/agentforce-d360-analyze

name: agentforce-d360-analyze
description: "Data Cloud 360° view of a single Agentforce session. TRIGGER when user asks to trace, inspect, summarize, or describe a specific Agentforce session by session id (Agent Session UUID `019d…` or MessagingSession id `0Mw…`). Also triggers on session discovery — find/list/search sessions by time, agent, channel, outcome, or conversation text — when the user has no session id yet. DO NOT TRIGGER for design-time architecture questions (use agentforce-architecture-analyze instead) or for runtime perf/latency/SLO questions that require platform telemetry beyond Data Cloud."
metadata:
  cliTools:
    - tool: ["python3"]
      semver: ">=3.10.0"
    - tool: ["sf"]
      semver: ">=2.0.0"
  relatedSkills:
    - "agentforce-architecture-analyze"
  version: "1.0"
  minApiVersion: "66.0"

agentforce-d360-analyze — Data Cloud 360° session view

Hierarchical session reconstruction from Data Cloud STDM + GenAI DMOs for one Agentforce session. Three stages — fetch → assemble → render. Typical wall-clock: ~10–30s for a ~15-turn session.

The pipeline is **DC-only**: it reads runtime audit rows that Data Cloud has materialized. It is **not** a runtime-availability tool — see "DC-only blind spot" below for what this skill cannot answer.

If the user hasn't given enough to proceed

When invoked with no session id AND no discovery criteria, print this block **verbatim** — do not paraphrase, do not pre-run any script. Trigger condition: the input is empty OR contains no session-id shape (neither a UUID nor a `0Mw…` messaging id) AND no discovery expression (no time phrase / `--agent` / `--channel` / `--outcome` / `--grep` / verbs like "find" / "list").

> Which session should I pull from Data Cloud, and in which org? > > I need: > - **Session id** — either an Agent Session UUID (`019db7f6-…`) or a MessagingSession id (`0Mw…`, 15/18 chars). > - **No session id?** — Tell me what you remember and I'll find it: how recent (e.g. "last 2 hours", "today", a date), which agent, which channel (Messaging / Builder / Voice), how it ended (escalated, user ended, transferred, timed out), or a phrase from the conversation. I'll show matching sessions as a numbered list — you pick one, I pull it. > - **Org alias** — for `sf` CLI auth (the alias you configured with `sf org login`). > > Artifacts land in `~/.vibe/data/agentforce-d360-analyze/<org_id15>/<agent>__<ver>/<session_id>/` (override per-script with `--data-dir <path>`).

Session id forms — UUID or MessagingSession id

Both forms are accepted on `--session`:

| Form | Example | Resolution | |---|---|---| | Agent Session UUID | `019dface-0000-7000-8000-000000000002` | Pass-through | | MessagingSession id (`0Mw` prefix) | `0MwTESTMSG12345AAA` | Resolved via `resolve_session.py` — live DC lookup on first fetch, disk-first thereafter |

**Multi-match is real.** One MessagingSession id can map to multiple Agent Session UUIDs. On multi-match the resolver prints every candidate and exits non-zero; the user re-invokes with a specific UUID.

Artifacts always land under `~/.vibe/data/agentforce-d360-analyze/<org_id15>/<agent>__<ver>/<session_id>/` (default; overridable per-script with `--data-dir <path>`) — the messaging id is a lookup key only, never a directory name. The dominant agent (first in `sorted(agents_observed)`) names the `<agent>__<ver>/` segment.

Resolving the script prefix

The default install puts the skill under the runtime's plugin root. If the skill was cloned somewhere else (e.g. directly from the `forcedotcom/sf-skills` repo into a custom path), set `PLUGIN_ROOT` to point at the runtime's skills directory.

prefix="${SKILL_ROOT:-${PLUGIN_ROOT:-$HOME/.vibe/skills}/agentforce-d360-analyze}/scripts"

Every subsequent invocation in this doc uses `"$prefix/..."`.

Session discovery (no id yet)

When the user doesn't have a session id, run `discover_sessions.py` against the STDM session DMO. Prints a numbered picker; user picks one; proceed with the chosen UUID.

python3 "$prefix/discover_sessions.py" --org <alias> [filters...]

**Filters** (all optional except `--org`): `--since <expr>` (default last 24h; accepts "last 2 hours", "today", ISO dates), `--agent <api-name>`, `--channel <Messaging|Builder|Voice>`, `--outcome <USER_ENDED|ESCALATED|TRANSFERRED|TIMEOUT|NOT_SET>`, `--grep <substring>` (conversation text), `--tz <IANA>`, `--limit <N>` (default 20).

**Output**: markdown table with `#`, `UUID`, `Start (UTC)`, `Agent`, `Channel`, `Duration`, `Outcome`. User replies with a number; proceed with that UUID.

Pipeline — three stages

fetch_dc.py     →  24 dc.<name>.json + dc._session_manifest.json     (DC Query REST waterfall, 5 waves)
assemble_dc.py  →  dc._session_tree.json                             (pure in-memory hierarchical join)
render_dc.py    →  dc._session_summary.md                            (human summary, multi-section)

Each stage is independently runnable. `fetch_dc.py --session <sid> --org <alias>` chains all three by default.

Invocation

python3 "$prefix/fetch_dc.py" --session <session-id-or-messaging-id> --org <alias>

Flags: `--verbose` for per-DMO row counts; `--no-assemble` / `--no-render` to stop early. All entry scripts (`fetch_dc.py`, `assemble_dc.py`, `render_dc.py`, `resolve_session.py`, `discover_sessions.py`) accept `--data-dir <path>` and `--cache-dir <path>` to override the default `~/.vibe/{data,cache}/agentforce-d360-analyze/` roots — pass these when the host runtime needs artifacts under a different distribution layout.

Output artifacts

Everything lands under `~/.vibe/data/agentforce-d360-analyze/<org_id15>/<agent>__<ver>/<session_id>/` (default; override with `--data-dir <path>`):

dc.sessions.json              dc.steps.json                dc.gateway_requests.json
dc.interactions.json          dc.messages.json             dc.gateway_responses.json
dc.participants.json          dc.generations.json