an output schema present and annotations carrying the safety profile, the description only needs to convey scope and differentiation, which it does. It would be complete at 5 if it hinted at query/topic filtering, the primary discovery path for this 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 75% and the schema already explains query semantics (all words must match, empty = newest reviews), lang, and topic slug sourcing from list_topics. The description adds no parameter-level detail of its own, so it sits at the baseline rather than earning above it.

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 ("search repositories"), scopes the corpus ("that HotRepo has reviewed"), and gives the ordering ("newest reviews first"). It also explicitly names get_repo as the detail-fetch sibling, so an agent can separate the two without opening schemas.

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 to "get_repo for the full review," which is a real use/use-instead pair. It does not address the other ways to discover repos in this server (get_trending, get_topic, list_topics), so the sibling routing is only partially covered.

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