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?
No annotations are provided, so the description must disclose all behavioral traits. It covers the authentication requirement but does not explain side effects (e.g., changes to pricing model usage, persistence, or rollback possibility) or error scenarios beyond authorization failure.
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 concise at two sentences, with the action stated front-loaded. However, the second sentence is lengthy and could be better structured as a bullet or separate line for readability.
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 the presence of an output schema, return values are not required in the description. However, critical context is missing: the format and constraints of 'model_json', error handling, effect on existing pricing, and relationship with sibling pricing tools. The description feels incomplete for a setting operation.
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%, yet the description adds no meaning to the parameters. It does not explain what 'model_json' should contain (e.g., format, structure) or the purpose of 'dpop_token'. The proof requirement is mentioned but not linked to any parameter.
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 'Set the active pricing model,' using a specific verb and resource. It also mentions 'RESTRICTED to operator,' which distinguishes it from sibling tools like cypher_get_pricing_model (read-only) and cypher_reset_pricing_model (reset).
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 explicitly notes that the tool is restricted to operators and requires a specific proof, giving clear context for eligibility. However, it does not directly state when not to use it or mention alternatives for non-operators, which is a minor gap.
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.
The set is heavily clustered: audit_why_exists, explain_capability, suggest_capability_why, and authorize_capability_why all answer the same basic 'why does this capability exist?' question and differ mainly in provenance/authority. Many status and provenance tools (adoption_status, session_status, service_status, issue_provenance, pr_provenance, symbol_provenance, service_provenance) also blur together without close reading.
The overwhelming majority of tools follow a predictable cypher_verb_noun pattern in snake_case, which provides strong naming consistency across a very large surface. Minor deviations such as cypher_oracle_about, cypher_oracle_how_to_join, cypher_which_service_handles, and cypher_what_realizes_capability are noticeable but do not break the overall pattern.
112 tools is an extreme count for a single MCP server, regardless of how well the clusters are named; it heavily burdens tool selection, context, and agent discovery. The set spans unrelated domains including payments, coupons, credentials, provenance, issues, patents, queries, pricing, and NOS transformations, which should be split into separate focused servers.
Many domain clusters have strong lifeycle coverage: COUPs have mint/list/update/delete/redeem, credentials have courier delivery/box status/update/delete/forget, and the named-query catalog has full CRUD plus published-tool management. Minor gaps exist—e.g., no generic list_services, no delete for capabilities, and no close/resolve action for issues—but most flows have no outright dead end.