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Glama

tollbooth-sample

by io.github.lonniev

weather_session_status

Check operator readiness. Returns the operator lifecycle state and clear guidance on what to do next. Free.

Lifecycle states:

  • ready: Operator is warm and fully operational — vault AND pricing model verified. Proceed with tool calls.

  • warming_up: Operator is initializing (cold start). Try a tool call — it will warm up on demand.

  • misconfigured: Persistence rejected a query with a permanent SQL error (permission denied, missing relation). Paid tools will fail until the operator repairs the database — retrying does not help.

  • quota_exceeded: The persistence provider (Neon) answered HTTP 402 — the operator's database has exhausted its compute/storage quota, so the books are locked for billing. Paid tools fail; retrying does NOT help. The operator's Authority must restore capacity (upgrade the plan or wait for the quota reset). Free tools remain available.

  • not_registered: Operator has no Authority relationship yet. Call register_operator first.

  • no_identity: Operator nsec is not configured. Deployment issue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patron_npubNoOptional. If supplied, the response includes an ``upstream_oauth`` block with the patron's stored OAuth token expiry (runtime-derived from vault state) so a client can refresh proactively rather than reactively after a stale-token failure.

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

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It explains states and failure modes, including retry advice and availability of free tools. It implies read-only behavior but does not explicitly state no side effects, missing a slight transparency opportunity.

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

Conciseness4/5

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

The description is lengthy but well-structured with bullet points for lifecycle states. Every sentence adds value; it is front-loaded with the purpose. Could be slightly more concise, but clarity justifies length.

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

Completeness4/5

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

Given an output schema exists (not shown), the description explains return values adequately via state enumeration and guidance. It covers all states and actionable next steps, though exact response shape is not detailed.

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 schema already explains the optional patron_npub parameter well. The tool description adds no extra parameter details, but the schema suffices; baseline 3 applies.

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 explicitly states 'Check operator readiness' and details lifecycle states, clearly distinguishing this tool from siblings that handle other weather-related operations.

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

Usage Guidelines5/5

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

Provides explicit guidance per lifecycle state (e.g., 'Proceed with tool calls' for ready, 'Try a tool call' for warming_up, and instructions to not retry for misconfigured and quota_exceeded, including alternatives like repairing or upgrading). It also notes prerequisites (e.g., register_operator first for not_registered).

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

All tollbooth-sample toolsInspect
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TDQS

B3.4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions, and the few similar pairs (e.g., check_balance vs check_authority_balance, account_statement vs account_statement_infographic) are well-differentiated by their descriptions. However, some overlapping concepts like forget_credentials vs delete_patron_credential/delete_operator_credential could still cause misselection without careful reading.

Naming Consistency2/5

All tools share the misleading 'weather_' prefix, which does not reflect their actual domain (billing, credentials, coupons, notarization). Naming patterns are inconsistent, mixing verb_noun (check_balance, list_coupons) with noun-ish names (account_statement, current, forecast) and varied verbs (get, list, check, request, receive, update, delete, forget, mint, redeem, etc.).

Tool Count1/5

With 52 tools, this is an extremely large surface for a sample server. Even though the domain is broad, this count far exceeds the typical well-scoped MCP server and creates unnecessary complexity for agents to navigate.

Completeness4/5

The tollbooth/billing domain is well-covered: credit purchasing, coupons, credentials, proofs, pricing models, notarization, and operator/patron status. Minor gaps exist (e.g., no single-coupon getter, no direct patron list), but core workflows have no dead ends. The weather aspect is thin with only three tools, but that seems intentional as an example paid service.

Resources