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 OneWave-AI/claude-skills --skill pitch-deck-reviewergit clone --depth 1 https://github.com/OneWave-AI/claude-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/onewave-ai/claude-skills/pitch-deck-reviewer)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/pitch-deck-reviewer"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/pitch-deck-reviewer/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/onewave-ai/claude-skills/pitch-deck-reviewer"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/pitch-deck-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00083 | $0.00835 |
| Opus 5 | $0.00042 | $0.00417 |
| Sonnet 5 | $0.00017 | $0.00167 |
| Haiku 4.5 | $0.00008 | $0.00084 |
Grade A, and why
pitch-deck-reviewer 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 9d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pitch Deck Reviewer
Review a pitch deck with VC-grade rigor and produce a scored, actionable pitch-review.md.
Contents
references/evaluation-framework.md-- The 8 scored dimensions, weights, red flags, scoring guides, design notes, and overall-score calculation.references/objections-and-benchmarks.md-- Investor objection categories and the canonical successful-deck benchmarks.references/output-template.md-- The exactpitch-review.mdstructure to generate.
Workflow
- Ingest the deck. Determine file type and location, then read every slide. Supported inputs: PDF (Read directly; for 10+ pages read in batches via the
pagesparameter), PowerPoint .pptx (invoke the pptx skill or Read), Google Slides links (WebFetch if public), images PNG/JPG (Read to inspect visually), markdown/text descriptions, and directories of slide images (Glob to enumerate, then Read each). For .pen files, state that they cannot be read directly. - Build a slide inventory. Catalog each slide by number and primary content before any analysis. Identify company name, stage, and industry. Flag any deck over 20 slides as a concern itself; most successful decks run 10-15.
- Score the 8 dimensions. Apply
references/evaluation-framework.md. Score each 1-10 with specific evidence from the deck, then compute the weighted overall score and assign the grade label. - Write slide-by-slide feedback. Cover every slide with content summary, purpose, effectiveness, strengths, weaknesses, and recommendations.
- Predict investor objections. Generate at least 5 using the categories in
references/objections-and-benchmarks.md, each with severity, trigger, suggested verbal response, and deck fix. - Compare to benchmark decks. Reference at least 2 relevant decks from
references/objections-and-benchmarks.md; name where this deck is stronger, weaker, and what to borrow. - Rank the top 5 improvements by impact and list any missing slides or sections for this stage and industry.
- Assemble
pitch-review.mdperreferences/output-template.md. Write the executive summary last. Save it beside the source deck (or the working directory). Show the overall-score math.
What ships with it
3 files 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.
- 9d ago First seen · 45 lines · 83 tokens per session scan A d1c4eda486e8
pitch-deck-reviewer is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 83 tokens to every session and 835 once invoked, about $0.0004 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 2026-09-03.
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