Pandawed — Chinese flashcards (HSK)

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

With no annotations, the description carries the burden itself and does disclose the key trait: it returns the static text of pandawed.ru/o-proekte/, which tells an agent this is a fixed read-only informational page, not a queryable resource. It doesn't state the language or format of the returned text, but for a zero-parameter static page that omission is small.

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 sentence front-loads the core question it answers ('what is Pandaved and what can it do'), then lists coverage, then names the source page. The feature enumeration is listy but each item tells the agent what topics are answerable, so it earns its space.

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, no-parameter, no-output-schema informational tool, the description covers what the tool is, what content it contains, and where it comes from — enough to call it correctly. Only minor gaps remain, such as return format and language.

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 are zero parameters, so the baseline is 4; the schema fully covers the empty object and the description correctly implies no input is needed. Nothing about parameters is misrepresented or left ambiguous.

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 a specific resource — the Pandaved about page — and enumerates the feature areas it covers (tone-color cards, sets/folders, class modes, spaced repetition, dictionary, account), so an agent knows exactly what content it gets. It doesn't explicitly contrast itself with siblings like get_article, but the static 'about the product' scope is distinct enough to be inferred.

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: it reads as the tool for onboarding/overview questions about what the app is and does. No explicit when-to-use, when-not, or pointer to an alternative (e.g., get_article for specific topics) is 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 full burden, and it does disclose the payload shape: intro, sections, Q&A, and a link, plus the notable trait that diagrams and interactive blocks are returned as markers rather than content. It says nothing about missing-slug/error behavior, authentication, or whether content is cached or translated.

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 dense sentence that front-loads the resource and then enumerates what comes back, with zero filler. Every clause earns its place by setting expectations about response contents.

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 no annotations and no output schema, the description usefully stands in for the missing return schema by listing the article's components. A residual gap is failure behavior for an invalid or unknown slug.

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 slug parameter already documents its format and origin (list_articles) with an example. The description adds no parameter meaning beyond that, so the 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?

Names a specific resource (the pandawed.ru blog article) and verb of retrieval, and 'целиком' scopes it to the full article rather than a snippet, which implicitly separates it from list_articles/search_articles. It stops short of naming those siblings explicitly, so an agent must infer the split.

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 only usage signal is 'целиком', which implies 'use this when you need the whole article' — usage is inferred, not stated. There is no explicit when-not or named alternative, though the schema's mention of list_articles supplies part of the routing hint.

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 burden, and it does disclose meaningful behavior: the truncation rule (up to 30 items, half for small sets) and the exact shape of what is returned (hieroglyphs, pinyin, Russian translation, link to the full card set). It omits permissions/rate-limit context, but for a read-only lookup of public study material that is a minor gap.

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 densely packed sentence: output content first, key taxonomy second, sibling pointer last. Everything earns its place, though the key enumeration is long enough that a short break would improve scannability.

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?

There is no output schema, so the description must describe return values, and it fully does: item count limits, the three fields per entry, and the accompanying link. For a single-parameter lookup tool, nothing an agent needs in order to call it correctly 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 coverage is 100%, so baseline would be 3, but the description goes beyond the schema by enumerating and explaining the key families: hsk1…hsk6, hsk7-9 for HSK 3.0, numbers, basic100, tema-* topics and uch-* textbook lessons. That is genuine semantic value over the regex pattern.

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 pair: returns the first words of a set (up to 30, half for small sets) with hieroglyphs, pinyin, Russian translation, plus a link to the full card set. This is clearly distinguishable from list_sets (which enumerates keys) and from the article tools, so an agent can pick it without opening the schema.

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?

Implicitly routes the agent: use this for a preview of a specific set, and consult list_sets for the complete key list. The alternative is named explicitly, but there is no statement of when NOT to use it (e.g., if you need the whole set, this preview is truncated).

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 full behavioral burden. It does disclose that only published articles are returned and lists the returned fields, which is genuinely useful. However, it says nothing about ordering, limits, pagination, or whether the result set can be large, which matters for a catalogue listing.

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 sentence with zero waste, front-loaded on the resource and scope, followed by the field list. 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?

There is no output schema, and the description compensates well by listing the returned fields, so an agent knows what it gets back. Missing only the secondary operational details (ordering, result size, pagination) for a zero-parameter 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?

The tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. The field enumeration it provides is return-value context rather than parameter semantics.

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: published blog articles on pandawed.ru about Chinese language and HSK, and enumerates the fields returned (slug, title, description, date). It is clearly a list operation distinguishable from get_article and search_articles, though it never explicitly contrasts them.

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

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

With no parameters and a clear 'published articles' scope, the use case is implied: browse the blog catalogue. But there is no explicit when/when-not guidance or reference to the sibling tools (get_article for a single item, search_articles for filtering), leaving the agent to infer the 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?

No annotations exist, so the description carries the full burden. It does disclose the shape of each result (word count and lesson link), which is genuinely useful, but says nothing about ordering, pagination, result size, or whether an unauthenticated call is allowed — significant gaps for a listing tool with no safety hints.

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 its contents, followed by the filtering option. The long parenthetical enumerations ('семья, еда, цвета, числа и ещё два десятка') are informative but slightly bulky; nothing is truly 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?

With no output schema, the description must convey the return shape, and it does at a high level (sets grouped by family, each with word count and lesson link). For a zero-required-parameter list tool this is close to sufficient, though ordering and volume remain 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?

The schema already documents the single parameter at 100% coverage, including an enum, so the baseline is 3. The description does gloss the enum values (temy = themes, uchebniki = textbooks) and confirms the no-parameter case shows everything, but that largely restates the schema rather than adding new meaning.

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

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

States a specific verb-plus-resource (listing word sets) and enumerates the three content families — HSK 3.0 levels, thematic sets, textbook lessons — so an agent immediately understands what will be returned. It never names a sibling; the contrast with get_set_preview (single-set detail) must be inferred from the noun 'наборы' 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?

The final sentence explains that the group filter is optional and names the three accepted values, which is usage context of a sort. There is no explicit when-to-use or when-not-to-use guidance against get_set_preview, search_articles, or list_articles, so routing between the siblings is left to inference.

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

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

With no annotations, the description carries the full load; it does disclose the searched fields and target site, which is real behavioral value. It says nothing about matching semantics (substring vs word), result ordering, or how many results come back, which matters for a search tool with no output schema.

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 immediately followed by the scope. Nothing redundant, nothing to trim.

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 single-param read tool this is close to adequate, but with no annotations and no output schema the description should indicate what a result contains (article titles? snippets?) and any result limit. That gap is not fatal but is real.

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?

Only one parameter, and the schema already documents it at 100% coverage with an example. The description's mention of the searched fields adds context about the query's effect but no syntax, length, or format guidance 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?

Names a specific verb (ищет) and resource (статьи) and narrows scope precisely to titles, descriptions and body text of the pandawed.ru blog. It implicitly separates itself from list_articles and get_article, but never names those siblings, so the differentiation is left to inference.

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 wording implies keyword lookup rather than enumeration, which hints at when to prefer this over list_articles, but the description never states that condition or any exclusion. An agent must guess that list_articles is for browsing and get_article for retrieving one known article.

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