Founder-skills deck-review

Scores and strengthens startup pitch decks against 35 investor-grade criteria before founders send them to VCs. Use when user asks to 'review my deck', 'pitch deck feedback', 'check my slides', 'is my deck ready', 'review this pitch deck', 'deck critique', 'improve my pitch deck', 'what's wrong with my deck', 'pitch deck review', 'fundraising deck feedback', or provides a pitch deck (PDF, PPTX, markdown, or text) for evaluation. Covers pre-seed, seed, and Series A against 2026 best practices from Sequoia, DocSend, YC, a16z, and Carta data. Do NOT use for financial model review, market sizing, or general document editing.

install

source · Clone the upstream repo

git clone https://github.com/lool-ventures/founder-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/lool-ventures/founder-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/founder-skills/skills/deck-review" ~/.claude/skills/lool-ventures-founder-skills-deck-review && rm -rf "$T"

manifest: founder-skills/skills/deck-review/SKILL.md

source content

Deck Review Skill

Help startup founders strengthen their pitch decks before sending them to investors. Produce a structured, scored review with specific, actionable recommendations grounded in 2026 best practices from Sequoia, DocSend, YC, a16z, and Carta data. The tone is founder-first: a candid coaching session, not a VC evaluation.

Input Formats

Accept any format: PDF, PowerPoint (PPTX), markdown, or text descriptions of slides.

Available Scripts

All scripts are at

${CLAUDE_PLUGIN_ROOT}/skills/deck-review/scripts/

checklist.py
— Scores 35 criteria across 7 categories (pass/fail/warn/not_applicable)
compose_report.py
— Assembles artifacts into final report with cross-artifact validation;
```
--strict
```
exits 1 on high/medium warnings
visualize.py
— Generates self-contained HTML with SVG charts (not JSON)

Run with:

python3 ${CLAUDE_PLUGIN_ROOT}/skills/deck-review/scripts/<script>.py --pretty [args]

Available References

Read as needed from

${CLAUDE_PLUGIN_ROOT}/skills/deck-review/references/

deck-best-practices.md
— Full 2026 best practices: slide frameworks, stage-specific guidelines, design rules, AI-company requirements
checklist-criteria.md
— Definitions for all 35 criteria with pass/fail/warn thresholds
artifact-schemas.md
— JSON schemas for all artifacts

Artifact Pipeline

Every review deposits structured JSON artifacts into a working directory. The final step assembles all artifacts into a report and validates consistency. This is not optional.


deck_inventory.json
stage_profile.json
slide_reviews.json
checklist.py
compose_report.py

Rules:

Deposit each artifact before proceeding to the next step
For agent-written artifacts (Steps 1-3), consult
```
references/artifact-schemas.md
```
for the JSON schema
If a step is not applicable, deposit a stub:
```
{"skipped": true, "reason": "..."}
```

Keep the founder informed with brief, plain-language updates at each step. Never mention file names, scripts, or JSON. After each analytical step (3–4), share a one-sentence finding before moving on.

Workflow

Path Setup

SCRIPTS="$CLAUDE_PLUGIN_ROOT/skills/deck-review/scripts"
REFS="$CLAUDE_PLUGIN_ROOT/skills/deck-review/references"
if ls "$(pwd)"/mnt/*/ >/dev/null 2>&1; then
  ARTIFACTS_ROOT="$(ls -d "$(pwd)"/mnt/*/ | head -1)artifacts"
elif ls "$(pwd)"/sessions/*/mnt/*/ >/dev/null 2>&1; then
  ARTIFACTS_ROOT="$(ls -d "$(pwd)"/sessions/*/mnt/*/ | head -1)artifacts"
else
  ARTIFACTS_ROOT="$(pwd)/artifacts"
fi

CLAUDE_PLUGIN_ROOT

is empty, fall back:

Glob

for

**/founder-skills/skills/deck-review/scripts/checklist.py

, strip to get

SCRIPTS

, derive

REFS

ARTIFACTS_ROOT

resolves to
$(pwd)/artifacts
but no
artifacts/
directory exists at
$(pwd)
: The workspace may not be mounted yet. Use

Glob

with pattern

**/artifacts/founder_context.json

to locate existing artifacts, and derive

ARTIFACTS_ROOT

from the result. If nothing is found,

mkdir -p "$ARTIFACTS_ROOT"

and proceed.

REVIEW_DIR="$ARTIFACTS_ROOT/deck-review-{company-slug}"
mkdir -p "$REVIEW_DIR"

Step 1: Ingest Deck ->

deck_inventory.json

Read the provided deck. For each slide, extract: headline, content summary, visuals description, word count estimate. Record metadata: company name, total slides, format, any claimed stage or raise amount.

Step 2: Detect Stage ->

stage_profile.json

Determine pre-seed/seed/series-a from signals in the deck. Read

references/deck-best-practices.md

for stage-specific frameworks. Record: detected stage, confidence, evidence, whether AI company, expected slide framework, stage benchmarks.

Stage signals: Pre-seed: no revenue, LOIs/waitlist, prototype, <$2.5M ask. Seed: early ARR, paying customers, <$6M ask. Series A: $1M+ ARR, cohort data, repeatable GTM, $10M+ ask. Later-stage: set detected_stage to

"series_b"

"growth"

— compose report flags this as out of calibrated scope. If ambiguous, ask the user.

Step 3: Review Each Slide ->

slide_reviews.json

Compare each slide against the stage-specific framework and non-negotiable principles. For each slide: identify strengths, weaknesses, and specific recommendations. Map to expected framework. Flag missing expected slides.

Critical: Every critique must cite a specific best-practice principle. No vague feedback.

Step 4: Score Checklist ->

checklist.json

Evaluate all 35 criteria from

references/checklist-criteria.md

. For non-AI companies, mark AI category items as

not_applicable

cat <<'CHECKLIST_EOF' | python3 "$SCRIPTS/checklist.py" --pretty -o "$REVIEW_DIR/checklist.json"
{
  "items": [
    {"id": "purpose_clear", "status": "pass", "evidence": "Sequoia: single declarative sentence", "notes": "Clear one-liner with quantified outcome"},
    ...all 35 items...
  ]
}
CHECKLIST_EOF

Evidence required: Always provide

evidence

for

fail

and

warn

items.

Step 5: Compose Report

python3 "$SCRIPTS/compose_report.py" --dir "$REVIEW_DIR" --pretty -o "$REVIEW_DIR/report.json"

Fix high-severity warnings and re-run. Use

--strict

to enforce a clean report.

Primary deliverable: Read

report_markdown

from the output JSON, write it to

$REVIEW_DIR/report.md

, and display it to the user in full. Present the file path so the user can access it directly. Then add coaching commentary.

Step 6 (Optional): Generate Visual Report

python3 "$SCRIPTS/visualize.py" --dir "$REVIEW_DIR" -o "$REVIEW_DIR/report.html"

Present the HTML file path to the user so they can open the visual report.

Step 7: Deliver Artifacts

Copy final deliverables to workspace root:

{Company}_Deck_Review.md

.html

(if generated),

.json

(optional).

Scoring

Each of 35 items: pass / fail / warn / not_applicable
```
score_pct
```
= pass / (total - not_applicable) x 100
Overall: "strong" (>=85%), "solid" (>=70%), "needs_work" (>=50%), "major_revision" (<50%)

Step	Artifact	Producer
1	`deck_inventory.json`	Agent (heredoc)
2	`stage_profile.json`	Agent (heredoc)
3	`slide_reviews.json`	Agent (heredoc)
4	`checklist.json`	`checklist.py`
5	Report	`compose_report.py`