afv-library/skills/investigating-agentforce-d360/scripts/config.py

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@W-22707610 feat: add investigating-agentforce-d360 skill Data Cloud 360° view of a single Agentforce session — DC-only, zero Splunk dependency. Pulls 24 STDM + GenAI DMOs via the Data Cloud Query REST API, assembles a hierarchical session tree (Interaction → Step → Generation → GatewayRequest), and renders a human-readable markdown summary with transcript + per-turn topic/action invocations + LLM generations + tool calls + audit chain. Migrated as a standalone Apache-2.0 skill from an internal hub plugin — self-contained, no sibling-skill or plugin dependencies. What this skill answers: - "Trace session <uuid>" / "Summarize what happened in <0Mw…>" - "Find escalated sessions today on Messaging in <org>" - Session discovery by time / agent / channel / outcome / conversation text when the user has no session id What it does NOT answer (use a different surface): - Design-time architecture — use investigating-agentforce-architecture - Runtime planner availability — DC alone can't tell you which topic/action was eligible for the classifier on a given turn Skill layout: - 8 Python pipeline modules (fetch_dc, assemble_dc, render_dc, discover_sessions, resolve_session, dc, storage, config) - 4 _shared helpers (paths, fs_guard, sql, __init__) with skill-scoped DATA_ROOT (~/.claude/data/investigating-agentforce-d360/) - 26 SQL templates under assets/dc/ - 27 test files (367 tests + 18 subtests, 100% passing) - 3 reference docs (artifacts.md, dc_dmo_fields.md, dc_pipeline_contract.md) - SKILL.md (sf-skills frontmatter, license: Apache-2.0, metadata.version: "1.0") - README.md (external-facing quick-start) - tools/grant_allowlist.py (idempotent first-run permission grant) - tools/archive_data_dir.sh (opt-in stop-hook tarballer) Quality gates: - pytest scripts/tests/: 367 passed + 18 subtests, 0 failures - npm run validate:skills: 62 of 62 skill(s) checked, 0 errors - Live end-to-end runs against 3 real Salesforce sessions exercising both the full-tree and STDM-lag gateway-direct render branches - 4 independent code-review rounds (correctness, security, markdown, architecture-critic) — all findings addressed Customer-data hygiene: no live tenant ids, no internal sprint markers, no hub/sibling-skill references. Synthetic fixtures look obviously synthetic (`019dface-…` UUIDs, `0MwTESTMSG…` MessagingSession ids, `00DTESTORG…` org ids, `MyAgent` placeholder agent name). Sibling skill: investigating-agentforce-architecture (PR #278) — same migration pattern, design-time metadata; complementary scope.
2026-05-28 18:57:52 +08:00
"""Shared constants for investigating-agentforce-d360.
Values that don't vary per environment or user live here. If a value
needs to be overridable at runtime in the future, swap this module for
a loader callers won't notice.
Path layout::
~/.claude/data/investigating-agentforce-d360/
<org_id_15>/
<agent_api_name>__<agent_version>/
<session_id>/ session artifacts
``DATA_ROOT`` is re-exported from the canonical helper in
``scripts/_shared/paths.py`` (sibling module, inlined at the skill
boundary). All session-dir composition MUST go through
``paths.session_dir(...)`` never compose ``DATA_ROOT / <sid>``
directly, because that bypasses the 4-segment regex validation.
"""
from __future__ import annotations
import sys
from pathlib import Path
# Data Cloud Query API — the instance_url prefix is resolved at runtime
# via `sf org display --target-org <alias> --json` (Claude does that,
# not python). Python only owns the path.
DC_API_PATH = "/services/data/v66.0/ssot/query"
# -----------------------------------------------------------------------------
# Shared path helpers — sibling _shared/ package
# -----------------------------------------------------------------------------
_SCRIPTS_DIR = Path(__file__).resolve().parent
if str(_SCRIPTS_DIR) not in sys.path:
sys.path.insert(0, str(_SCRIPTS_DIR))
from _shared import paths # type: ignore # noqa: E402,F401 — re-export
from _shared import sql # type: ignore # noqa: E402,F401 — re-export
# One persistent tree per session. Writes land directly here — no
# ephemeral /tmp staging. Re-running the same session id finds prior
# results, which later enables per-artifact caching.
DATA_ROOT = paths.DATA_ROOT