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industrial-aiops

OT-AIops Energy

alarm_flood_analysis

Read-only

Identifies ISA-18.2 alarm flood episodes, chattering, and stale alarms, with advisory suppression values for operator review.

Instructions

[READ][risk=low] ISA-18.2 deep alarm-flood analysis: episodes + chattering + stale + advice.

Deepens alarm_bad_actors: detects flood *episodes* (start/end/count/peak rate/
top contributors + each episode's first-out annunciation, per ISA-18.2's >=10
alarms per 10 min per operator), alarms chattering ACTIVE↔CLEARED, standing/
stale alarms, and percent-time-in-flood vs the ISA-18.2 targets (~1-2 alarms/
10 min steady state, <1% time in flood). Also returns an ISA-18.2 'load_profile'
(per-bucket rate band + peak period + trend) and per-source 'suppression_advice'
(deadband/on-off-delay for chatter, time-limited shelve for standing alarms).
The suppression advice is ADVISORY ONLY — starting values for a human to review
and approve via your ISA-18.2 / management-of-change process; this tool never
applies suppression, shelving, deadband, or delay changes. Pass 'events' for
pure analysis, or an endpoint to collect live via the same OPC-UA active-
condition scan the RCA copilot uses (polled over duration_s; other protocols
contribute no alarms). Output is bounded; 'truncated' flags say when caps bit.

Args:
    endpoint: Endpoint name from config (used only when events is omitted).
    duration_s: Live collection window in seconds (1..300, default 60).
    window_s: Flood analysis window in seconds (ISA-18.2 default 600).
    threshold: Annunciations per window that start a flood (default 10).
    events: Injected alarm events — {source, timestamp (ISO-8601), state?
        (ACTIVE/RTN/CLEARED)}; skips live collection entirely.
    stale_after_s: Continuously-active age that marks a standing alarm (default 24h).
    max_episodes: Cap on returned flood episodes (default 20).
    max_rows: Cap on chattering / stale / suppression-advice / worksheet rows (default 50).
    load_bucket_s: Load-profile bucket width in seconds (ISA-18.2 default 600 = 10 min).

Returns dict: {event_count, summary:{insufficient_data, percent_time_in_flood,
    avg_alarms_per_10min, peak_alarms_per_10min, isa_18_2_targets, ...},
    load_profile:{overall_band, peak_bucket, band_distribution, trend,
    busiest_buckets:[...], ...}, flood_episodes:[{start, end, ..., top_contributors,
    first_out:{source, ts}}], chattering:[{source, cycles, cycles_per_hour, ...}],
    stale_standing:[{source, active_since, active_for_s}], suppression_advice:[{source,
    kind, technique, suggested_on_delay_s, suggested_off_delay_s, suggested_shelve_max_s,
    basis, advisory}], worksheet_preview:[...], advisory_note, truncated:{...}, collected?}.

Example: alarm_flood_analysis(events=[{"source":"FIC101",
    "timestamp":"2026-06-28T10:00:00Z","state":"ACTIVE"}, ...]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventsNo
endpointNo
max_rowsNo
window_sNo
thresholdNo
duration_sNo
max_episodesNo
load_bucket_sNo
stale_after_sNo
Behavior5/5

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

Even with annotations indicating readOnly/openWorld/non-destructive, the description adds substantial behavioral depth: it never applies suppression/shelving/deadband/delay changes, output is bounded with truncation flags, and live collection is limited to the OPC-UA active-condition scan. This goes far beyond the annotations and explains non-obvious side effects and limitations.

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?

Though long, the description is efficiently structured: a one-line summary, a detailed paragraph, then Args/Returns/Example sections. Every sentence adds information; there is no filler or tautology. The density is warranted for a tool with 9 parameters and a rich output shape.

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?

There is no output schema, so the description's detailed 'Returns dict' fills the gap with field names and nested structures. It also covers collection methods, advisory semantics, truncation behavior, and supplies a concrete example. For a complex analytical tool, this is a complete and self-sufficient specification.

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 description coverage is 0%, but the Args section fully compensates by explaining all 9 parameters with meanings, defaults, and relationships (e.g., 'endpoint used only when events is omitted', 'events skips live collection entirely', 'stale_after_s: Continuously-active age that marks a standing alarm'). This adds critical semantics the schema lacks.

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 opens with a specific verb and resource ('ISA-18.2 deep alarm-flood analysis') and lists concrete outputs (episodes, chattering, stale, advice). It explicitly differentiates from the sibling tool alarm_bad_actors by stating 'Deepens alarm_bad_actors', making the tool's unique scope unmistakable.

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?

Provides clear situational guidance: 'Pass events for pure analysis, or an endpoint to collect live' and warns that 'other protocols contribute no alarms' (an explicit exclusion). The advisory-only caveat tells the agent this tool is not for applying changes, effectively distinguishing it from mutation-oriented siblings.

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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