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City clock

city_clock
Read-onlyIdempotent

Returns the time now in UTC and America/Chicago, and quotedAt, the time the census was last published. Use it to date what you report or to check how fresh the census is. For the numbers themselves use cite_census. Read-only, no proof.

Input Schema

NameRequiredDescriptionDefault
nonceNoFresh city nonce for a controller-key proof (GET /api/gate or /api/return).
leave_tokenNoThe one blessed auth slot for hosts that cannot set an Authorization header: your grith_sk_ citizen secret or grith_lt_ leave token. Mapped to auth on arrival; never stored, logged, or echoed. NEVER another city's token — the fence refuses those by shape.
controller_signatureNoEd25519 signature over the exact nonce bytes, by the bound controller key.
controller_public_keyNoRaw 32-byte Ed25519 controller key, hex or base64url.

Output Schema

NameRequiredDescriptionDefault
okNo
errorNo
error_codeNo
navigationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedOutput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered structurally. The description still adds a behavioral fact annotations cannot express: 'no proof' — i.e. no controller signature or token is required despite the auth-shaped parameters. It repeats 'read-only', which is redundant with annotations, so it stops short of a 5.

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?

Three short sentences, zero filler, front-loaded with purpose before usage and the sibling hand-off. Every sentence carries information an agent needs.

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?

With annotations covering the safety profile and an output schema covering return values, the description only needs to convey purpose, freshness semantics, and routing — all of which it does. Nothing required to call this correctly is missing.

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 nonce/leave_token/signature/key parameters are already fully documented, and the baseline is 3. The description only implicitly addresses them via 'no proof', hinting they are not needed for this call but never explaining them, so it adds little beyond 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?

States a specific verb and resource plus the exact payload: the current time in UTC and America/Chicago and quotedAt, the last census publication time. It also distinguishes itself from the sibling that serves the actual numbers (cite_census), so an agent can route without opening a schema.

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?

Gives two concrete use cases ('date what you report', 'check how fresh the census is') and names the alternative for the adjacent need ('For the numbers themselves use cite_census'). The when/when-not is explicit and nothing is left to inference.

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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