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/stefanoskarakasis/Product-Marketing-SkillsWrote 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/stefanoskarakasis/product-marketing-skills/retro)<a href="https://agentmods.dev/commands/stefanoskarakasis/product-marketing-skills/retro"><img src="https://agentmods.dev/badge/commands/stefanoskarakasis/product-marketing-skills/retro/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/stefanoskarakasis/product-marketing-skills/retro"><img src="https://agentmods.dev/badge/commands/stefanoskarakasis/product-marketing-skills/retro.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 | $0.00013 | $0.00160 |
| Opus 5 | $0.00006 | $0.00080 |
| Sonnet 5 | $0.00003 | $0.00032 |
| Haiku 4.5 | $0.00001 | $0.00016 |
Grade A, and why
retro 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.
What it actually says
/pmm-execution:retro -- GTM Retrospective
Run a structured retrospective for a completed launch or sprint, anchored to the OKRs it was meant to move — not a general discussion.
Invocation
/pmm-execution:retro Q2 SSO launch
/pmm-execution:retro Sprint 14
Workflow
Uses the retro skill. Establishes the outcome anchor (what the cycle
was meant to achieve), collects and themes feedback, traces each theme
to a structural root cause, and produces a maximum of 3 OKR-linked
action items with a single named owner each.
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 · 24 lines · 13 tokens per session scan A 13b4a2c2fa7e
retro is a command published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (5 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 160 once invoked, about $0.0001 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
discover
Run a full discovery cycle — problem framing, JTBD demand-side analysis, assumption mapping, opportunity sizing, and OST mapping — from a rough idea to validated opportunity.
onboarding
Set up PM Copilot — a guided wizard that builds your persistent memory profile so every future session is grounded in your product context.
plan-sprint
Plan the upcoming sprint — epic breakdown, user story decomposition, RICE prioritization, dependency check, and capacity allocation.
roadmap
Build or review your roadmap — OKR alignment, Now/Next/Later structuring, dependency mapping, and stakeholder views, pulling live Linear/Jira state.
set-okrs
Structure OKRs — define objectives, write measurable key results, align to strategy, stress-test for quality, and cascade across teams.
stakeholder-update
Generate tailored stakeholder updates by audience — pulls live tracker state from Linear/Jira, formats by audience (exec / engineering / customer) using Pyramid Principle.