deck-critique

deck-critique is a skill for Claude Code from ai-analyst-lab/ai-analyst-plugin. It costs 115 tokens per session (3,505 once invoked), scanned A, original, MIT.

A structured review of a presentation, checking each slide for its main point, importance, supporting evidence, and requested action. It produces slide-level scorecards, warnings about common problems, an overall A–F grade, and ranked fixes.

In plain words
What is it for?
Use it to assess a Marp presentation file or Google Slides deck, especially before a presentation-rescue process, with an optional audience and meeting context.
Why use it?
It shows why a deck is unclear or unconvincing instead of giving only general feedback. The review helps you focus revisions on the changes most likely to improve the presentation.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the ai-analyst-plus plugin — 44 skills, 1 command, 13 agents shipped together

Good fit Use it to assess a Marp presentation file or Google Slides deck, especially before a presentation-rescue process, with an optional audience and meeting context.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai-analyst-lab/ai-analyst-plugin/deck-critique
Install

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.

Any agent
npx skills add ai-analyst-lab/ai-analyst-plugin --skill deck-critique
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plugin

Made for: Claude Code.

Or install ai-analyst-plus, the plugin that ships this one along with the rest of its 44 skills, 1 command, 13 agents.

Wrote 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.

agentmods badge for deck-critique

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/deck-critique.svg)](https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/deck-critique)
Your own site
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/deck-critique"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/deck-critique.svg" alt="Measured on agentmods" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,505 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00115 $0.03505
Opus 5 $0.00057 $0.01752
Sonnet 5 $0.00023 $0.00701
Haiku 4.5 $0.00012 $0.00350

Measured 8d ago against content hash b3652d457508, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

deck-critique 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 8d 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.

ai-analyst-plus/skills/deck-critique/SKILL.md · 292 lines

How it starts

The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Deck Critique

Purpose

Score any presentation slide-by-slide against the Data Story Checklist (SO-WHAT, STAKES, EVIDENCE, ASK). Returns a diagnosis report with per-slide scorecards, anti-pattern flags, an overall grade, and a prioritized prescription for fixes.

When to Use

Apply this skill when:

  1. The user asks to review, critique, or diagnose a deck — "review my deck", "what's wrong with these slides", "critique this presentation"
  2. Before running /deck-rescue — the critique is a prerequisite input for the full rescue pipeline
  3. The user provides a Marp .marp.md file or a Google Slides URL/ID for evaluation

This skill can be invoked directly as /deck-critique or auto-fires when the presentation-doctor orchestrator agent runs.

Inputs

  • {{DECK_SOURCE}}: Path to a Marp .marp.md file OR a Google Slides presentation ID/URL
  • {{AUDIENCE}} (optional): Who the presentation is for — informs STAKES scoring
  • {{CONTEXT}} (optional): What decision or meeting this deck supports

Instructions

The Data Story Checklist Scoring System

Every slide is scored on 4 dimensions, each 0-3 points (max 12 per slide):

SO-WHAT (0-3): Does the title state a finding?
Score Criteria Example
3 Action headline — states a specific finding with data "Incomplete onboarding drives 67% of enterprise churn"
2 Descriptive headline — describes what's shown but not what it means "Churn by onboarding status"
1 Label — generic category name "Churn Analysis"
0 Missing or generic — no title, or "Q3 Results" "Q3 Update"
STAKES (0-3): Does the audience know why this matters?
Score Criteria Example
3 Explicit impact — quantified business consequence "$2.3M ARR at risk, growing 15% QoQ"
2 Implied impact — consequence is suggested but not quantified "This is our fastest-growing churn segment"
1 Generic — vague importance claim "This is important for the business"
0 None — no reason given for audience to care (just data, no framing)

Read the full file on GitHub · 292 lines

Changes

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.

  1. 8d ago First seen · 292 lines · 115 tokens per session scan A b3652d457508

Subscribe to this mod's changes

deck-critique is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (32 stars, last pushed 12d ago), licensed MIT. It adds 115 tokens to every session and 3,505 once invoked, about $0.0006 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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