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/meta-verify)<a href="https://agentmods.dev/commands/stefanoskarakasis/product-marketing-skills/meta-verify"><img src="https://agentmods.dev/badge/commands/stefanoskarakasis/product-marketing-skills/meta-verify/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/meta-verify"><img src="https://agentmods.dev/badge/commands/stefanoskarakasis/product-marketing-skills/meta-verify.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 | $0.00011 | $0.00160 |
| Opus 5.5 | $0.00004 | $0.00064 |
| Sonnet 5.5 | $0.00002 | $0.00032 |
| Haiku 4.5 | $0.00001 | $0.00016 |
Grade A, and why
meta-verify 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 1mo 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-meta:meta-verify -- Output Verification
Run a second-pass quality check on a skill's output before it goes out the door — catching issues the first pass missed.
Invocation
/pmm-meta:meta-verify Check this positioning brief before I send it
/pmm-meta:meta-verify Verify the last GTM strategy output
Workflow
Uses the meta-verify skill. Re-checks the output against the
originating skill's own quality bar, flags anything that doesn't meet
it, and returns specific fixes rather than a pass/fail verdict alone.
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.
- 1mo ago First seen · 23 lines · 11 tokens per session scan A 3cc0ec2d8822
meta-verify is a command published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (8 stars, last pushed yesterday), licensed MIT. It adds 11 tokens to every session and 160 once invoked, about $0.0000 per session on Opus 5.5. 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
getpix
Find a free licensed image on the internet and add it to the project, optimized.
photo-pass
Art-direction photo pass over the site: add photography only where it earns its place.
strategy
Create a comprehensive product strategy using the 9-section Strategy Canvas — from vision to defensibility.
plan-okrs
Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results.
privacy-policy
Draft a privacy policy covering data collection, usage, storage, and compliance requirements.
conjure
Use when you want to build a new Claude Code skill, agent, hook, or MCP server but aren't sure which — or when you want to describe what you want in plain language. Auto-detects the right artifact type, asks targeted questions, explains the reasoning, then builds it.