sf-ai-agentforce-testing

これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。

---
name: sf-ai-agentforce-testing
description: >
  Agentforce agent testing with dual-track workflow and 100-point scoring.
  TRIGGER when: user tests Agentforce agents, runs sf agent test commands, creates
  test specs, validates topic routing, or analyzes agent test coverage.
  DO NOT TRIGGER when: Apex unit tests (use sf-testing), building agents
  (use sf-ai-agentforce), or Agent Script DSL (use sf-ai-agentscript).
license: MIT
compatibility: "Requires API v66.0+ (Spring '26) and Agentforce enabled org"
metadata:
  version: "2.1.0"
  author: "Jag Valaiyapathy"
  scoring: "100 points across 7 categories"
---

# sf-ai-agentforce-testing: Agentforce Test Execution & Coverage Analysis

Use this skill when the user needs **formal Agentforce testing**: multi-turn conversation validation, CLI Testing Center specs, topic/action coverage analysis, preview checks, or a structured test-fix loop after publish.

## When This Skill Owns the Task

Use `sf-ai-agentforce-testing` when the work involves:
- `sf agent test` workflows
- multi-turn Agent Runtime API testing
- topic routing, action invocation, context preservation, guardrail, or escalation validation
- test-spec generation and coverage analysis
- post-publish / post-activate test-fix loops

Delegate elsewhere when the user is:
- building or editing the agent itself → [sf-ai-agentforce](../sf-ai-agentforce/SKILL.md) or [sf-ai-agentscript](../sf-ai-agentscript/SKILL.md)
- running Apex unit tests → [sf-testing](../sf-testing/SKILL.md)
- creating seed data for actions → [sf-data](../sf-data/SKILL.md)
- analyzing session telemetry / STDM traces → [sf-ai-agentforce-observability](../sf-ai-agentforce-observability/SKILL.md)

---

## Core Operating Rules

- Testing comes **after** deploy / publish / activate.
- Use **multi-turn API testing** as the primary path when conversation continuity matters.
- Use **CLI Testing Center** as the secondary path for single-utterance and org-supported test-center workflows.
- Interactive and programmatic CLI preview use standard `sf org login web` authentication; **ECA is only required for Agent Runtime API testing**, not for live preview.
- Fixes to the agent should be delegated to **[sf-ai-agentscript](../sf-ai-agentscript/SKILL.md)** when Agent Script changes are needed.
- Do **not** use raw `curl` for OAuth token validation in the ECA flow; use the provided credential tooling.

### Script path rule
Use the existing scripts under:
- `~/.claude/skills/sf-ai-agentforce-testing/hooks/scripts/`

These scripts are pre-approved. Do not recreate them.

---

<a id="phase-0-prerequisites--agent-discovery"></a>

## Required Context to Gather First

Ask for or infer:
- agent API name / developer name
- target org alias
- testing goal: smoke test, regression, coverage expansion, or bug reproduction
- whether the agent is already published and activated
- whether the org has **Agent Testing Center** available
- whether **ECA credentials** are available for Agent Runtime API testing

Preflight checks:
1. discover the agent
2. confirm publish / activation state
3. verify dependencies (Flows, Apex, data)
4. choose testing track

---

## Dual-Track Workflow

### Track A — Multi-turn API testing (primary)
Use when you need:
- multi-turn conversation testing
- topic re-matching validation
- context preservation checks
- escalation or action-chain analysis across turns

Requires:
- ECA / auth setup
- agent runtime access

### Track B — CLI Testing Center (secondary)
Use when you need:
- org-native `sf agent test` workflows
- test spec YAML execution
- quick single-utterance validation
- CLI-centered CI/CD usage where Testing Center is available

### Quick manual path
For manual validation without full formal testing, use preview workflows first, then escalate to Track A or B as needed.

---

## Recommended Workflow

### 1. Discover and verify
- locate the agent in the target org
- confirm it is published and activated
- confirm required actions / Flows / Apex exist
-