tokportal_get_account_managed_subscription

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read operation. The description adds significant behavioral context beyond these: eventual consistency at period_end with a few-minute delay for the renewal worker, explicit period_expired boundary, the validity of zero-credit quotes, and the nuanced meaning of a 404 (grandfathered, ineligible, or not yet delivered). It also clarifies that coverage is independent from bundle completion, preventing false causal inferences. No contradictions with annotations.

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 the core return values in the first sentence, then adds edge cases and behavioral notes in subsequent sentences. Every sentence adds unique value. At ~120 words, it is dense but not wasteful. A minor improvement could be to list return fields more structurally (e.g., bullet points) to improve scannability, but overall it is well-organized for an AI agent.

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?

No output schema is provided, so the description must fully document return semantics. It covers effective status, 30-day period, account rate, unpaid periods, task access, reactivation quote, period_end behavior, lock_version, and edge cases (grandfathering, 404 interpretation, zero-credit). However, it does not explicitly list every possible field (e.g., timestamps beyond current_period_end) and could benefit from a structured enumeration. Overall, sufficient for a complex domain but leaves minor ambiguity.

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% (one 'id' param with description 'Saved account ID.'). The tool description does not elaborate on this parameter beyond the schema—it does not specify constraints (e.g., must be a saved account that was previously created), format expectations, or relationship to other entities. Given full schema coverage, the baseline is 3, and the description adds no extra semantic value here.

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 the tool retrieves TokPortal Coverage status and enumerates specific returned fields (status, period, rate, unpaid periods, task access, reactivation quote). This distinguishes it from sibling get tools like tokportal_get_account (which returns general account details) and tokportal_get_bundle_account (bundle-focused). The verb 'Get' and resource 'Coverage status' align precisely with the tool name's 'managed_subscription' domain.

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 explains how to interpret results (grandfathered accounts, 404 meaning, zero-credit quote validity) but does not explicitly state when to use this tool versus alternatives like tokportal_reactivate_account_managed_subscription or tokportal_get_account. No context is given for prerequisites or conditions that should be checked before calling. The edge case guidance is helpful but usage direction is implied rather than explicit.

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