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 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 decide whether Track A or Track B fits the request 2. Plan tests Cover at least: main topics expected actions guardrails / off topic handling escalation behavior phrasing variation 3. Execute the right track Track A validate ECA credentials with the provided tooling retrieve metadata needed for scenario generation run multi turn scenarios with the provided Python scripts analyze per turn failures and coverage Track B generate or refine a flat YAML test spec run sf agent test commands inspect structured results and verbose action output 4. Classify failures Typical failure buckets: topic not matched wrong topic matched action not invoked wrong action selected action invocation failed context preservation failure guardrail failure escalation failure 5. Run fix loop When failures imply agent authoring issues: delegate fixes to [sf ai agentscript](../sf ai agentscript/SKILL.md) re publish / re activate if needed re run focused tests before full regression Testing Guardrails Never skip these: test only after publish/activate include harmful / off topic / refusal scenarios use multiple phrasings per important topic clean up sessions after API tests keep swarm execution small and controlled Avoid these anti patterns: testing unpublished agents treating one happy path utterance as coverage storing ECA secrets in repo files debugging auth with brittle shell expanded curl commands changing both tests and agent simultaneously without isolating the cause Output Format When finishing a run, report in this order: 1. Test track used 2. What was executed 3. Pass/fail summary 4. Coverage gaps 5. Root cause themes 6. Recommended fix loop / next test step Suggested shape: Cross Skill Integration Need Delegate to Reason fix Agent Script logic [sf ai agentscript](../sf ai agentscript/SKILL.md) authoring and deterministic fix loops create test data [sf data](../sf data/SKILL.md) action ready data setup fix Flow backed actions [sf flow](../sf flow/SKILL.md) Flow repair fix Apex backed actions [sf apex](../sf apex/SKILL.md) Apex repair set up ECA / OAuth for Agent Runtime API [sf connected apps](../sf connected apps/SKILL.md) auth and app configuration analyze session telemetry [sf ai agentforce observability](../sf ai agentforce observability/SKILL.md) STDM / trace analysis Reference Map Start here [references/interview wizard.md](references/interview wizard.md) [references/multi turn testing.md](references/multi turn testing.md) [references/cli commands.md](references/cli commands.md) [references/test spec reference.md](references/test spec reference.md) Execution / auth [references/execution protocol.md](references/execution protocol.md) [references/multi turn execution.md](references/multi turn execution.md) [references/eca setup guide.md](references/eca setup guide.md) [references/credential convention.md](references/credential convention.md) [references/connected app setup.md](references/connected app setup.md) Coverage / fix loops [references/coverage analysis.md](references/coverage analysis.md) [references/agentic fix loops.md](references/agentic fix loops.md) [references/results scoring.md](references/results scoring.md) [references/known issues.md](references/known issues.md) Advanced / specialized [references/agentscript agents.md](references/agentscript agents.md) [references/agentscript testing patterns.md](references/agentscript testing patterns.md) [references/cli testing details.md](references/cli testing details.md) [references/deep conversation history patterns.md](references/deep conversation history patterns.md) [references/swarm execution.md](references/swarm execution.md) [references/trace analysis.md](references/trace analysis.md) [references/agent api reference.md](references/agent api reference.md) Templates / assets [references/test templates.md](references/test templates.md) [references/test plan format.md](references/test plan format.md) [assets/](assets/) Score Guide Score Meaning 90+ production ready test confidence 80–89 strong coverage with minor gaps 70–79 acceptable but coverage expansion recommended 60–69 partial validation only < 60 insufficient confidence; block release

sf-ai-agentforce-testing