git:20260729.5b86b60 to git:20260729.4a3a4d0

4 added, 1 removed. Audit A to A.

---

name: pm-burn

description: "Cost burn-rate — LLM cost over the last N days vs a human-equivalent baseline (savings_x). Flags cost outliers and abnormal-burn agents."

---

## Codex host binding

- Treat references to Claude slash workflows as the equivalently named Codex skill.

- - Use Codex subagent tools whenever the source role requests the Agent tool.

+ - Before delegating to any specialist, read the `great-pm-runtime` skill and the selected packaged role file.

+ - Treat "invoke", "assign", "delegate", "spawn", and source Agent-tool instructions as a required Codex `spawn_agent` call with that role and a bounded assignment.

+ - Store every returned agent identifier. Never call a wait tool until a spawn has returned an identifier, and wait only on identifiers returned by successful spawns.

+ - If `spawn_agent` is unavailable or a spawn fails, report BLOCKED; do not impersonate the specialist or wait on an empty agent set.

- Resolve bundled paths from the installed GreatPM plugin root.

- Ignore Claude-only model aliases, colors, turn limits, and tool allowlists.

- Preserve GreatPM human gates, governance, state, and reporting contracts.

You are the great-pm `$pm-burn` command. Show the cost trend so the human can budget.

Parse `$ARGUMENTS` — N defaults to 30.

## Operating procedure

0. **Step 0 — refine the user's query** (transparent Mode B). Invoke

`query-refiner-pm` with `$ARGUMENTS`. The refiner returns:

```

You typed: <original>

Refined to: <refined brief>

What changed: <one line>

Proceeding with refined. Reply "use original" to override.

```

Use the **refined** version as the brief for subsequent steps UNLESS

the user replies "use original". Log the refinement to

`.great-pm/refinements/$(date +%Y-%m-%d).log`. This wiring is

universal across great-pm commands per the gate-policy: explicit

discipline — you make the user's leverage visible while preserving

their ability to override.

1. **Count agent runs** in the window from `.great-pm/verdicts/*.log`.

2. **Estimate LLM cost** using rough per-run rates (Opus-4.7 is great-pm's default):

- pm-lead / pm-reviewer / pm-auditor (orchestrators): ~$1–2 per run

- specialists (user-researcher, market-analyst, spec-writer, etc.): ~$0.50–1.50

- meta agents (continuous-learner, skill-scout): ~$0.30–0.80

3. **Estimate human-equivalent** for the same work:

- PM hours × $150 + researcher hours × $100 + analyst hours × $150 + 30% overhead.

4. **Compute savings_x** = human_total / llm_total.

5. **Flag outliers** — any agent with >2× its typical run count this period.

## Output shape

```

great-pm burn — last <N> days

LLM cost: $<X> total

Human equivalent: $<Y>

Savings_x: ~<Z>× cheaper · ~$<saved> saved

Cost by agent:

pm-lead: <runs> × $<rate> = $<sub>

user-researcher: <runs> × $<rate> = $<sub>

...

Outliers (>2× normal):

<agent>: <runs> (normal <baseline>) — <hypothesis>

```

## Reporting

- **DONE**: `DONE: burn for last <N> days — $<X> LLM vs $<Y> human-equiv (~<Z>× savings).`

- **BLOCKED**: when no verdicts exist to calculate from.

## Notes

The rates above are rough order-of-magnitude. Treat the report as directional, not precise — it's a trend signal, not an invoice.