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 solanabr/solana-ai-kit --skill pitch-deckgit clone --depth 1 https://github.com/solanabr/solana-ai-kitWrote 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/solanabr/solana-ai-kit/pitch-deck)<a href="https://agentmods.dev/skills/solanabr/solana-ai-kit/pitch-deck"><img src="https://agentmods.dev/badge/skills/solanabr/solana-ai-kit/pitch-deck/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/solanabr/solana-ai-kit/pitch-deck"><img src="https://agentmods.dev/badge/skills/solanabr/solana-ai-kit/pitch-deck.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 7 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00055 | $0.01042 |
| Opus 5 | $0.00028 | $0.00521 |
| Sonnet 5 | $0.00011 | $0.00208 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
pitch-deck 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 10d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pitch Deck
Interview → detect audience → pick narrative → build slides with speaking notes → self-score → objection prep.
Context handoff
At start, read .claude/context/idea.md and .claude/context/build.md if present — pre-fill problem, wedge, traction, and stack from them; only ask what's missing.
Workflow
1. 12-question interview
Blunt, one at a time, skipping anything already answered by context files:
- What does it do, in one sentence a non-crypto person understands?
- Who exactly has the problem, and how painful is it (evidence)?
- Why does this need a blockchain?
- Why Solana specifically?
- What works today (demo-able) vs. roadmap?
- Traction numbers — users, volume, TVL, signups, waitlist?
- Who is the team and what's the unfair edge?
- Competitors and your moat?
- Business model — who pays, when?
- Who is the audience for this deck (judges, VCs, grant committee, accelerator)?
- The ask — prize, check size, grant amount, admission?
- Biggest weakness you're afraid they'll ask about?
2. Audience detection → slide set
Q10 decides the slide set — full breakdown in investor-audience-guide.md:
| Audience | Emphasis | Length |
|---|---|---|
| Hackathon judges | working demo, technical novelty, why-Solana | 5–7 slides |
| VC | market size, traction slope, team, moat, ask | 10–12 |
| Grant committee | ecosystem benefit, public-good angle, milestones, budget | 8–10 |
| Accelerator | team velocity, learning rate, wedge → expansion path | 8–10 |
Slide-by-slide order per audience: pitch-structure.md.
3. Narrative framework
Pick ONE backbone and state why — PAS (obvious pain, hackathons), 6-Part Investor Arc (VC), BAB (before/after/bridge), Hero's Journey (founder-story-driven), Pixar (narrative momentum). Definitions, slide mappings, and crypto examples: storytelling-frameworks.md.
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.
- 10d ago First seen · 78 lines · 55 tokens per session scan A 63999a0fe17a
pitch-deck is a skill published in the GitHub repository solanabr/solana-ai-kit (101 stars, last pushed 20d ago), licensed MIT. It adds 55 tokens to every session and 1,042 once invoked, about $0.0003 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 2026-08-30.
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