Claude Code Skills Marketplace is a collection and marketplace of skills, plugins, agents, and instructions that extend Claude Code with specialized development workflows. It is for developers who want to install existing workflows or create, validate, and package their own Claude Code skills.
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 daymade/claude-code-skills --skill meeting-minutes-takergit clone --depth 1 https://github.com/daymade/claude-code-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/daymade/claude-code-skills/meeting-minutes-taker)<a href="https://agentmods.dev/skills/daymade/claude-code-skills/meeting-minutes-taker"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/meeting-minutes-taker/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/daymade/claude-code-skills/meeting-minutes-taker"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/meeting-minutes-taker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Memory Poisoning · line 335 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
- medium Excessive Agency · line 687 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00190 | $0.09007 |
| Opus 5 | $0.00095 | $0.04503 |
| Sonnet 5 | $0.00038 | $0.01801 |
| Haiku 4.5 | $0.00019 | $0.00901 |
Grade A, and why
meeting-minutes-taker 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 11d 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 — 716 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Minutes Taker
Transform raw meeting transcripts into comprehensive, evidence-based meeting minutes through iterative review.
Quick Start
Pre-processing (Optional but Recommended):
- Document conversion: Use
doc-to-markdownskill to convert .docx/.pdf to Markdown first (preserves tables/images) - Transcript cleanup: Use
transcript-fixerskill to fix ASR/STT errors if transcript quality is poor - Context file: Prepare
context.mdwith team directory for accurate speaker identification
Core Workflow:
- Read the transcript provided by user
- Load project-specific context file if provided by user (optional)
- Intelligent file naming: Auto-generate filename from content (see below)
- Speaker identification: If transcript has "Speaker 1/2/3", FIRST ask the user to label speakers on the source platform and re-export (see Step 1.5 Phase 0); infer from text only as a fallback
- Multi-turn generation: Use multiple passes or subagents with isolated context, merge using UNION
- Self-review using references/completeness_review_checklist.md
- Present draft to user for human line-by-line review
- Cross-AI comparison (optional): Human may provide output from other AI tools (e.g., Gemini, ChatGPT) - merge to reduce bias
- Iterate on feedback until human approves final version
Intelligent File Naming
Auto-generate output filename from transcript content:
Pattern: YYYY-MM-DD-<topic>-<type>.md
| Component | Source | Examples |
|---|---|---|
| Date | Transcript metadata or first date mention | 2026-01-25 |
| Topic | Main discussion subject (2-4 words, kebab-case) | api-design, product-roadmap |
| Type | Meeting category | review, sync, planning, retro, kickoff |
Examples:
2026-01-25-order-api-design-review.md2026-01-20-q1-sprint-planning.md2026-01-18-onboarding-flow-sync.md
Ask user to confirm the suggested filename before writing.
What ships with it
3 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.
- 11d ago First seen · 716 lines · 190 tokens per session scan A ab6bb018326e
meeting-minutes-taker is a skill published in the GitHub repository daymade/claude-code-skills (1,387 stars, last pushed today), licensed MIT. It adds 190 tokens to every session and 9,007 once invoked, about $0.0010 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
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…
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…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…