A command that compares language-model spending over a chosen number of days with an estimate of what equivalent human work would cost.

Use it to review recent agent-run costs, estimate the human-equivalent baseline, and identify abnormal burn rates for budgeting.

It shows spending trends and highlights agents or runs whose costs are unusually high.

pm-burn — Command for Claude Code by VandanaAjayDubey111

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pm

Made for: Claude Code.

Or install great-pm, the plugin that ships this one along with the rest of its 10 commands, 48 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-burn/github.svg)](https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-burn)

Your own site

<a href="https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-burn"><img src="https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-burn/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-burn"><img src="https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-burn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 683 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00033	$0.00683
Opus 5	$0.00016	$0.00342
Sonnet 5	$0.00007	$0.00137
Haiku 4.5	$0.00003	$0.00068

Measured 11d ago against content hash 774125b61009, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

pm-burn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

commands/pm-burn.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

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.
Count agent runs in the window from .great-pm/verdicts/*.log.
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
Estimate human-equivalent for the same work:
- PM hours × $150 + researcher hours × $100 + analyst hours × $150 + 30% overhead.
Compute savings_x = human_total / llm_total.
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.

Read the full file on GitHub · 67 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

11d ago First seen · 67 lines · 33 tokens per session scan A 774125b61009

Subscribe to this mod's changes

pm-burn is a command published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 683 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Analytics and metrics Claude Code Finance and fintech LLM Multi-Agent agentic ai-agents claude-code-plugin

pm-burn

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

Operating procedure

Output shape

Reporting

Notes

What this file has done since we first saw it

Other commands, from other repositories

cost

close-review

procurement-review

tax-review

CLAUDE

research