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get_upstream_status

Check upstream endpoint health before requesting Dubai data to avoid failed fetches. Shows status, last success/failure, and reason for non-working endpoints.

Instructions

Return the current health of every registered upstream endpoint.

Reads from the passive health registry in _shared/health.py. Each upstream entry reports status (working, blocked, degraded, credentials_missing, static, unknown), the endpoint host, whether it requires auth, the last success and last failure timestamps, and the latest reason string if the upstream is not working.

This tool never probes endpoints proactively. Status is derived from what happened during normal tool calls in this process, plus static state declared at bootstrap (known Cloudflare blocks, credential availability, and features that ship without any upstream call).

LLM agents should call this before attempting Tier 1 (Dubai Pulse) or FCSC work, to avoid asking the server for data it cannot fetch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description fully covers behavior: it never probes proactively, statuses are derived from normal calls and bootstrap state. It lists possible status values and what fields are returned. It lacks mention of rate limits or auth needs, but for a read-only passive tool this is adequate.

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-structured: a clear opening statement, then details on source, behavior, and usage advice. Every sentence adds value without unnecessary repetition. It is concise yet comprehensive.

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?

Given zero parameters and the presence of an output schema (implied from context), the description adequately describes the return information, including status, host, auth requirement, timestamps, and reason. No gaps remain for agent invocation.

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

Parameters4/5

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

There are no parameters, so the description does not need to add parameter info. The baseline for zero params is 4, and no additional explanation is required.

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 clearly states 'Return the current health of every registered upstream endpoint', which is a specific verb plus resource. It distinguishes itself from siblings by focusing on upstream status, a concept not present in any sibling tool name.

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?

The description explicitly advises: 'LLM agents should call this before attempting Tier 1 (Dubai Pulse) or FCSC work, to avoid asking the server for data it cannot fetch.' This provides clear guidance on when to use the tool and what to avoid.

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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