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beepboop2025

Seiche — Funding and FX Evidence

Current funding-stress read

funding_stress_now
Read-onlyIdempotent

Read the current USD funding-stress regime and drivers, returning a 0-100 composite index with component breakdown and data faults. Use for headline regime, drivers, and data freshness.

Instructions

Read the current US dollar funding-stress conclusion. Choose this for the headline regime and its drivers; use money_market_context for detailed rate and liquidity metrics, or data_health to inspect input freshness. Returns a 0-100 composite index, the regime (CALM/EROSION/STRAIN/STRESS), per-component decomposition, the market-stress 'Tell', and any data faults. Preserve the source dates and missing evidence when reporting the reading.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoFalse for a tool failure.
tellNo
as_ofNo
proofNo
faultsNo
reasonNo
schemaNo
statusNo
readingNo
versionNo
categoryNo
deliveryNo
headlineNo
compositeNo
editorialNo
conclusionNo
data_qualityNo
generated_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.16.5

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds real behavioral value beyond that: it tells the agent the reading is a 0-100 composite with named regimes and per-component decomposition, and instructs it to preserve source dates and missing evidence when reporting — a non-obvious reporting constraint.

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 sentences, front-loaded with the purpose, then routing, then reporting constraint. Dense but every clause carries distinct information — no restatement of the name or title.

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?

An output schema exists, so return values need not be enumerated, yet the description still summarizes the payload shape (index, regime, decomposition, Tell, data faults) and adds the evidence-preservation rule. With annotations covering safety, nothing an agent needs 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.

Parameters4/5

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

The tool takes no parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description correctly presents this as a zero-argument read rather than implying hidden inputs.

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: 'Read the current US dollar funding-stress conclusion.' It further names the headline scope (regime and drivers), which distinguishes it from the metric-detail tools in the same family.

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?

Explicit routing: 'Choose this for the headline regime and its drivers; use money_market_context for detailed rate and liquidity metrics, or data_health to inspect input freshness.' Both alternatives are named with the condition that selects them.

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