2read.gr

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

No annotations are supplied, so the description carries the burden; "Get" and the mention of current price/availability make the read-only, single-record nature clear. It omits error behavior for unknown ids, whether prices include currency/VAT, and any auth or rate-limit constraints, which matter for a live-pricing lookup.

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 resource and returned fields, with the id provenance in parentheses. Nothing is redundant or padded.

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 output schema, the description names the salient return fields (price, availability, description), which is the key thing an agent needs. Minor gaps remain around failure modes and currency/format details, but nothing essential for correct invocation 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% for the single required parameter, so the baseline is 3. The description adds value by giving provenance (derived from search_products) and an inline example id format, which helps the agent supply 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?

States a specific verb (Get) and resource (one 2read.gr product) plus the exact fields returned (price, availability, full description). The word "one" and the product_id keying clearly separate it from search_products, which returns multiple results.

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 tells the agent where the identifier comes from ("from search_products"), establishing the search-then-fetch workflow. It does not state any when-not-to-use case or what happens with an invalid/stale id, so it stops short of full routing 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?

No annotations are supplied, so the description carries the full disclosure burden. It does well on the output side — price in EUR, stock status, product URL, image — and on language behavior, but says nothing about whether matching is keyword or fuzzy, how results are ordered, or any rate/auth constraints, which matters for a search that an agent may call repeatedly.

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 purpose is front-loaded in the first clause and the rest is supporting detail. The product enumeration is somewhat marketing-flavored, but it does earn its place by telling the agent what vocabulary to search with, so little 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 four-parameter search with no output schema, the description covers what the tool searches, the language of input, and the shape of the returned product records. The main remaining gap is result ordering and pagination behavior, which the agent must infer from the schema's page and max_results fields.

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%, so query, page, max_results and in_stock_only are already documented in the schema. The description adds no parameter-level meaning beyond that — notably it never connects the 'stock status' it advertises in results to the in_stock_only filter, so 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?

The description opens with a specific verb and resource: 'Search the 2read.gr ... product catalog', and enumerates the catalog domain (reading glasses, pocket readers, pinhole glasses) so the agent knows what a hit means. It does not name the sibling get_product as the alternative for fetching a single known item, so sibling differentiation is implied 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?

'Works in Greek or English' gives a concrete usage hint about how to phrase the query, and the catalog inventory tells the agent when this tool is applicable. However, there is no explicit when-not guidance and no routing to get_product for detail lookups or store_info for shop-level questions, leaving the choice between siblings 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?

No annotations are provided, so the description carries the full behavioral burden. It does not say whether the data is static or live, what language or currency the policies are in, whether results are paginated or scoped by region, or whether the call has any cost or rate limit; a zero-parameter tool that implicitly performs a read should at least confirm that and describe the nature of the content.

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

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

It is a single short fragment with no filler, so nothing is wasted. The weakness is structural rather than length-based: it leads with a domain name and a topic list instead of a verb-led statement of what the call does.

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 zero-parameter info tool with no output schema, the topic enumeration gives an agent enough to know roughly what comes back. It still omits the return shape (single text block versus structured fields) and any environment or localization detail, which matters because no output schema exists to fill that 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?

The tool takes zero parameters, which is the baseline-4 case; there is no parameter semantics to explain. The topic list does usefully signal that the output is a fixed, all-in-one info bundle rather than a parameterized query.

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 (2read.gr store information) and enumerates topics – shipping, payment methods, returns, contact details – which clearly separates it from the product-oriented siblings get_product and search_products. However, it is a bare noun fragment with no verb, so it never states the action (retrieve/fetch) and reads as a topic label rather than a purpose statement.

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

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

Usage is only implied by the topic list: an agent can infer this is the tool for store-policy and contact questions. There is no explicit when-to-use framing, no statement of when not to use it, and no mention of the sibling tools as alternatives.

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