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roastify-mcp

by io.github.lonniev

roastify_report_issue

File a field report about this service as a GitHub issue on the operator's repo.

Found a tool's metadata or response wrong or confusing? Report it where the tool lives. The author of record is your npub — no npub / no proof, no issue — and it is stamped into the issue so the report is attributed to you, not the operator. Costs a small fee (a free write to an issue tracker would be abused). The report is PUBLIC and goes to the maintainers' normal triage; nothing is verified here.

Returns the filed issue's repo, number, and url. If this operator has not enabled field reports, returns an "issue reporting not configured" situation and you are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesThe details — which tool, what was wrong, what you expected.
npubYesYour Nostr public key (npub1...); the report's author of record.
titleYesOne-line summary of the problem.
tool_nameNoOptional: the specific tool the report is about (e.g. "schwab_get_option_chain").
dpop_tokenYesRaw JSON of a kind-27235 Nostr event signed by npub — not base64, not NIP-98 'Authorization: Nostr <b64>' framing. Its `u` tag must hold THIS tool's exact name (from tools/list), not the endpoint URL; content:"", created_at within 60s of now, and a random `nonce` tag recommended. Or a cached dpop_token phrase.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full responsibility and does well: it discloses that the npub is the author of record, the issue is public, a fee is charged, nothing is verified locally, and the report goes to maintainers' normal triage. It also explains the not-configured case where the user is not charged. This is rich behavioral disclosure beyond what the schema or annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized: an opening action statement, a motivational context sentence, behavioral consequences, and a return/error summary. Every sentence adds necessary operational or behavioral detail, and the important constraints are front-loaded. Despite length, it earns its length with high-value information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, prerequisites, costs, privacy/publicity, attribution, expected behavior, return values, and the error case. The schema and output schema provide the remaining parameter and output structural details. An agent has everything needed to decide when and how to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3; the schema already documents all parameters in detail. The description adds contextual meaning around npub and the cost/failure behavior, but it does not meaningfully elaborate the individual parameter semantics beyond the schema. It adequately complements rather than replaces the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'File a field report about this service as a GitHub issue on the operator's repo.' It clearly explains the purpose and provides concrete context ('Found a tool's metadata or response wrong or confusing?'), making it easy to distinguish from the many sibling tools. No sibling has a similar reporting function, so no further differentiation is needed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear conditions for use: report a tool when its metadata or response is wrong or confusing. It also states what happens if the operator has not enabled field reports, which helps the agent anticipate failure. It does not explicitly mention alternatives or when not to use it, but no sibling alternative exists for this action.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness3/5

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.

Resources