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nempulse

by au.com.nempulse
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Battery detail

get_battery_detail
Read-onlyIdempotent

Deep-dive metrics for one battery by DUID (e.g. HPR1 = Hornsdale): revenue, dispatch, SOC, FCAS. WARNING: rev_today, energy_rev_today, fcas_rev_today and contingency_fcas_rev_today are MONTH-TO-DATE by default, not daily (matching the rev_mtd keys in fcas_breakdown) — do not report them as 'today's revenue'. throughput_cycles, throughput_mwh, avg_dispatch_price, avg_charge_price and efficiency_pct cover the same window. Pass date_from and date_to (both required together) to scope this window explicitly, e.g. to a single day, instead of relying on the month-to-date default. For a true daily time series use get_battery_revenue. rte_pct is NOT window-scoped: it is the unit's latest measured round-trip efficiency (fitted from AEMO's reported energy storage against its dispatch over a trailing 30 days, refreshed weekly), and is null for units whose fit has not cleared its acceptance checks — null means 'not measured', never 'inefficient'. Also returns commercial_context (e.g. TOLLED, CONTRACTED) and commercial_note — ALWAYS check commercial_context before comparing this unit's revenue against another unit's: tolled/contracted units do not trade merchant and their spot figures are not comparable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
duidYesBattery DUID, e.g. HPR1. Use list_bess_units to find it from a station name.
date_toNoOptional end date YYYY-MM-DD (requires date_from too).
date_fromNoOptional start date YYYY-MM-DD (scopes revenue/throughput stats; requires date_to too). Omit both for the month-to-date default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / date_from / format
      Added value: +"date"
    • changedInput schema / properties / duid / description
      Previous value: -"Battery DUID, e.g. HPR1"New value: +"Battery DUID, e.g. HPR1. Use list_bess_units to find it from a station name."
  2. Changed2 schema fields changed
    • addedInput schema / properties / date_from
      Added value: +{
+  "description": "Optional start date YYYY-MM-DD (scopes revenue/throughput stats; requires date_to too). Omit both for the month-to-date default.",
+  "type": "string"
+}
    • addedInput schema / properties / date_to
      Added value: +{
+  "description": "Optional end date YYYY-MM-DD (requires date_from too).",
+  "type": "string"
+}
  3. First observed

TDQS

A5/5.0
Behavior5/5

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

With readOnlyHint/idempotentHint already declaring the safety profile, the description still adds substantial non-obvious behavior: rev_today/energy_rev_today/fcas_rev_today/contingency_fcas_rev_today are month-to-date, rte_pct is not window-scoped and null means 'not measured', and the date_from/date_to pair scopes the window. These are exactly the traps an agent would otherwise fall into.

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?

Long but front-loaded and entirely load-bearing: purpose first, then the MTD warning, then window scoping, then the rte_pct caveat, then the commercial_context comparison rule. The all-caps emphasis is used sparingly on the two genuinely dangerous mistakes. No filler sentences.

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?

No output schema exists, so the description carries the return-value burden, and it does: it names returned field groups, explains the MTD vs windowed semantics, defines null rte_pct, and describes commercial_context/commercial_note. Nothing an agent needs to call and interpret this correctly is missing.

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

Parameters5/5

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

Schema coverage is 100% (baseline 3), but the description goes well beyond it: it explains the coupling constraint that date_from and date_to are 'both required together', states what the window actually scopes (revenue/throughput stats) versus what it does not (rte_pct), and clarifies the month-to-date default when omitted.

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 (deep-dive metrics) and resource (one battery by DUID), enumerates the metric families returned (revenue, dispatch, SOC, FCAS), and explicitly distinguishes itself from the sibling get_battery_revenue for daily time series. An agent can tell it apart from the other 10 siblings 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 explicit when-to-use ('for a true daily time series use get_battery_revenue'), how to resolve input ('use list_bess_units to find it from a station name'), and a when-not-to-be-misled rule ('ALWAYS check commercial_context before comparing this unit's revenue against another'). Alternatives and exclusions are both named.

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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