roastify_reset_pricing_modelErase all pricing models and restore a viable default.
Deletes every stored model, then self-initializes a fresh one from the tool registry — all tools at 0 sats with proper UUIDs. Returns the new model.
RESTRICTED to operator — requires proof (nsec-signed).
| Name | Required | Description | Default |
|---|---|---|---|
| dpop_token | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden and does so well. It explicitly discloses destructive behavior ('Erase all', 'Deletes every stored model'), describes the re-initialization outcome ('all tools at 0 sats with proper UUIDs'), states it returns the new model, and flags the nsec-signed proof requirement for operators.
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 action in the first line, followed by necessary behavioral detail and the security restriction. Every sentence contributes distinct information without filler, and the destructive nature is immediately visible.
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?
For a destructive reset tool with an output schema, the description covers the operation's effect, re-initialization details, return value, and authorization requirement. It does not explicitly describe failure modes for non-operators or clarify how dpop_token should carry the proof, leaving a minor completeness gap.
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 schema coverage for the single dpop_token parameter is 0%, and the description does not explicitly map the nsec-signed proof to that parameter. However, the parameter name 'dpop_token' plus the stated proof requirement gives a plausible but indirect connection. This is partial compensation rather than full parameter clarity.
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 leads with a specific action: 'Erase all pricing models and restore a viable default.' It then clarifies the behavior: 'Deletes every stored model, then self-initializes a fresh one from the tool registry.' This clearly distinguishes it from siblings like set_pricing_model, which would not perform a wholesale destructive 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 clearly scopes the tool as a destructive, wholesale reset and adds an explicit operator-only restriction with proof requirement. It does not name alternatives such as set_pricing_model, but the context is clear enough for an agent to infer when this tool is appropriate versus a targeted pricing update.
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 clearly distinct resources—patron balances vs. operator Authority balances, design text vs. full design fetches, operator vs. patron credentials—and the verbose descriptions carefully separate request/receive flows. A few pairs could still be confused at a glance, such as service_status/session_status, forget_coupon/delete_coupon, and get_design_text/fetch_design.
All tools share the roastify_ snake_case prefix and mostly follow a verb_noun pattern like list_, get_, update_, delete_, and create. However, several noun-only names (service_status, session_status, account_statement, oracle_about) and the inconsistent forget_ vs. delete_ distinction for credential/coupon removal keep it from being fully consistent.
69 tools is an extreme count for a single MCP surface and far exceeds the 25+ threshold. Even though the tools span many subdomains—design, payments, coupons, credentials, pricing, notarization, oracle—the sheer number will be heavy on agent context and selection accuracy.
Core workflows are largely covered: design storage/editing, coupon lifecycle, credential vaults, credit purchasing, pricing models, notarization, and the oracle all have reasonable read/write surfaces. However, session_status explicitly tells not_registered operators to call register_operator, which does not exist in the tool set, and design editing lacks any delete-element operation, leaving notable dead ends.