sprkly_get_billing_summarySubscription status, current plan, period end, purchased handles and the last few billing events. No payment method details; the Stripe customer id is truncated.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint: true and openWorldHint: false, so the description doesn't need to restate that it's a read operation. The description adds context by specifying what it includes (purchased handles, billing events) and what it excludes (payment method details, Stripe ID truncated). This adds some behavioral context beyond the annotations, but it doesn't mention any other behaviors like rate limits or response format, which are less critical since it's a simple read with no parameters.
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 extremely concise: two sentences with zero waste. The first sentence lists the key output components, and the second clarifies exclusions. It is front-loaded with the most important information and every word 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?
Given that this is a simple read-only tool with no parameters and no output schema, the description is fairly complete. It explains the contents of the summary and notes what's excluded. However, it doesn't mention any edge cases like what happens if the subscription is inactive or if there are no billing events, and it doesn't state the return format (e.g., JSON structure). Since it's a simple tool, this is acceptable, but there is a slight gap in completeness.
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 has 0 parameters and the schema coverage is 100%. With no parameters, the baseline is 4 as per the rubric. The description adds value by explaining what the tool returns, which is especially important given the absence of parameters. It clarifies the output scope, which compensates for the lack of an output 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 clearly states what the tool does: it retrieves billing summary information. The description lists specific components (Subscription status, current plan, period end, purchased handles, last few billing events), which distinguishes it from sibling tools like sprkly_get_account_summary or sprkly_get_analytics, though it doesn't explicitly name them. The purpose is clear and specific.
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 context: when a user wants to see billing information. However, it doesn't explicitly state when NOT to use this tool or compare it to alternatives like sprkly_get_account_summary. The mention of what's excluded (no payment method details) gives some guidance about its scope, but it lacks explicit guidance on when to choose this over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources and actions, and detailed descriptions make subtle differences clear. Minor ambiguity exists between sprkly_list_profiles and sprkly_list_connected_social_accounts, and between sprkly_get_post_status and sprkly_get_post_approval_status, but the descriptions provide enough context to disambiguate.
All tools share the sprkly_ prefix and use a snake_case verb_noun pattern. Read operations are consistently split between get_ for singular/detail and list_ for plural collections, with action verbs like schedule, draft, delete, request, and validate following the same clear style.
18 tools is on the heavier side, but the server covers a broad social media workflow spanning scheduling, approvals, analytics, billing, and automation templates. A few tools are explicitly optional, like sprkly_add_media_from_url and sprkly_get_tiktok_posting_options, so the set could be tightened slightly, but the count remains defensible for the scope.
The core post lifecycle is well covered: draft, validate, schedule, update, delete, get status, and approval flow. Minor gaps exist around draft/media library management and automation template listing/deletion, but agents can accomplish the main scheduling tasks without dead ends.