Allegro MCP

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

With no annotations, the description does carry some behavioral weight: it discloses live scraping via a stealth browser and a 30–120s latency window, which is genuinely useful. However, it omits auth requirements, rate limits, failure behavior, and result/pagination characteristics, leaving significant gaps for a 7-parameter scraping tool.

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 tightly written sentences, with the core action and scope front-loaded and the latency caveat placed second. No wasted words.

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 tool with no annotations and no output schema, the description covers the essential action and adds latency context. It does not describe the shape of returned offers or any operational constraints, which leaves the agent with meaningful unknowns before calling it.

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 all seven parameters are documented in the schema, including enums and defaults. The description only adds that `category` accepts an id or full URL, which the schema already states, 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?

States a specific verb ('Browse') and resource ('live Allegro.pl offers within a category'), and clarifies the accepted category identifier forms. It relates itself to allegro_search via 'same filters', but does not explicitly state when an agent should pick this over search, so it stops short of full sibling differentiation.

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 reference to 'same filters as allegro_search' implies a family relationship, but there is no explicit guidance on when to use category browsing versus keyword search or get_offer. Usage is implied rather than 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?

With no annotations, the description carries the full burden and does disclose the most decision-relevant trait: data is scraped live through a stealth browser, so a call costs roughly 30–120s. That latency warning materially affects how an agent schedules calls. It stops short of stating auth needs, rate limits, or what happens on an invalid/removed offer.

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, zero waste: the core action and return fields come first, and the latency caveat follows as a separate, clearly bounded sentence. 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 by listing the returned fields (title, price, seller, condition, description summary, parameters, images) plus the latency profile. Failure modes for a bad id or delisted offer are the main remaining 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 100% and the single offerId parameter already documents that it accepts a numeric id or a full oferta URL, so the description's 'by id or URL' restates rather than augments it. Baseline 3 applies when the schema does the heavy lifting.

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 — fetch a single Allegro.pl offer — and scopes it to one item, which implicitly separates it from the list-oriented siblings allegro_search and allegro_browse_category. The parenthetical enumerates exactly what comes back, so an agent knows the payload before 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?

Usage is implied by 'single ... offer by id or URL', but the description never names the alternatives (allegro_search, allegro_browse_category) or states when to prefer them. There are no explicit exclusions or preconditions, so routing to the right sibling 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 behavioral burden and does well: it discloses live scraping via a stealth browser, a 30–120s latency window, and output caveats such as the `offers` key and formatted price strings. It does not cover rate limits, reliability, or auth needs, but the major operational traits are present.

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 front-loaded with purpose and latency, then moves into return-shape details without wasted introductory text. Some return-shape explanation is redundant with the output schema, though the `offers` key and formatted-price warnings add practical value.

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 an output schema, the description supplies the important missing context: live scraping behavior, latency expectations, and result-field caveats. Combined with full schema coverage, an agent has enough information to call and interpret the tool 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 100%, so the schema already documents all six parameters including enums and defaults. The description mentions phrase, price range, condition, and sort but adds little syntax or semantics beyond what the schema provides.

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: search live Allegro.pl marketplace offers by phrase with optional filters. It clearly distinguishes this from category browsing or fetching a specific offer by describing phrase-based search.

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-based search context and optional filters imply when the tool is appropriate, and the sibling names make browse-category and get-offer alternatives inferable. However, it never explicitly says when to use this versus allegro_browse_category or allegro_get_offer.

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