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 ljucask/pureinn-product-development --skill pm-pitch-deckgit clone --depth 1 https://github.com/ljucask/pureinn-product-developmentWrote 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/ljucask/pureinn-product-development/pm-pitch-deck)<a href="https://agentmods.dev/skills/ljucask/pureinn-product-development/pm-pitch-deck"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-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/ljucask/pureinn-product-development/pm-pitch-deck"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-pitch-deck.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 | $0.00052 | $0.05251 |
| Opus 5 | $0.00026 | $0.02625 |
| Sonnet 5 | $0.00010 | $0.01050 |
| Haiku 4.5 | $0.00005 | $0.00525 |
Grade A, and why
pm-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 11d 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 — 540 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM - Pitch Deck
Agent mode (--agent)
Supports --agent: runs autonomously in a subagent, drafts the artifact from existing inputs, and returns a short summary + coverage note.
- No flag → interactive (default); if inputs are heavy, offer agent mode.
--agent→ obey. First check inputs are complete. Anything missing: do NOT invent it - mark[ASSUMED - what/why]in the output and summary. Never hallucinate to fill a gap.
What this skill does
Produces a slide-by-slide content brief for a pitch deck. Does not generate slides directly - it generates structured content that Gamma uses to build the visual presentation.
Two-step process:
- Intake questionnaire - determines type, audience, style, maintenance model
- Content generation - maps existing Pureinn artifacts to slides, applies quality rules per slide
Quality rules are derived from analysis of 82 reviewed pre-seed/seed pitch decks and 590 investor Reddit comments. These are constraints, not suggestions - every slide is generated to pass them.
Gamma integration: Once content brief is complete, the skill passes it to Gamma MCP to produce the visual deck. Requires Gamma MCP connected (claude.ai Gamma via /mcp). If Gamma is not connected, the skill stops after Step 5 and outputs the content brief as a standalone artifact.
Dependencies
Recommended before running:
pm-lean-canvas- business model, UVP, channels, revenuepm-problem-validation- problem evidence and interview quotespm-personas- specific customer profile for the problem storypm-market-analysis- market size data (bottom-up preferred)pm-business-case- financial projections and askpm-hypotheses- traction evidence, validation resultspm-kotler- differentiation and positioning
Produces artifacts used by:
- External investors / partners / customers (primary audience)
pm-product-roadmap- milestone and ask should match roadmap
Step 0: Current state check
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.
- 11d ago First seen · 540 lines · 52 tokens per session scan A a9bb5f0ff099
pm-pitch-deck is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 5,251 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 2026-08-31.
Other skills, from other repositories
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frontend-development
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relay
A Chinese-language procedure for handing an unfinished task from one AI session to another without losing its context.
validation-loop
A development routine that checks each important file immediately after it is changed by running the project’s build, lint, type-check, or test commands.