agentforce-architecture-analyze

# agentforce-architecture-analyze — declared architecture snapshot Design-time metadata tree for one Agentforce agent: planner → topics → actions → flows → Apex → prompts → NGA plugins. Reads declared metadata only — `BotDefinition`, `GenAiPlanner*`, `GenAiPlugin*`, `GenAiFunction*`, `Flow`, `ApexClass`, `GenAiPromptTemplate`. Does **not** read runtime audit rows. **Runtime budget: 30–45s typical, ≤60s hard cap** on reference fixtures. Sequential baseline would be 90–220s; parallel Tooling SOQL fan-out delivers a 3–5× speedup. Large bots with many flows scale approximately linearly — each flow metadata retrieve is one round-trip. Runs **inline** — no subagent. Every phase is deterministic file processing. ## If the user hasn't named an agent Trigger condition: `$ARGUMENTS` names no agent (no `--agent` flag and no exact `BotDefinition` API name in the prose). Never invent an agent name. Instead, discover what the org actually contains — one read-only query, no pipeline yet. Use the `--org` alias if given, otherwise the default target org (omit `--target-org`): ```bash sf data query --query "SELECT DeveloperName, MasterLabel FROM BotDefinition ORDER BY DeveloperName" \ [--target-org <alias>] --json ``` If the user gave no org alias, the pipeline block defaults `--org` to the CLI default target org itself (`sf config get target-org --json` → `.result[0].value`) — you don't need to resolve it. Then branch on the rows returned: - **Zero agents** — tell the user the org has no Agentforce agents and stop. Do not fabricate an agent or a tree. - **Exactly one agent, or exactly one whose `DeveloperName`/`MasterLabel` matches the user's description** (e.g. "support", "service", "sales") — use it, say explicitly which agent you picked and why, then run the pipeline block below with `ARG_AGENT=<DeveloperName>` (and `ARG_ORG=<alias>` if the user named one) set as its first lines, e.g. `ARG_AGENT=Customer_Support_Agent`. The block reads `ARG_*` from the environment; flags in `$ARGUMENTS` still override. - **Otherwise** — print the block below, with the discovered agents listed as a numbered `DeveloperName — MasterLabel` table under the first line, and wait for the user to pick. - **Query fails** (no default org, auth error) — print the block below without the list. > Which agent should I document, and in which org? > > I need: > - **Agent API name** — the `DeveloperName` of the `BotDefinition` (e.g. `MyAgent`, `MySalesAgent`). Not the label. > - **Org alias** — for `sf` CLI auth (the alias you configured with `sf org login`) > > Optional: > - **Version** — an `agent_version_api_name` like `v5`. If omitted, I'll resolve the active `BotVersion`. > - **`--force`** — ignore cached tree; re-fetch everything. > - **`--reprobe`** — re-run the 7-day channel-probe cache (only needed after a Salesforce release). > > I'll run the metadata pipeline inline. Artifacts land under `~/.vibe/data/agentforce-architecture-analyze/<org_id15>/<agent_api_name>__<agent_version>/` (overridable with `--data-dir`). ## Pipeline invocation Run this block once the agent is known — from `--agent <api_name>` in `$ARGUMENTS`, or preset as `ARG_AGENT=<DeveloperName>` after discovery. `--org` (or `ARG_ORG`) is optional; without it the CLI default target org is used. One `python3` invocation drives the full pipeline. `main.py` writes `.emit_ctx.json`; `emit_result.py` reads it and prints the final `=== RESULT ===` block last to stdout. ```bash set -euo pipefail # zsh arrays are 1-indexed by default; bash arrays are 0-indexed. # This block uses 0-indexed semantics throughout (_args[$i] starting at i=0), # so under zsh + `set -u` the very first read of `_args[0]` would trip # `parameter not set`. KSH_ARRAYS makes zsh treat arrays as 0-indexed, # matching the bash shebang's expectation. No-op under bash. [ -n "${ZSH_VERSION:-}" ] && setopt KSH_ARRAYS # <SKILL_DIR> = absolute path of this skill's own directory (the folder holding # this SKILL.md); substitute it from the skill path in context. Runtimes install # skills in different places, so also probe the known install roots and use the # first that actually contains this skill's scripts. An exported SKILL_ROOT wins. _skill=agentforce-architecture-analyze for _c in "${SKILL_ROOT:-}" "<SKILL_DIR>" \ "${CLAUDE_PLUGIN_ROOT:+$CLAUDE_PLUGIN_ROOT/skills/$_skill}" \ "${VIBES_SKILLS_DIR:+$VIBES_SKILLS_DIR/$_skill}" \ "$HOME/.claude/skills/$_skill" "$PWD/.claude/skills/$_skill" \ "${PLUGIN_ROOT:-$HOME/.vibe/skills}/$_skill"; do [ -n "$_c" ] || continue # Some stagers (ADK eval) nest the bundled files under <skill>/artifacts/. for _r in "$_c" "$_c/artifacts"; do [ -f "$_r/scripts/main.py" ] && { SKILL_ROOT="$_r"; break 2; } done done [ -f "${SKILL_ROOT:-}/scripts/main.py" ] || { echo "$_skill: scripts not found — set SKILL_ROOT to this skill's directory" >&2; exit 1; } # Argument parser. Accepts both `--org foo` and `--org=foo`. # `$ARGUMENTS` is the raw user input Claude Code substitutes; it may be unset # or plain prose. Each ARG_* starts from the environment, so a value resolved # during discovery can be preset (e.g. `ARG_AGENT=MyAgent` on the first line); # flags in $ARGUMENTS still override. ARG_ORG="${ARG_ORG:-}" ARG_AGENT="${ARG_AGENT:-}" ARG_VERSION="${ARG_VERSION:-}" ARG_FORCE="${ARG_FORCE:-}" ARG_REPROBE="${ARG_REPROBE:-}" ARG_PARALLELISM="${ARG_PARALLELISM:-}" ARG_MAX_MERMAID="${ARG_MAX_MERMAID:-}" # Word-split $ARGUMENTS (zsh needs SH_WORD_SPLIT for that) with globbing off # so prose like `*` never expands to filenames. [ -n "${ZSH_VERSION:-}" ] && setopt SH_WORD_SPLIT set -f # shellcheck disable=SC2206 _args=(${ARGUMENTS:-}) set +f i=0 while [ $i -lt ${#_args[@]} ]; do tok="${_args[$i]}" case "$tok" in --org=*) ARG_ORG="${tok#--org=}" ;; --org) i=$((i+1)); ARG_ORG="${_args[$i]:-}" ;; --agent=*) ARG_AGENT="${tok#--agent=}" ;; --agent) i=$((i+1)); ARG_AGENT="${_args[$i]:-}" ;; --version=*) ARG_VERSION="${tok#--version=}" ;; --version) i=$((i+1)); ARG_VERSION="${_args[$i]:-}" ;; --parallelism=*) ARG_PARALLELISM="${tok#--parallelism=}" ;; --parallelism) i=$((i+1)); ARG_PARALLELISM="${_args[$i]:-}" ;; --max-mermaid-nodes=*) ARG_MAX_MERMAID="${tok#--max-mermaid-nodes=}" ;; --max-mermaid-nodes) i=$((i+1)); ARG_MAX_MERMAID="${_args[$i]:-}" ;; --force) ARG_FORCE="1" ;; --reprobe) ARG_REPROBE="1" ;; esac i=$((i+1)) done # No org named anywhere: fall back to the sf CLI default target org # (`sf config get target-org --json` -> .result[0].value). Extracted with sed # so the block needs neither jq nor an inline interpreter; any failure leaves # ARG_ORG empty and the usage block below fires. if [ -z "$ARG_ORG" ] && command -v sf >/dev/null 2>&1; then _cfg="$(sf config get target-org --json 2>/dev/null || true)" _cfg="$(printf '%s\n' "$_cfg" | sed -n 's/.*"value"[[:space:]]*:[[:space:]]*"\([^"]*\)".*/\1/p' || true)" ARG_ORG="${_cfg%%$'\n'*}" fi # Usage block if required flags missing. Agent reads stderr, # prints verbatim, and stops — does NOT pre-run main.py. if [ -z "$ARG_ORG" ] || [ -z "$ARG_AGENT" ]; then cat >&2 <<'USAGE' > Which agent should I document, and in which org? > > I need: > - **Agent API name** — the BotDefinition.DeveloperName (e.g. `MyAgent`) > - **Org alias** — for `sf` CLI auth (the alias you configured with `sf org login`); > only needed when no default target org is set (`sf config set target-org <alias>`) > > Optional flags: > - `--version v5` — pin a specific BotVersion (default: Active+highest) > - `--force` — bypass cache > - `--reprobe` — force channel-probe refresh > - `--parallelism N` — ThreadPoolExecutor size (default 5) > - `--max-mermaid-nodes N` — cap Mermaid node count (default 80) USAGE exit 2 fi # Fresh work dir per invocation. Epoch + random suffix avoids collisions # between concurrent runs on the same host. WORK_DIR="/tmp/agentforce-architecture-analyze-$(date +%s)-$RANDOM" mkdir -p "$WORK_DIR" # Input validation at the boundary, BEFORE any python3 call. # fs_guard exits 1 and prints an INVALID_INPUT RESULT block on failure; # `|| exit 1` is mandatory — bare calls silently continue past failures. python3 "$SKILL_ROOT/scripts/_shared/fs_guard.py" "$ARG_AGENT" agent_api_name api_name || exit 1 python3 "$SKILL_ROOT/scripts/_shared/fs_guard.py" "$ARG_ORG" org_alias not_empty || exit 1 python3 "$SKILL_ROOT/scripts/_shared/fs_guard.py" "$WORK_DIR" WORK_DIR symlink || exit 1 python3 "$SKILL_ROOT/scripts/_shared/fs_guard.py" "$WORK_DIR" WORK_DIR owned || exit 1 if [ -n "$ARG_VERSION" ]; then python3 "$SKILL_ROOT/scripts/_shared/fs_guard.py" "$ARG_VERSION" agent_version api_name || exit 1 fi # Single python3 call drives all pipeline phases. main.py writes # `.emit_ctx.json` into $WORK_DIR — emit_result.py then renders the # RESULT block from that ctx. No subprocess-per-phase. _main_args=(--org-alias "$ARG_ORG" --agent "$ARG_AGENT" --work-dir "$WORK_DIR") [ -n "$ARG_VERSION" ] && _main_args+=(--version "$ARG_VERSION") [ -n "$ARG_FORCE" ] && _main_args+=(--force) [ -n "$ARG_REPROBE" ] && _main_args+=(--reprobe) [ -n "$ARG_PARALLELISM" ] && _main_args+=(--parallelism "$ARG_PARALLELISM") [ -n "$ARG_MAX_MERMAID" ] && _main_args+=(--max-mermaid-nodes "$ARG_MAX_MERMAID") # main.py returns nonzero on terminal failures; we DON'T short-circuit — # emit_result still publishes the failure RESULT block. `set -e` is # temporarily relaxed around this single call. set +e python3 "$SKILL_ROOT/scripts/main.py" "${_main_args[@]}" _rc=$? set -e # Final RESULT block is emit_result.py's stdout — MUST be the last thing # stdout sees. emit_result exits 0 on render success; the bash harness # propagates main.py's rc for the agent's exit status. WORK_DIR="$WORK_DIR" python3 "$SKILL_ROOT/scripts/emit_result.py" exit "$_rc" ``` ## Inputs | Input | Flag | Required | Default | |---|---|---|---| | `org_alias` | `--org` | no | sf CLI default target org (`sf config get target-org`) | | `agent_api_name` | `--agent` | yes | — | | `agent_version_api_name` | `--version` | no | active BotVersion | | `force_refresh` | `--force` | no | false (honor cache) | | `reprobe` | `--reprobe` | no | false (honor 7-day channel-probe cache) | | `parallelism` | `--parallelism` | no | 5 | | `max_mermaid_nodes` | `--max-mermaid-nodes` | no | 80 | | `data_dir` | `--data-dir` | no | `~/.vibe/data/agentforce-architecture-analyze` |