Product Launch Press Kit

Product Launch Press Kit is a skill for Claude Code, Codex from AgentEra/Agently. It costs 43 tokens per session (229 once invoked), scanned A, original, Apache-2.0.

A guide for creating a product launch press kit from a product brief. It produces market positioning, a statement describing the product’s place in the market, and a register of launch risks and mitigations.

In plain words
What is it for?
Use it to prepare positioning, compare listed competitors, identify launch risks, and plan responses before a release.
Why use it?
It brings the product’s market message and possible launch problems into one document while keeping claims tied to the supplied brief.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to prepare positioning, compare listed competitors, identify launch risks, and plan responses before a release.

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Install with agentmods
npx agentmods add skills/agentera/agently/product-launch-press-kit
About the project

Agently is a Python framework for building AI applications that coordinate language models, structured data, tools, and multi-step workflows. Teams use it to create assistants, internal copilots, knowledge tools, operational workflows, and AI-backed APIs.

AgentEra/Agently · 1,649 stars · on GitHub · agently.tech

Install

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.

Any agent
npx skills add AgentEra/Agently --skill product-launch-press-kit
Clone the repo
git clone --depth 1 https://github.com/AgentEra/Agently

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for Product Launch Press Kit

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentera/agently/product-launch-press-kit/github.svg)](https://agentmods.dev/skills/agentera/agently/product-launch-press-kit)
Your own site
<a href="https://agentmods.dev/skills/agentera/agently/product-launch-press-kit"><img src="https://agentmods.dev/badge/skills/agentera/agently/product-launch-press-kit/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.

agentmods 80×15 button for Product Launch Press Kit

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentera/agently/product-launch-press-kit"><img src="https://agentmods.dev/badge/skills/agentera/agently/product-launch-press-kit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 229 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.00229
Opus 5 $0.00022 $0.00114
Sonnet 5 $0.00009 $0.00046
Haiku 4.5 $0.00004 $0.00023

Measured 9d ago against content hash afaece279723, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

Product Launch Press Kit 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 9d 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.

examples/archived/pre-4.1.3.8-skills-orchestration/agent_auto_orchestration/skills/product-launch-press-kit/SKILL.md · 28 lines

What it actually says

Product Launch Press Kit

You are a product marketing lead + technical risk analyst. Given a product brief, produce a launch press kit in ONE pass.

Positioning brief

  • A 2-3 paragraph market landscape summary.
  • One crisp positioning statement.
  • 3-5 differentiators vs the listed competitors, grounded in the brief's features, pricing, and beta results.

Launch risk register

  • 5-8 risks, each with severity (low/medium/high), category (e.g. market, technical, compliance, GTM), and a one-sentence description.
  • For the top 3 risks, add a concrete mitigation.

Be specific to the product brief; do not invent features, pricing, or metrics that are not present.

Changes

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.

  1. 9d ago First seen · 28 lines · 43 tokens per session scan A afaece279723

Subscribe to this mod's changes

Product Launch Press Kit is a skill published in the GitHub repository AgentEra/Agently (1,649 stars, last pushed yesterday), licensed Apache-2.0. It adds 43 tokens to every session and 229 once invoked, about $0.0002 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.