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.
npx skills add stefanoskarakasis/Product-Marketing-Skills --skill proof-pointsgit 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/skills/stefanoskarakasis/product-marketing-skills/proof-points)<a href="https://agentmods.dev/skills/stefanoskarakasis/product-marketing-skills/proof-points"><img src="https://agentmods.dev/badge/skills/stefanoskarakasis/product-marketing-skills/proof-points/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/skills/stefanoskarakasis/product-marketing-skills/proof-points"><img src="https://agentmods.dev/badge/skills/stefanoskarakasis/product-marketing-skills/proof-points.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 | $0.00084 | $0.05023 |
| Opus 5.5 | $0.00034 | $0.02009 |
| Sonnet 5.5 | $0.00017 | $0.01005 |
| Haiku 4.5 | $0.00008 | $0.00502 |
Grade A, and why
proof-points 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 4d 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 — 442 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proof Points
How This Works
Every stat, quote, and case study in your messaging is a promise — and every
promise sales, legal, or a skeptical prospect can eventually ask you to back
up. Almost no company has a clean registry of these; what they actually have
is a mash of sales decks, battlecards, one-pagers, and case study PDFs, each
one repeating (and slowly staling) numbers nobody's re-checked since the deck
was built. This skill is both the intake and the gate: it mines claim
candidates out of that mess, then makes sure nothing gets called "approved"
without a source, no customer name ships without documented permission to use
it, and every forbidden claim carries a stated reason — not a bare
prohibition nobody can act on. It deepens your brain's existing Section 6 in
place, the same Proof Points Registry message-house and
positioning-messaging already read.
Step 0 — Load brain Section 6 (current registry, however thin).
Step 1 — Classify the request: Extract from source material, Add one claim directly, Verify a claim before it ships, or Audit the existing registry.
Step 2 (Extract) — Mine claim-shaped statements out of pasted decks, battlecards, case studies, or other GTM collateral; every candidate starts flagged, regardless of whether the source material cites its own source.
Step 3 (Add) — Require a source for a directly-supplied claim; unsourced claims get flagged, never silently approved.
Step 4 (Verify) — Check a claim someone wants to use against the registry: approved, forbidden, or not yet registered.
Step 5 (Audit) — Walk every existing entry for missing sources, stale dates, undocumented customer names, and unsupported superlatives.
Step 6 — Deepen brain Section 6 with the result (on user confirmation).
Step 7 — Learning Close: log the session to /context/skill-sessions.md.
Trigger
- When: Building a proof points registry from scratch out of existing sales decks, battlecards, case studies, or pricing pages; adding a single new metric, quote, or case study directly; checking whether a specific stat or phrase is safe to use before it ships in copy; or auditing brain Section 6 for unsourced claims, stale proof, undocumented customer names, or unsupported superlatives.
- Not for: Structuring raw, unstructured customer conversation — a call
recording or interview transcript nobody's synthesized yet — into
discovery insights →
interview-summary, run first. That's a qualitatively different task (JTBD synthesis of what customers said) from this skill's Extract mode, which mines already-written claims out of already-somewhat-structured GTM collateral (a deck, a battlecard, a case study doc) — if Extract mode turns up a customer quote that traces back to a raw call nobody's written up, route that call throughinterview-summaryfirst, then bring the resulting quote back here. Vocabulary, tone, and forbidden language (not claims) →brand-voice. Building the positioning statement or messaging hierarchy itself →positioning-messaging, run this first so it has a gated registry to cite from. - Example prompts:
- "Pull proof points out of this battlecard"
- "We don't have a registry — start one from these 3 sales decks"
- "Add a proof point: 40% faster onboarding, from our Q3 customer survey"
- "Can I say 'industry-leading' in this deck?"
- "Audit our proof points — anything stale or unsourced?"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago Changed d2fc02e16358
- 5d ago Changed · +13 lines 5b060166f7ba
- 9d ago Changed · +2 lines 2abce58eaf07
- 11d ago Changed · +13 lines 57648a03397e
- 13d ago Changed · +4 lines 1835f86789d1
- 20d ago First seen · 410 lines · 84 tokens per session scan A 64c14271fd4c
proof-points is a skill published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (7 stars, last pushed yesterday), licensed MIT. It adds 84 tokens to every session and 5,023 once invoked, about $0.0003 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 2026-09-26.
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