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Agentforce observe

Skill divingsbysangam/salesforce-compound-engineering-plugin/skills/agentforce-observe

Analyze production Agentforce agent behavior using STDM session traces in Data Cloud, plus a fallback path using sf agent test + sf agent preview --authoring-bundle when STDM is unavailable. Use when investigating production failures, regressions, or performance regressions; querying ssot__AiAgentSession__dlm; reproducing reported issues in preview; or improving the .agent file based on production evidence. Trigger phrases: 'why is my agent failing in production', 'analyze production sessions', 'investigate this Agentforce regression', 'what happened in this session', 'reproduce this production issue', 'find sessions where the agent misrouted'. Do NOT trigger for first-time authoring (`agentforce-develop`) or planned test-suite work (`agentforce-test`).From its SKILL.md

Install

npx -y skills add divingsbysangam/salesforce-compound-engineering-plugin --skill agentforce-observe

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

10 stars10 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.2 KB, as published. Nobody here has run it

<span data-proof="authored" data-by="ai:claude">/agentforce-observe</span>

<span data-proof="authored" data-by="ai:claude">Principles enforced:</span> <span data-proof="authored" data-by="ai:claude">7 (outsource thinking, not understanding), 3 (jagged intelligence in production), 5 (taste / drift detection), 1 (preserve the quality ceiling). See</span> <span data-proof="authored" data-by="ai:claude">PRINCIPLES.md.</span>

Required reads

Procedure lives in sibling files, not only in this orchestrator:

When to use this skill — read references/when-to-use-this-skill.md before acting on this section.
Inputs to gather before starting — read references/inputs-to-gather-before-starting.md before acting on this section.
Phase 0: Discover the Data Space — read references/phase-0-discover-the-data-space.md before acting on this section.
Phase 1: Observe — query STDM (preferred path) — read references/phase-1-observe-query-stdm-preferred-path.md before acting on this section.
Phase 1-ALT: Fallback when STDM is unavailable — read references/phase-1-alt-fallback-when-stdm-is-unavailable.md before acting on this section.
Phase 2: Reproduce — live preview, 3-run classification — read references/phase-2-reproduce-live-preview-3-run-classification.md before acting on this section.
Phase 3: Improve — edit the .agent file directly — read references/phase-3-improve-edit-the-agent-file-directly.md before acting on this section.
Capture learnings — read references/capture-learnings.md before acting on this section.
Inspiration — read references/inspiration.md before acting on this section.

<span data-proof="authored" data-by="ai:claude">Copy-paste-to-agent</span>

Improve a deployed Agentforce agent using session-trace evidence. Three phases: (1) Observe
— query STDM session traces from Data Cloud (or fall back to sf agent test + sf agent preview
--authoring-bundle when STDM is unavailable); (2) Reproduce — re-run problematic conversations
in sf agent preview, classify CONFIRMED / INTERMITTENT / NOT REPRODUCED across 3 runs; (3)
Improve — edit the .agent file with targeted fixes, validate, publish, activate, then verify
in preview and post 24-48h re-run Phase 1 against baseline. Always pass --json on every sf
CLI command. Always re-run safety probes after any fix. Fail-closed: if STDM cannot run,
use Phase 1-ALT and record `stdm=unavailable: <reason>` — do not invent production
evidence. If preview also cannot run, stop; do not mark the issue reproduced.

Cross-skill integration

Need	Delegate to	Reason
Author or republish the `.agent` file	`agentforce-develop`	Observe proposes; develop publishes
Add a regression suite for the fix	`agentforce-test`	Repeatable probes
Apex/Flow backing bug	`apex-generate` / `flow-generate`	Code, not script
Capture a production misroute pattern	`sf-compound`	Institutional memory

Keep looking

Skills are one crate of 628,853. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.