Canada Health Product Recalls MCP

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

With no annotations at all, the description carries the full burden. It usefully discloses two behavioral traits: the call is free and the result set is capped at 5 newest items, which is real information an agent can't get from schema or annotations. It says nothing about auth requirements, pagination, or what happens when nothing matches.

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 dense sentence with no waste: cost signal, jurisdiction, resource, match semantics, and result cap all front-loaded in that order.

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 single-optional-param read tool with no output schema, the description covers the essentials (what it returns, how many). It leaves gaps an agent may care about: behavior with no keyword supplied, whether results are sorted strictly by date, and the data source coverage.

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%, so the description must compensate, and it partly does by enumerating what a keyword can be (product, brand, allergen, hazard). However, the single parameter is optional (required=0), and the description never says what happens when keyword is omitted — a meaningful ambiguity for a 1-param tool.

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 (health product recalls) with scope qualifiers (Canada, latest, newest 5) and what the keyword can match (product, brand, allergen, hazard). It implicitly distinguishes itself from recall_search by capping results to the newest 5, but never names that sibling 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?

The word 'latest' plus 'newest 5' implies this is the recency-oriented lookup versus a broader search, but there is no explicit when-to-use / when-not-to-use guidance and no sibling (new_since, recall_search, watchlist) is named as an alternative.

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.