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 w95/awesome-claude-corporate-skills --skill dd-meeting-prepgit clone --depth 1 https://github.com/w95/awesome-claude-corporate-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/w95/awesome-claude-corporate-skills/dd-meeting-prep)<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/dd-meeting-prep"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/dd-meeting-prep/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/w95/awesome-claude-corporate-skills/dd-meeting-prep"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/dd-meeting-prep.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 | $0.00000 | $0.00961 |
| Opus 5 | $0.00000 | $0.00481 |
| Sonnet 5 | $0.00000 | $0.00192 |
| Haiku 4.5 | $0.00000 | $0.00096 |
Grade A, and why
dd-meeting-prep 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.
This is a copy
94% identical to dd-meeting-prep — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Diligence Meeting Prep
description: Prepare for due diligence meetings — management presentations, expert network calls, customer references, and advisor sessions. Generates targeted question lists, benchmarks to reference, and red flags to probe. Use before any diligence meeting or call. Triggers on "prep for management meeting", "diligence call prep", "expert call questions", "customer reference questions", or "meeting prep for [company]".
Workflow
Step 1: Meeting Context
Ask the user for:
- Meeting type: Management presentation, expert call, customer reference, advisor check-in, site visit
- Attendees: Who from the target company or third party
- Topic focus: Full business overview, or specific workstream (financial, commercial, operational, tech)
- What you already know: Prior meetings, CIM, data room findings
- Key concerns: Specific issues to probe
Step 2: Generate Question List
Organize questions by priority and topic. Structure depends on meeting type:
Management Presentation
Business Overview (warm-up)
- Walk us through the founding story and key milestones
- How do you describe the business to someone unfamiliar with the space?
- What are you most proud of? What would you do differently?
Revenue & Growth
- Walk us through revenue by customer/segment/geography
- What's driving growth? Price vs. volume vs. new customers
- What does the sales cycle look like? How has win rate trended?
- Where do you see the biggest growth opportunities in the next 3-5 years?
Competitive Positioning
- Who do you lose deals to and why?
- What's your moat? How defensible is it?
- How do customers evaluate you vs. alternatives?
Operations & Team
- Walk us through the org chart — who are the key people?
- What roles are you hiring for? What's been hardest to fill?
- What keeps you up at night operationally?
Financial Deep-Dive
- Walk us through the margin bridge — what's changed and why?
- Any one-time or non-recurring items we should understand?
- How do you think about capex — maintenance vs. growth?
- Working capital seasonality?
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 · 101 lines · 0 tokens per session scan A 28a8826e83de
dd-meeting-prep is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (198 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 961 tokens. A static security scan graded it A with 0 findings. It is 94% identical to dd-meeting-prep, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
design-por-referencia
Use when a landing page, marketing site, or hero section looks generic/AI-made ("cara de vibe coding") and needs a $10k-agency-level redesign, or when building a new landing from scratch. Triggers - "o site ficou com cara de IA", "quero uma landing premium", "redesenha a landing", "faz o site baseado em [site de…
lighthouse-95
Use when a website must score 95+ in every Lighthouse category (Performance, Accessibility, Best Practices, SEO), when scores are stuck below target, or when diagnosing poor FCP, LCP, TBT, or CLS on a deployed site.
seo-validate
SEO validator: meta/OG, Schema.org, hreflang, Core Web Vitals, crawlability. Triggers: SEO, meta tags, Schema.org, hreflang, LCP, INP, CLS, Core Web Vitals, sitemap, crawlability.
debug
Systematic debugging via logs, health checks, hypothesis-driven investigation. Triggers: debug, error, trace root cause, fix bug, reproduce symptom, investigation.
pr
Creates GitHub PR after pre-flight checks (lint/typecheck/tests), structured summary from commits. Triggers: pr, pull request, create PR, ready to merge.
research-mastery
Hierarchical retrieval: KB → MCP/Context7 → web. Triggers: research, fact-check, verify, synthesize, cross-reference, multi-source, cite sources.