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 agentmods add skills/patrickserrano/lacquer/public-relationsnpx skills add patrickserrano/lacquer --skill public-relationsgit clone --depth 1 https://github.com/patrickserrano/lacquerWrote 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/patrickserrano/lacquer/public-relations)<a href="https://agentmods.dev/skills/patrickserrano/lacquer/public-relations"><img src="https://agentmods.dev/badge/skills/patrickserrano/lacquer/public-relations.svg" alt="Measured on agentmods" 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 | $0.00239 | $0.02035 |
| Opus 5 | $0.00120 | $0.01018 |
| Sonnet 5 | $0.00048 | $0.00407 |
| Haiku 4.5 | $0.00024 | $0.00203 |
Grade A, and why
public-relations 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 3d 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
100% identical to public-relations — 0 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Public Relations & Earned Media
You are an expert in earned media for software products. Your goal is to help the user get covered by journalists, podcasts, and newsletters — efficiently, with respect for the people on the other end of the pitch.
Before Starting
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Core Philosophy
PR is not a substitute for distribution. It's a multiplier for it.
- Earned media doesn't drive direct conversions. A TechCrunch hit will not give you 1,000 paying customers. It will give you backlinks, brand legitimacy, AI-citation surface area, and ammo for sales conversations.
- Pitch journalists like you'd pitch a customer: specific, useful, fast, and never about you.
- The story is not your product. The story is the trend, the data, the conflict, or the human. Your product is the evidence. Every pitchable story bends toward one of three angles — Founding Story, David vs Goliath, or Have an Enemy (a broken system, never a competitor). See references/story-angles.md.
- Chase press for the compound effect, not the traffic bump. The bump fades in a day; authority, journalist relationships, and AI-citation surface compound. Build media relationships before you need them, and run one core asset through the whole repurposing flywheel.
- Speed beats polish on reactive PR. A B+ pitch in the first hour of a story beats an A+ pitch on day three.
When PR is worth it
- You have a real story — proprietary data, a strong opinion, a milestone, a customer with a sharp before/after, or a fresh angle on a trending topic
- You have founder/exec time — journalists want quotes from people with skin in the game, not from a PR rep
- You have a destination — a press page, blog post, or product launch that converts attention into something useful
What ships with it
7 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.
- 3d ago First seen · 143 lines · 239 tokens per session scan A 36fe43e755d9
public-relations is a skill published in the GitHub repository patrickserrano/lacquer (3 stars, last pushed today), licensed MIT. It adds 239 tokens to every session and 2,035 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to public-relations, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
opik
This skill should be used when the user needs to add Opik tracing or integrations to their code, instrument an LLM application, or needs reference for Opik SDK usage (Python, TypeScript, REST API). Use for tasks like "add tracing", "instrument my code", "use trackopenai", "add OpikTracer", "what span types are…
ollama-review
Get a second opinion from a local Ollama LLM on your current code changes. Analyzes staged/unstaged diffs and returns prioritized findings. No API keys needed. Use when user asks to "review with Ollama", "local code review", or "review offline".
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
swarm
Run a multi-agent audit of a codebase by spawning specialized parallel subagents (security, performance, tests, architecture, dead-code), then synthesize their findings into a single prioritized action plan. Use this whenever the user runs /swarm, asks to "audit the repo," "review this codebase," "find issues across…
hyper-plan
Use when about to start a non-trivial implementation that needs decomposition before coding. Also when the user invokes /hyperclaude:hyper-plan. Produces an ordered, bite-sized plan in .hyperclaude/plans/ — the input for /hyperclaude:hyper-plan-review and /hyperclaude:hyper-implement.
hyper-docs-review
Use after documentation edits — typically after the documenter agent runs, or when the user invokes /hyperclaude:hyper-docs-review. Runs Codex for accuracy, drift, completeness, broken links, cross-doc inconsistencies, redundancy — NOT prose or style. Distinct from /hyperclaude:hyper-code-review (code diffs) and…