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

With no annotations, the description carries the full burden and largely meets it: it lists the inputs it fuses (temperature, comment reactions, poster reputation, deal age/status, title conditions), discloses that temperature can go negative, and defines the output contract (verdict with evidence, never a bare score). It omits failure modes, auth/permission needs, and any rate-limit or caching 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?

Front-loaded with the core purpose in the first sentence, then layers scope, mechanism and output contract. It is somewhat prose-heavy across three short paragraphs, but each sentence adds usable information rather than restating the name.

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 2-parameter analytical tool with no output schema and no annotations, the description covers purpose, evidence sources, output shape and limitations adequately. The remaining gap is parameter-level detail, which is the one area callers would still have to guess at.

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

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

Schema description coverage is 0%, so the description must compensate for the two undocumented parameters, and it does not: 'id_or_slug' format and 'include_comments' are never mentioned, leaving it unclear how the boolean toggles the comment-reaction signal it describes. The mention of 'comment reactions' as an input loosely implies comments matter, but no real parameter guidance is given.

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 ('Judge whether the community believes a deal is genuine') and is easily distinguished from siblings like get_deal, get_deal_comments and search_deals, which retrieve raw data rather than render a sentiment verdict. The description also pins the scope of judgment (community belief, not merchant truth).

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 context for when this tool is the right one ('This is what Pelando has that a price comparator does not') and draws an explicit boundary around what it will not do ('cannot verify that the price is real or still available'). It stops short of naming sibling tools or routing conditions (e.g. use get_deal for raw facts), so it is strong but not fully explicit.

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 behavioral burden. It usefully discloses error-handling behavior: unknown slugs are rejected at this layer because the upstream API silently ignores them and returns the global feed. But it says nothing about auth requirements, rate limits, result shape, or how limit/include_expired behave.

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

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

Front-loaded with the action, followed by parameter guidance in three tight sentences with no filler. The community discussion is somewhat long relative to the rest of the tool's surface, but every sentence 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?

For a four-parameter tool with no annotations and no output schema, the coverage is uneven: community is well covered while limit, include_expired, and the return structure are not. An agent can invoke it, but not with full confidence about limits or result shape.

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

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

Schema description coverage is 0%, so the description must compensate. It does so only for `community` (11 canonical slugs, examples, rejection behavior); `limit`, `include_expired`, and `feed` receive no semantic explanation beyond their names/enums. Partial compensation of one of four parameters warrants a 3.

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 ('Browse Pelando's own feeds') and adds scoping detail ('optionally scoped to one community'). It does not explicitly contrast itself with the sibling search_deals, so the browse-vs-search distinction 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?

It gives real guidance on the community parameter (use one of 11 canonical slugs, use `tech-lover`/`mundo-gamer` for electronics), which implies when this tool is appropriate. However, it never states when to prefer browse_feed over search_deals or list_communities, so alternative selection is not addressed.

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

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

No annotations are provided, so the description carries the full behavioral burden, and it mostly doesn't. It never says what a 'deal' response contains, whether a missing deal errors or returns empty, or if there are auth/rate-limit considerations. The only disclosed behavior is input-shape flexibility, which is closer to parameter guidance.

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 paragraphs, the core action front-loaded, and one concrete example that earns its place by resolving the URL case. 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?

With no output schema and no annotations, the description should ideally sketch what comes back so an agent can plan next steps (e.g. whether comments or quality assessment are worth calling). It covers input handling well but leaves the return contract entirely unspecified.

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% — the schema says only 'Id Or Slug' as a bare string — so the description must compensate, and it does: it explains that both UUID and slug are accepted and shows how to extract the slug from a pasted URL. That is real semantic value the schema lacks, though it doesn't specify format expectations (e.g. UUID casing) or error handling for a bad 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?

States a specific verb ('Fetch') and resource ('one deal') and names the two accepted identifier forms (UUID or slug), which cleanly separates it from the plural sibling search_deals. It does not explicitly name that sibling, so the differentiation 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?

Usage is implied: use this when you already have an identifier for a single deal. The slug/URL paragraph is genuinely helpful for invoking it, but there is no statement of when to prefer this over search_deals or browse_feed, and no mention of failure behavior when the identifier doesn't resolve.

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 behavioral burden and discloses important behavior: the upstream endpoint has no pagination, returns the whole tree at once, and the local limit truncates results. It also mentions a truncated indicator, which helps the agent interpret output, though it omits auth, rate limits, and broader return structure.

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 appropriately sized and front-loads the purpose in the first clause. The second sentence adds useful context about why the thread matters, and the third covers pagination behavior without excessive padding.

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

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

Given no annotations and no output schema, the description should do more, but it does cover the critical non-pagination behavior and truncated output signal. It still leaves the return shape, comment structure, and identifier format largely to inference.

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

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

Schema description coverage is 0%, so the description must compensate for both parameters. It explains limit well—local truncation rather than server-side pagination—but gives no explicit semantics for the required id_or_slug parameter beyond the general phrase 'a deal's comment thread.'

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 states the verb and resource: 'Read a deal's comment thread.' It distinguishes the tool from generic deal-fetching siblings by focusing on the comment thread and its role in correcting bad postings, though it does not explicitly name sibling alternatives.

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

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

Usage is implied rather than explicit: the thread is framed as the place to investigate fake discounts and corrections because no report/flag field exists. However, the description gives no direct when-to-use instruction or comparison against tools like get_deal or assess_deal_quality.

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

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

With no annotations, the description carries the full burden and does real work here: it warns that coupons expire silently, that no code is guaranteed to work, and that each code carries its posting date so freshness is visible. It does not cover auth, rate limits, or pagination, but the data-reliability disclosure is unusually candid.

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 purpose, then the filter semantics, then the expiry caveat. Nothing is redundant and each sentence earns its place; the quoted bad value is illustrative rather than 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 two-parameter read tool with no output schema, the description covers purpose, the non-obvious flag, and return-data caveats well enough to call it correctly. The only gap is the expected format of the `store` argument, which is minor.

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

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

Schema description coverage is 0%, so the description must compensate, and it does for only_valid_codes: it explains the filter drops prose entries and gives a concrete example of the junk value seen. The `store` parameter is left unexplained, but its meaning is self-evident.

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 opens with a specific verb and resource: 'Fetch a store's coupon codes', which is unambiguous. Coupons are a distinct resource from the deal/store/community siblings, so an agent can separate it, though no sibling is named or contrasted explicitly.

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: fetch coupons when you want a store's coupon codes. There is no statement of when to prefer this over search_deals or get_deal, and no prerequisites or exclusions. The only_valid_codes explanation hints at a filter decision but does not frame when to use the tool.

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 add real behavioral value: it warns that categoryId is a bare numeric with no label anywhere in the data, which prevents a doomed lookup attempt. However, it says nothing about the `refresh` flag's effect, caching, network cost, or return shape, so it is only partially transparent.

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, front-loaded with the core action and count, with each sentence carrying distinct information (count, taxonomy gap, example names). The example community names are slightly decorative but do aid recognition.

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 or annotation coverage, and the description omits both the return format and the `refresh` semantics. What it does supply — the count, the taxonomy caveat, and sample names — is genuinely useful for a small list tool, but a fully self-sufficient definition would cover the one parameter.

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 single `refresh` parameter has 0% schema description coverage and is not mentioned at all in the description. The reader cannot tell whether refresh forces a network fetch, invalidates a cache, or changes the payload, so meaning is missing at both levels.

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?

It names a specific verb and resource ('List Pelando's 11 communities') and even fixes the cardinality, so an agent knows exactly what comes back. It also distinguishes the tool from any category-style lookup by stating this is the site's only browse taxonomy. No sibling does anything similar, so it is unambiguous.

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 calling this 'the site's only browse taxonomy' the description implies the tool is the entry point for discovering communities, but it never states when to prefer it over siblings like browse_feed or search_deals, nor any prerequisites. Usage is inferable rather than explicit.

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. It discloses the return payload, which is genuinely useful, but says nothing about side effects, latency, or failure modes — acceptable for a trivial read-only ping, hence a middling 3.

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 terse sentences, zero waste, with the purpose front-loaded before the return-value detail. Nothing could be cut 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?

For a parameterless health-check tool with no output schema, declaring the returned fields is exactly the information an agent needs. Only the absence of any 'when to use' context keeps it short of a 5.

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

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

The tool takes zero parameters, and the schema is empty with 100% coverage. There is nothing for the description to disambiguate, so the baseline of 4 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 operation (liveness check) and enumerates the returned payload (server name, version, runtime config). This clearly distinguishes it from the deal/feed/store siblings, though it doesn't name an alternative explicitly.

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?

"Liveness check" implies use for health/availability verification, but the description never states when to reach for it versus, say, discovering tools, nor any conditions or exclusions.

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 and does so well: loose token-based matching, the `relevance` block, that `drop_irrelevant` relocates weak matches to `related` rather than deleting them, and the critical server-side (`include_expired`, `sort`) versus locally-applied filter split. These are exactly the non-obvious behaviors an agent needs.

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 short paragraphs, front-loaded with the highest-value caveat (no catalogue behind it), then matching behavior, then the server/local filter trap. Every sentence carries information an agent would otherwise get wrong; nothing is filler.

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

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

For a 11-param, no-annotation, no-output-schema tool, the description covers the essentials — result character, empty-result legitimacy, `relevance`/`related` shape, and filter execution. It stops short of explaining pagination interplay and what `temperature` means, which leaves minor gaps.

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

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

Schema coverage is 0% across 11 params, so the description must compensate; it adds real meaning for the non-obvious ones (`drop_irrelevant`, `include_expired`, `sort`, `size`) and the server-vs-local execution model. It leaves `kind`, `store`, `max_price`, `min_temperature`, and `free_shipping_only` to inference from their names, so compensation is partial but substantive.

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 deals that Pelando users have posted') and immediately characterizes the corpus ('community postings, NOT a catalogue'), which is the decisive fact distinguishing it from get_deal or browse_feed. An agent can tell what it retrieves 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?

It gives strong usage-shaping context — that mainstream terms can legitimately return nothing, and that most filters run locally so a narrow filter plus small `size` may under-return — but it never explicitly names alternatives (get_deal, browse_feed, assess_deal_quality) or states when-not-to-use it. Clear context, no explicit routing.

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

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

With no annotations, the description carries the full burden and does well: it discloses loose substring matching, that results are re-ranked by name similarity, and the important caveat that promotion_count has no listing endpoint anywhere. It omits auth/permission needs, rate limits, and pagination behavior, keeping it short of 5.

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 paragraphs, front-loaded with purpose and then escalating to caveats; every sentence carries information. The bold/backtick formatting is slightly heavy but does not waste 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?

With no output schema and no annotations, the description compensates by naming returned fields (promotion_count, top coupons) and warning about match accuracy and the promotions dead-end. The main gap is the undocumented limit and include_coupons parameters, which leaves an agent guessing on pagination and coupon inclusion.

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% across three parameters, so the description must compensate and largely does not: query matching is loosely described, but limit and include_coupons are never explained, including what include_coupons=false suppresses. Only the query parameter gets meaningful elucidation.

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 and resource ("Look up a merchant") and states what comes back ("live activity counts and its top coupons"), which is more than a restatement of the name. It partially differentiates from siblings by pointing to the alternate path ("search a product term and filter by store") for deals, though it never names search_deals or get_store_coupons directly.

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?

Provides actionable usage guidance: verify the returned name before acting on the first row, and use product-term search when the goal is deals. It lacks an explicit "when not to use this / use X instead" routing statement naming the sibling tools, so it stops short of a 5.

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