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 sruthir28/enterprise-ai-skills --skill mckinsey-chartsgit clone --depth 1 https://github.com/sruthir28/enterprise-ai-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/sruthir28/enterprise-ai-skills/mckinsey-charts)<a href="https://agentmods.dev/skills/sruthir28/enterprise-ai-skills/mckinsey-charts"><img src="https://agentmods.dev/badge/skills/sruthir28/enterprise-ai-skills/mckinsey-charts/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/sruthir28/enterprise-ai-skills/mckinsey-charts"><img src="https://agentmods.dev/badge/skills/sruthir28/enterprise-ai-skills/mckinsey-charts.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 | $0.01141 |
| Opus 5 | $0.00042 | $0.00571 |
| Sonnet 5 | $0.00017 | $0.00228 |
| Haiku 4.5 | $0.00008 | $0.00114 |
Grade A, and why
mckinsey-charts 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 12d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
McKinsey Charts
Drop-in chart builders for python-pptx. Charts are inserted as native PowerPoint chart objects — your audience can edit the data, change the colors, copy the chart to their own deck. No images, no screenshots.
The Three Charts
| Type | When to use | Example |
|---|---|---|
bar_callout |
One number is the story. TAM, market size, headcount, anything where you want to anchor on a single highlighted bar with a big callout. | "RTD coffee TAM will hit $42.5B by 2028" |
stacked_bar_over_time |
Composition over time. Revenue by segment, usage by feature, headcount by function. Shows both total growth and mix shift. | "Revenue grew 3x, but enterprise segment grew 7x" |
waterfall |
Bridging two numbers. Revenue walk, cost walk, headcount changes, any "start → adds → subtracts → end" story. | "FY24 → FY25 revenue bridge: $80M → $112M" |
Design choices (intentional, not configurable)
- Title is a claim, not a label. "RTD market will hit $42.5B by 2028" beats "Market Size."
- One highlight color, everything else grey. McKinsey decks don't rainbow. The chart points at one thing.
- No gridlines, no chart border, no legend unless multi-series. Less ink → more signal.
- Source line at the bottom in light grey italic. Always include it.
- Single font (Inter) at consistent sizes. Title 20pt, axis 10pt, source 9pt.
How to use
from pptx import Presentation
from pptx.util import Inches
from charts import add_bar_callout, add_stacked_bar_over_time, add_waterfall, new_deck
prs = new_deck() # 16:9 with title slide layout
slide = prs.slides.add_slide(prs.slide_layouts[6]) # blank
add_bar_callout(
slide,
title="RTD coffee TAM will hit $42.5B by 2028",
categories=["2023", "2024", "2025", "2026", "2027", "2028"],
values=[28.1, 30.8, 33.6, 36.5, 39.4, 42.5],
highlight_index=5, # which bar to highlight (last one here)
callout="$42.5B\n2028 TAM",
y_label="USD, billions",
source="Euromonitor 2025; Mintel; team analysis",
)
prs.save("output.pptx")
What ships with it
2 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.
- 12d ago First seen · 92 lines · 83 tokens per session scan A e31f8f632e3e
mckinsey-charts is a skill published in the GitHub repository sruthir28/enterprise-ai-skills (139 stars, last pushed 11d ago), licensed MIT. It adds 83 tokens to every session and 1,141 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 2026-08-30.
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