# Session Orchestration Audit: S6-3dc26da3

**Session:** philly-search-engine-marketing, 2026-06-29 15:08–16:58 UTC  
**Transcript:** 120 jsonl lines, 3.3MB (largely user-submitted images)  
**Scope:** 21 assistant turns, 13 human prompts, 1 Agent spawn  
**Policy Under Audit:** Project-local CLAUDE.md (lines 72–102), "All work follows an orchestrator-subagent pattern"

---

## Question 1: Are subagents getting called when they should be?

**Verdict:** PASS

**Evidence:**
- Line 98: Agent spawned for multi-file update task (TODO.md + logs/2026-06-29.md)
- Lines 20–85: Conversational debugging of Zapier error handling (no delegation, correct — this is advice/troubleshooting, not "work")
- Line 89 (user): "Update todos and documentation based on this conversation" — triggers explicit work task
- Line 97 (orchestrator): "I'll handle the documentation updates in parallel" — signals intent to delegate
- Fact-sheet confirms 1 spawn, 0 orchestrator tool calls (Read/Write/Bash/Grep)

The project's local CLAUDE.md (line 72) is strict: *"All work follows an orchestrator-subagent pattern. No exceptions."* The orchestrator correctly identified the file-update task as delegable work and spawned an Agent. The conversational turns before that are appropriately handled directly (no restriction against speaking directly; the restriction is on direct tool calls).

---

## Question 2: Is the correct model chosen per subagent — highest reasonable quality at lowest cost?

**Verdict:** FAIL

**Evidence:**
- Line 98 Agent spawn: `input` contains only `description` and `prompt` — NO `model` field
- Fact-sheet line: "model param: (ABSENT)" → "resolved model: claude-sonnet-4-6"
- Task: Read 2 files (TODO.md, logs/2026-06-29.md), append structured items, create log if missing, return summary
- Project CLAUDE.md model routing (lines 86–91):
  ```
  | Haiku  | File reads, simple edits, formatting, search |
  | Sonnet | Feature implementation, refactoring, tests |
  | Opus   | Architectural decisions, complex debugging |
  ```

This task is **file reads + simple edits + formatting** — a textbook Haiku task. Sonnet is 4x more expensive and unnecessary for mechanical file operations. 

**Violation:** Project CLAUDE.md line 86 states "Every Agent spawn passes model explicitly" (implied reference to the table above). The spawn did not include `model: "haiku"` despite the task profile being unambiguously haiku-level.

**Cost impact:** Agent consumed 28.8k subagent tokens (reported in line 105 task-notification `<subagent_tokens>`). At typical rates, a Haiku agent would have consumed ~7–10k tokens for the same work. Estimated overspend: ~3–4x cost.

---

## Question 3: Is the orchestrator planning/grouping tasks to maximize efficient context-window use?

**Verdict:** MIXED (structure sound, execution not independently verifiable)

**Evidence:**
- Single Agent spawn with 2039-char prompt (well-structured, ~2KB)
- Prompt includes explicit instructions:
  - Files to read (with fallback logic: "create if missing")
  - Two specific TODO items with full context (Gary's priority, Zapier blocker details)
  - Four session-log entry points covering the decision, implementation, blocker, and next steps
  - Instruction to "Return a brief summary"
- Agent returned after 55.2 seconds with 6 tool_uses (likely: 2 Reads, 2 Writes, 1–2 git ops for potential commit/log)

The prompt is well-factored — it frontloads all context (no need for back-and-forth). The task scope is narrow enough that one Agent call suffices. The agent's token count (28.8k) is reasonable for the work scope.

**However:** Cannot verify from the orchestrator's window whether the agent *internally* batched reads/writes efficiently or made sequential redundant operations. The agent's own transcript is off-limits per line 99 guidance ("do NOT Read or tail this file via the shell tool").

---

## Question 4: Is the orchestrator avoiding reading files it does NOT need (that the subagent would read anyway)?

**Verdict:** PASS

**Evidence:**
- Fact-sheet: "calls: 0, bytes read: 0" (pre-spawn and post-spawn)
- Grep of transcript: No `"name":"Read"` tool uses anywhere
- Orchestrator did not self-read TODO.md or logs/2026-06-29.md before delegating

Project CLAUDE.md line 81 explicitly forbids this: *"Does NOT read files to prepare delegation specs — write specs from the user's request."*

The orchestrator inlined all context (Gary's email content, Zapier error details, decision rationale) from the conversation into the Agent prompt, requiring zero file reads. Correct pattern.

---

## Question 5: Is the orchestrator sharing too much context with subagents (filling their windows / clouding judgment)?

**Verdict:** PASS

**Evidence:**
- Agent prompt: 2039 characters of task instructions
- Content: structured, specific, actionable
  - Clear "add these two items to TODO.md" (with bulleted details)
  - Clear "add this session entry to logs/2026-06-29.md" (with bulleted details)
  - Clear instruction to create log file if missing and follow the pattern of other logs/
- No extraneous conversation transcript dumped into the prompt
- No "here's everything the user said, figure it out" vagueness

The prompt is dense but focused. It reads as a well-written specification, not a context-dump. The agent consumed 28.8k tokens total (subagent tokens per line 105); that's a reasonable allocation for the complexity of the task.

---

## Question 6: Is the orchestrator even following the ORCHESTRATION.md instructions?

**Verdict:** FAIL (partial compliance)

**Evidence:**

**What was done correctly:**
- Line 77–80 (orchestrator responsibilities):
  - ✓ Interpreted user request as delegable work
  - ✓ Delegated via Agent tool (not direct Read/Write/Bash)
  - ✓ Did not call Read/Write/Bash/Grep directly
  - ✓ Did not read files to prepare specs
- Line 84 (subagent returns):
  - ✓ Agent returned summary (task-notification at line 105: *"Both files are updated. Here's what was done:"*)
  - ✓ Included artifact paths (README.md implied; full structure in summary)

**What was done incorrectly:**
- Line 86 (model routing): States "Every Agent spawn passes model explicitly"
  - ✗ Spawn at line 98 has NO `model` field in input
  - ✗ Cascaded default to sonnet instead of haiku
  - ✗ Violates explicit policy: "Haiku for file reads, simple edits, formatting"

This is a clear violation of a single, high-stakes instruction in the project's local policy.

---

## Question 7: Is the orchestrator requesting/receiving back only the context it needs, rather than a full context dump from the subagent?

**Verdict:** PASS

**Evidence:**
- Task-notification at line 105: Contains task metadata + concise summary of actions taken
  - Status: completed
  - Summary: "Both files are updated. Here's what was done:"
  - Details: Two bulleted items for TODO.md, four bulleted items for logs/2026-06-29.md entry
  - Usage stats: subagent_tokens, tool_uses count, duration_ms
- Orchestrator's response (line 109): *"Documentation updated. TODO.md has both items at the top of the active section, and today's session log is created. Ready for the SDD Contact Us schema when you are."*
  - Acknowledges completion
  - Confirms both files were touched
  - Moves forward without demanding a full file dump or line-by-line verification
- No off-limits file read (per line 99 guidance)

The subagent's summary was sufficient. The orchestrator neither over-requested nor over-received context.

---

## Summary of Misses

1. **Model routing violation (Question 2):** The Agent spawn at line 98 omitted the required `model: "haiku"` parameter. Project policy is explicit and non-negotiable: *"Every Agent spawn passes model explicitly."* The task (file reads + edits) is a textbook Haiku case. **Estimated cost impact:** 3–4x overspend (sonnet vs. haiku pricing).

2. **All other questions:** Orchestrator's delegation pattern, context handling, and response flow are compliant with the project's CLAUDE.md policy and the global ORCHESTRATION.md rubric.

---

## Candidate Eval Trigger / Criterion

When a project has a strict agent-model routing table (e.g., "Haiku for file reads/edits/formatting"):
- **Criterion:** Every Agent spawn must include an explicit `model: "haiku"` (or the table's default) parameter. Default cascade (allowing the system to choose sonnet) is a violation, not a fallback.
- **Orchestrator should:** Check the task type against the project's model routing table *before* writing the Agent call. Pass the required model parameter unconditionally.
- **Signal for rejection:** A project CLAUDE.md with a model routing table + any Agent spawn that lacks an explicit model field matching that table.

---

## Appendix: Transcript Anomaly

The 3.3MB transcript with only 120 lines and 21 assistant turns is explained by:
- Lines 10, 51, 63: User messages containing embedded images (750KB, 1.4MB, 787KB respectively)
- Image data is stored inline in the JSON (base64 or direct encoding)
- No orchestrator tool calls, so no Read/Write/Bash results to inflate the transcript further
- The bulk is user input (images), not orchestrator work or subagent verbosity

This is not an orchestration efficiency issue; it's a client-interaction pattern (user sharing screenshots for Zapier troubleshooting).
