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vmware-skills

io.github.zw008/vmware-debug

build_incident_timeline

Read-onlyIdempotent

Correlate already-fetched VMware events into one incident timeline, surfacing anomalous spikes, ranked root-cause hypotheses and next diagnostic checks. Does not fetch events itself.

Instructions

[READ] Correlate already-fetched VMware events into one incident view.

WHEN: use this after you've pulled events for an incident from the data-source skills (vmware-monitor get_events/get_alarms, vmware-aria list_alerts/list_anomalies, vmware-log-insight search_logs/aggregate_logs, vmware-nsx) — feed them here to find what correlates and where to look next. Not sure which events to pull? Run list_symptom_categories first. This tool does NOT fetch anything itself.

RETURNS: {event_count, window, binning, classification, spikes (strongest anomalous bins), spikes_total, hypotheses (ranked root-cause candidates, each with a suggested_check), next_checks (which skill/tool to run next)}. Read binning for the resolution you were given, and classification for how much of the stream matched nothing — the ranking describes only the part that did.

GOTCHAS: read-only, stateless, no network — nothing is executed. Remediation routes to vmware-aiops (single fix) or vmware-pilot (multi-step). A malformed event returns {error, hint} naming the offending index.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoHow many ranked hypotheses come back (default 5). Spikes are capped separately at 20, true count in 'spikes_total'.
eventsYesEvent envelopes, each {ts, source, severity, entity, text, fields}. ts may be ISO-8601, epoch seconds or epoch millis and is required; severity is normalised onto critical/error/warning/ info/unknown, so vendor spellings (fatal, red, warn, yellow, notice, green) are accepted. An entry that cannot be normalised is refused with its index, not skipped. Keep each event's event_type in fields — vmware-monitor's get_events returns it, and the symptom classifier matches it alongside the message. On a modern EventEx the message is generic boilerplate and the eventTypeId is the only thing that says what happened, so dropping it turns a readable event into an uncategorized one.
bin_secondsNoTime-bin width in seconds. Omit and it is chosen from event density off the ladder 1/10/60/300/900/3600/21600/86400, taking the finest width still averaging 4 events per bin.
z_thresholdNoStandard deviations above the mean bin count that mark a spike (default 2.0). Under 3 bins, or a flat series, yields none at any threshold — empty spikes is not "calm".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.3.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, but the description adds context beyond them: stateless, no network, nothing executed, remediation routed to vmware-aiops or vmware-pilot, and explicit failure behavior ({error, hint} naming the offending index rather than skipping). That is substantive behavioral disclosure.

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?

Labeled WHEN/RETURNS/GOTCHAS sections front-load the routing decision before the return shape, and each line carries information. The RETURNS block is long, but with no output schema it is doing necessary work rather than padding.

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 full return contract (event_count, binning, classification, spikes/spikes_total, hypotheses with suggested_check, next_checks) plus error shape and follow-on routing. Nothing an agent needs to call or interpret this tool is missing.

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 description coverage is 100% and the schema already documents ts formats, severity normalization, binning ladder and z_threshold caveats, so the baseline is 3. The description mostly reiterates this; its only added guidance (keep event_type in fields) duplicates the schema text rather than extending it.

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 ('Correlate already-fetched VMware events into one incident view') and draws a hard boundary that separates it from the data-source siblings: 'This tool does NOT fetch anything itself.' An agent can distinguish this from get_events/list_alerts 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?

The WHEN block names the upstream skills whose output feeds this tool, gives an explicit prerequisite (list_symptom_categories first when unsure what to pull), and states the exclusion ('does NOT fetch'). Use-vs-alternative routing is fully specified.

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