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.
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pmWrote 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.
[](https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-cost)<a href="https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-cost"><img src="https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-cost/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.
<a href="https://agentmods.dev/commands/vandanaajaydubey111/great-pm/pm-cost"><img src="https://agentmods.dev/badge/commands/vandanaajaydubey111/great-pm/pm-cost.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00043 | $0.00797 |
| Opus 5 | $0.00022 | $0.00398 |
| Sonnet 5 | $0.00009 | $0.00159 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
pm-cost scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the great-pm /pm-cost command. Project the cost of a proposed initiative before commitment.
Operating procedure
-
Step 0 — refine the user's query (transparent Mode B). Invoke
query-refiner-pmwith$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. -
Parse the initiative description from
$ARGUMENTS. -
Sketch the loop stages this initiative will touch — some skip stages (a quick bug-fix skips Discover & Strategize).
-
Estimate agent runs per stage:
- Discover (if applicable): user-researcher 1, feedback-synthesizer 1, market-analyst 1
- Strategize (if applicable): product-strategist 1, pricing-strategist 0–1
- Prioritize: prioritization-analyst 1, roadmap-planner 1
- Define: spec-writer 1, spec-reviewer 1, metrics-architect 1
- Launch: launch-manager 1, gtm-strategist 1
- Measure: experiment-designer 0–1, analytics-analyst 1
- Cross-cutting: pm-lead orchestrates throughout; pm-reviewer reviews each gate
-
Pull lessons — read
.great-pm/lessons.mdfor cost outliers tagged similar; apply if relevant. -
Sum LLM cost at Opus-4.7 rates (~$0.50–2 per agent run; orchestrators on the high end).
-
Human-equivalent — same work, human team rates ($150/hr PM, $100/hr researcher, $150/hr analyst, +30% coordination).
-
Output: range (optimistic – pessimistic), savings_x, top 2 risks.
Output shape
Cost estimate — <initiative>
Loop stages: <list, e.g. Discover → Strategize → Prioritize → Define>
Expected agent runs: <total>
LLM cost: $<X.XX> (optimistic) — $<Y.YY> (pessimistic)
Human equivalent: $<H_low> — $<H_high>
Savings_x: ~<Z>×
Top risks (cost outliers from past):
- <risk>: <why> → <mitigation>
Assumptions:
- <key assumption>
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.
- 12d ago First seen · 71 lines · 43 tokens per session scan A 2db1cebc9122
pm-cost is a command published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 797 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.
Other commands, from other repositories
poc
Start a hypothesis-driven POC with hard timebox. Skips 80% of the production pipeline; forces ship/pivot/kill decision at expiry.
rfc
RFC process for cross-team decisions. Create, track, and close RFCs. Accepted RFCs auto-create ADRs.
discover
Run a full product discovery cycle — from outcome definition through opportunity mapping, prioritisation, and experiment design. Use when the team isn't sure what to build next, or before writing a PRD for a complex feature space.
migrate
Migrate existing PROJECT.md to the latest greatcto schema — appends missing fields without touching existing values.
ownership
Service ownership matrix. Who owns what: team, tech lead, on-call, SLA. Auto-detects from git history. Generates CODEOWNERS.
prd
Create a Product Requirements Document — conversational intake, 8-section output. Run BEFORE architect to lock WHAT and WHY before the team decides HOW.