Get the active pricing model for this operator. Free.
If no model exists, self-initializes a scaffold with all registered tools at 0 sats. No economic data from code.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
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No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses key behavioral traits: it is free, self-initializes a scaffold if no model exists, and explicitly states 'No economic data from code.' This is comprehensive for a getter.
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 sentences, no filler. First sentence states purpose, second clarifies a special case. Front-loaded and efficient.
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 zero parameters and existence of an output schema, the description covers the essential behavioral aspects (initialization, cost, data source). No further info needed for a low-complexity tool.
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?
No parameters exist, so schema coverage is 100%. The description does not add parameter info beyond the schema, but the baseline for zero-parameter tools is 4.
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?
Clearly states 'Get the active pricing model for this operator', which is a specific verb-noun combination. Distinguishes from sibling tools like set_pricing_model and reset_pricing_model by being the getter operation.
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?
Implicitly clear when to use: querying the pricing model. Mentions free cost and self-initialization behavior, but does not explicitly state when not to use or list alternatives. However, the description provides enough context.
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.
Each tool targets a distinct operation and domain (account, posts, coupons, credentials, scheduling, oracle, etc.), with clear differentiation even for similar-sounding tools like check_balance vs check_authority_balance or list_coupons vs list_my_coupons. There is no ambiguity.
All tools follow a consistent verb_noun snake_case pattern (e.g., create_post, delete_coupon, list_posts), with no mixing of styles. The excalibur_ prefix is uniform.
With 72 tools, the server far exceeds the typical well-scoped range (3–15). While the functionality is broad, the sheer number feels excessive for a single MCP server, leading to an extreme mismatch.
The tool surface covers the full lifecycle for core domains: CRUD for posts, snippets, coupons, credentials; complete flows for OAuth, npub proof, scheduling, notarization, and payments. No obvious gaps are present.