Set the active pricing model. RESTRICTED to operator.
Requires a valid proof (Schnorr-signed kind-27235 event) proving the caller holds the operator's nsec.
| Name | Required | Description | Default |
|---|---|---|---|
| dpop_token | No | ||
| model_json | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the restriction and proof requirement, which are key behavioral traits. However, it does not mention any side effects or success/failure responses.
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 two sentences, front-loaded with the purpose. Every sentence provides essential information without unnecessary fluff.
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?
The tool has 2 parameters and an output schema. The description covers the auth requirement and purpose, but lacks parameter explanations and return value details. It is minimally adequate but leaves gaps.
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 0%, meaning the description must explain the parameters. It mentions `model_json` in the schema but not in the description, and `dpop_token` is not explained. The description adds no semantic value to the parameters.
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 starts with 'Set the active pricing model', providing a clear verb and resource. It distinguishes itself from sibling tools like `excalibur_get_pricing_model` and `excalibur_reset_pricing_model` by focusing on setting rather than getting or resetting.
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 states the tool is 'RESTRICTED to operator' and requires a proof, implying only operators should use it. However, it does not explicitly mention when not to use it or provide alternative tools for non-operators.
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.