PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
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 mohitagw15856/pm-claude-skills --skill board-deck-narrativegit clone --depth 1 https://github.com/mohitagw15856/pm-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/mohitagw15856/pm-claude-skills/board-deck-narrative)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/board-deck-narrative"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/board-deck-narrative/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/mohitagw15856/pm-claude-skills/board-deck-narrative"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/board-deck-narrative.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 | $0.00060 | $0.01767 |
| Opus 5.5 | $0.00024 | $0.00707 |
| Sonnet 5.5 | $0.00012 | $0.00353 |
| Haiku 4.5 | $0.00006 | $0.00177 |
Grade A, and why
board-deck-narrative 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- board-deck-narrative — 91% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Board Deck Narrative Skill
This skill builds the complete narrative and slide structure for a board presentation — from opening framing to closing asks. It produces slide-by-slide content guidance, not just a list of topics.
Required Inputs
Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked (assumed, confirm) and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).
- Company stage and context (Seed / Series A / Growth — and where you are in the year)
- Board meeting type (Regular quarterly / Annual / Special / Fundraise-related)
- Key themes for this meeting (e.g. strong growth quarter / pivoting strategy / hiring challenge / fundraise update)
- Key metrics to feature
- Decisions needed from the board (if any)
- Time available (e.g. 60 min / 90 min)
- Audience (investors only / investors + independent directors / mixed)
Output Structure
Board Deck Narrative: [Company] — [Quarter/Period]
Meeting type: [Regular quarterly / Special] Time: [X minutes] Narrative theme: [The one-sentence story of this quarter — e.g. "We hit our revenue target, but activation is the problem we need to solve together."]
Opening Frame (Slide 1–2)
Slide 1: Title
- Company name, quarter, date
- One-sentence framing of the meeting's narrative arc
Slide 2: Agenda
- List of sections + time allocation
- Flag which sections need board input vs. are informational
Presenter note: Board members are busy. Tell them in the first 2 minutes what you need from them today. It changes how they listen.
Business Performance (Slides 3–6, ~15 min)
Slide 3: Scorecard / KPI Dashboard
- Content: Key metrics vs. targets for the quarter. No more than 6 metrics.
- Format: Traffic-light table (Green / Amber / Red against plan)
- Narrative: [1–2 sentences — the headline story of the quarter in numbers]
- Don't hide reds. Boards lose trust when they discover hidden problems later.
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.
- 2d ago First seen · 170 lines · 60 tokens per session scan A d15118b9d7b9
board-deck-narrative is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,449 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 1,767 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-12.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…