Generate a Merkle inclusion proof that a patron's balance was included in a Bitcoin-notarized snapshot.
| Name | Required | Description | Default |
|---|---|---|---|
| npub | Yes | The patron's Nostr public key (npub1...). | |
| notarization_id | Yes | The notarization record ID. |
| 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?
With no annotations, the description must carry the behavioral burden. It explains that a Merkle proof is generated from a notarization and a patron key, but it does not disclose whether this has any state-changing side effects, whether a notarization must already exist, or any failure conditions. The get-style name suggests read-only behavior, but that is not explicit.
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?
One sentence with no filler, front-loading the action and clarifying the exact purpose. Every word contributes meaning.
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 two-parameter tool with an output schema and fully described parameters, the overview is largely sufficient. It lacks only an explicit linkage to related proof tools and prerequisites, which would help an agent new to the domain.
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 100%, so npub and notarization_id are already documented in the schema. The description adds domain context but does not enrich the meaning of either parameter beyond what the schema contains, hitting the baseline for fully covered schemas.
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 uses a specific verb ('Generate'), a clear resource ('Merkle inclusion proof'), and a domain context ('patron's balance ... Bitcoin-notarized snapshot'). It does not explicitly contrast with sibling tools like roastify_receive_npub_proof or roastify_request_npub_proof, so it misses full differentiation.
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 intended use—generating a proof for a notarized patron balance—is implied from the purpose statement, but the description does not state when to choose this tool over related siblings or mention any exclusions/prerequisites. This leaves the agent to infer the selection criteria.
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.