ALK Compliance MCP

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds a useful 'not legal advice' disclaimer and cites the underlying regulations, but it does not explain the output format or how the deadlines are calculated.

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 dense but front-loaded, with the core purpose stated first and regulatory citations earning their place. It could be split for readability, but it avoids unnecessary 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, the description should carry more weight, and it does cover all five parameter concepts and the legal context. It still lacks an explicit statement of the return structure, but it is sufficient for an agent to understand what the tool computes.

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%, setting a baseline of 3, but the description adds regulatory meaning by tying parameters to ICS timing under FAR 52.216-7, grant report cadence and closeout under 2 CFR 200.328/200.344, and single audit thresholds under 2 CFR 200.501. This helps an agent understand why each input matters.

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 it returns federal award deadlines scoped by fiscal year end and award type, with specific regulatory citations. It does not explicitly distinguish itself from sibling tools, but the domain is specific enough for an agent to identify the tool's purpose.

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 description implies usage for federal contractors or grant recipients needing compliance deadlines, but it does not state when to use this tool versus alternatives like form_5500_check or product_compliance_requirements. No explicit exclusions or prerequisites are provided.

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?

Annotations already cover read-only and closed-world, but the description adds real value beyond them: the deadline computation rule (7th month after plan year end), the Form 5558 extension, the welfare exemption flag, and the fact that the response cites IRS/DOL rules and links the Compliance Desk. The 'likely' and 'not legal advice' hedges also set expectations about result reliability.

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 and the deadline rule are front-loaded in the first clause, with the caveat compressed into a short trailing sentence. The parenthetical is dense but every element (deadline rule, extension, exemption, sources) is load-bearing; only the Compliance Desk link note borders on promotional 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 four fully documented parameters and no output schema, the description compensates by describing what comes back (a needs-to-file determination, due date, exemption flag, rule citations). It is essentially complete for an agent to call correctly; only the absence of guidance on ambiguous inputs (e.g. unknown welfare funding) 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 description coverage is 100%, including enum meanings and the date format, so the schema carries the parameter burden. The description hints that the welfare exemption depends on funding arrangement and adds the participant context indirectly, but adds no syntax or threshold detail beyond 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?

States a specific verb and resource (checks whether a plan needs a Form 5500 and when it's due) and scopes it to employee benefit plans, which separates it from product_compliance_requirements and federal_award_deadlines. It does not explicitly name or rule out those siblings, though, so an agent must infer the boundary from domain terms.

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 the domain (plan sponsors/administrators checking a filing obligation) but there is no explicit when-to-use guidance, no prerequisites, and no statement of when to prefer a sibling such as federal_award_deadlines for non-benefit-plan deadlines. The 'not legal advice' line is a disclaimer, not 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine value by disclosing the return content (each desk's fix and URL), which is important given there is no output schema. It stops short of saying whether the list is static/complete, ordered, or how large it is.

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 sentence with zero filler, and the key facts (what is listed, what each entry contains) are front-loaded. 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?

For a zero-parameter, read-only lookup with no output schema, the description covers the essentials: what is returned and why it matters in the workflow. Minor gaps remain around list size, ordering, and whether the returned directory is exhaustive.

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, so there is no parameter semantics to explain; the baseline for a param-less tool is 4. Nothing in the description misleads about inputs.

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 (Lists) and a specific resource (ALK Trading compliance desks), plus what each entry contains (the fix and its URL). It also implicitly distinguishes itself from siblings by framing itself as the remediation directory for 'the issues these tools flag', though it does not name those siblings 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 implied rather than stated: an agent can infer it should call this after another tool reports a compliance issue, since the desks 'fix the issues these tools flag'. There is no explicit when-to-use instruction, no when-not to use it, and no named alternative among federal_award_deadlines, form_5500_check, or product_compliance_requirements.

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?

Annotations already cover read-only and closed-world, and the description adds genuine value beyond them: the shape of each returned item (issue + official source link + owning ALK desk) and a 'not legal advice' disclaimer that matters for how the agent relays results. Marking it 'Likely' also signals heuristic rather than authoritative output. It does not say what happens on no-match or how results are ordered, keeping it off a 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?

Front-loaded with the scope and rule list in a single dense sentence, followed by two short clauses covering return shape and the disclaimer. Every sentence earns its place, though the acronym-heavy rule enumeration (CPSIA, PFAS, EPR) is packed tightly enough to slow a first read.

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, the description carries the burden of describing returns and does so ('potential issue with an official source link and the ALK desk that fixes it'), plus a scope disclaimer. Complete enough to call correctly; only the empty-result and coverage-limit behavior are unstated.

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 the schema already defines all six parameters including the boolean flags. The description mentions the PFAS, children's-product, and packaging EPR rule families, which loosely hints at what the corresponding booleans unlock, but it never explains parameter semantics directly. Baseline 3 is appropriate.

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 combination ('Likely US product compliance rules for a product sold into a US state or market') and then enumerates the exact rule domains covered: CPSIA certificates, Prop 65, Minnesota PFAS, and packaging EPR in Oregon/Colorado/California. An agent immediately knows what it will get back and can distinguish it from the unrelated siblings (federal_award_deadlines, form_5500_check, list_desks).

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 framing 'for a product sold into a US state or market' plus the required state/product_type parameters makes the triggering context clear. 'Likely' and 'each item is a potential issue' correctly set expectations that this is a screening pass, not a definitive answer. It stops short of explicit when-not guidance (e.g., non-US markets, non-product questions), so it is not a 5.

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