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failover_verdict

Read-only

Determines the best operational provider to fail over to from a degraded provider, using live incident data and route-verdict fusion. Free preview or full tier with ranked alternatives.

Instructions

Provider A is degraded; TensorFeed's signed ruling on the single best operational provider to fail over to for a task right now. Confirms A against the live incident-triage feed, then runs the route-verdict fusion with A (and any provider already in failover) excluded. Requires from. tier='preview' (default) is free (10 calls per day per IP), the failover target only. tier='full' costs 1 credit ($0.02), adds the full candidate (pricing, measured p95 latency, quality), the ranked alternatives, the confirmed incident on A, and an AFTA-signed receipt, and needs a TENSORFEED_TOKEN. Get credits at tensorfeed.ai/developers/agent-payments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNo'preview' (default, free) or 'full' (1 credit; adds candidate detail, ranked alternatives, incident, signed receipt).
fromYesThe degraded provider to fail over FROM (e.g. "anthropic", "openai"). Required.
taskNoTask type to optimize the failover target for. Optional.
Behavior5/5

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

Beyond annotations (readOnlyHint true), the description discloses internal process (confirms against live feed, fusion, exclusion), tier behavior with return differences, rate limits (10 calls/day per IP for preview), auth requirements (TENSORFEED_TOKEN for full), and cost ($0.02 for full). No contradiction with annotations.

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 front-loaded with the core purpose, then efficiently covers process, tier details, and requirements. It is packed with information without being verbose.

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 no output schema, the description explains return values for both tiers in detail (candidate, latency, quality, alternatives, incident, receipt). It also covers credits and auth. Complete for this tool's complexity.

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 coverage is 100% and parameters are well-described in the schema. The description adds some context for 'from' (degraded provider) and 'tier' (explains differences), but largely repeats schema info. No new semantics for 'task'.

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 states a specific verb ('get ruling') and resource ('single best operational provider to fail over to'), clearly distinguishing this tool from siblings like route_verdict by mentioning 'route-verdict fusion' and 'excluded A and any provider already in failover'.

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 provides context for when to use (when a provider is degraded) and explains tier differences (preview vs full). However, it does not explicitly compare to alternative tools or state when not to use, which would improve clarity.

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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