Canada Consumer Product Recalls MCP

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

With no annotations, the description does carry useful behavioral facts: the call is free, results are ordered newest-first, and the response is capped at 5 items. It omits auth requirements, rate limits, and what happens with an empty/absent keyword, which matters for a tool with zero structured 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?

A single tight sentence with the cost signal and scope front-loaded, the match semantics in the middle, and the result cap at the end. No filler at all.

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, no-annotation, no-output-schema tool, the description communicates cost, ordering, and result count. It still leaves the agent guessing about the shape of each recall record and about behavior when keyword is omitted.

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 is a bare untyped string — so the description must compensate, and it does by explaining that the keyword matches product, brand, allergen, or hazard. It stops short of saying whether keyword is optional (required list is empty) or how matching is performed.

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 (retrieve latest recalls), a specific resource (Canada consumer product recalls), a match field set (product, brand, allergen, hazard), and a result cap (newest 5). It is clearly a 'latest snapshot' tool, which implicitly contrasts with recall_search, but it never names the sibling to make the distinction explicit.

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?

'Latest' and 'newest 5' imply a quick-glance use case, and the 'FREE' prefix hints at a cost trade-off versus siblings. However, no alternative (recall_search, new_since, watchlist) is named and there is no statement of when this tool is the wrong choice.

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 must carry the behavioral disclosure burden. It adds PRO gating and inclusive date semantics, but omits read-only status, pagination/rate limits, and return behavior, leaving important gaps.

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, front-loaded with the core scope and with no wasted verbiage. The PRO marker and monitoring use case are compactly conveyed.

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 two-parameter list tool without an output schema, the description covers the core filter and a use case. However, with no annotations and incomplete schema descriptions, it should say more about date format, auth/pagination, and result scope.

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 50%; the description clarifies that 'since' means recalls updated on or after that date, adding meaning beyond the schema's bare string type. It does not specify date format, and access_token semantics come only from 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?

The description states the resource (recalls) and the temporal filter (updated on or after a date), making the scope clear and distinguishable from latest_recalls and recall_search. It lacks an explicit verb and does not name siblings, so it stops short of 5.

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 'for daily monitoring jobs' gives a clear usage scenario, but there is no when-not guidance, prerequisite detail, or explicit comparison to latest_recalls/watchlist. The context is implied rather than fully specified.

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 must carry the behavioral load; it does disclose two useful traits — a 100-result cap and a 'PRO'/subscriber-tier requirement (reinforced by the access_token param). It omits result ordering, pagination/truncation behavior, and anything about read vs. write semantics or rate limits.

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?

Extremely tight, front-loaded, and every fragment carries information; 'PRO.' telegraphs the tier constraint immediately. It is slightly clipped to the point of terseness (no full sentence framing), but nothing 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 5-parameter, no-annotation, no-output-schema search tool, the definition covers filters and the result cap but says nothing about the shape of returned recall records or what happens past 100 results, leaving the agent guessing about output.

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 20%, so the description must compensate; it does name four of the five parameters (keyword, category, recall class, since) and adds the YYYY-MM-DD format for since, but leaves keyword matching semantics and the valid values for category/recall_class unexplained.

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 concrete action (return up to 100 recalls) with an explicit list of filter dimensions, so the agent knows it's a filtered search over recalls. It is distinguishable in spirit from latest_recalls and new_since, but the description never names those siblings or states the boundary between 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?

There is no explicit when-to-use or when-not-to-use guidance; the only hint is that filters exist, which implies 'use this when you need filtering.' Nothing tells the agent how this differs from latest_recalls or new_since, so the routing decision 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 disclosure burden. It usefully adds the 50-item cap, indicates a read-style check returning matching recalls, and notes the optional 'since' filter, but it does not explain matching behavior, result shape, rate limits, or that access_token authentication is required.

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 efficient sentence with the core capability front-loaded. The leading 'PRO.' is compact but slightly cryptic, and the parenthetical date filter is appropriately brief.

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 three-parameter tool with no annotations and no output schema, the description covers the basic purpose, batch limit, and return intent. However, it leaves out important context such as authentication requirements, matching semantics, and what a matching recall record contains, making it only minimally sufficient.

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 33%, but the description compensates by explaining that 'items' are products, brands, or suppliers and are limited to 50, and that 'since' optionally restricts results by date. The access_token parameter is documented in the schema, so most parameter meaning is covered, though item format and date syntax remain unstated.

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 action and resource: checking batches of up to 50 products, brands, or suppliers for matching recalls, with an optional date filter. It is clear what the tool does, but it does not explicitly distinguish itself from siblings like recall_search or new_since, despite overlapping recall-search semantics.

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?

There is no explicit guidance on when to choose watchlist over recall_search, new_since, or latest_recalls. The word 'PRO' hints at a paid-plan gate, but the description does not say when this batch check is preferable to the sibling tools.

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