FylloCode: Skill for Codex

.agents/skills/product-writing/SKILL.md

product-writing is a skill for Codex from Fioooooooo/FylloCode. It costs 66 tokens per session (926 once invoked), scanned A, original, MIT.

Writing guidance for producing evidence-based English and Chinese copy for product, technical, marketing, and internal materials. It focuses on matching the reader, channel, length, and confirmed product facts.

In plain words
What is it for?
Use it when drafting or reviewing feature announcements, documentation, blog posts, interface text, or internal communication. It provides a process for gathering facts and choosing an appropriate voice.
Why use it?
It helps turn product information into clear copy without unsupported claims, empty language, or one generic style for every audience. It also separates confirmed behavior from plans and assumptions.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is Fioooooooo/FylloCode's own configuration. It tells Codex how to work on FylloCode itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything FylloCode configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Fioooooooo/FylloCode. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Fioooooooo/FylloCode/main/.agents/skills/product-writing/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Fioooooooo/FylloCode

Made for: 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-writing

README.md
[![agentmods](https://agentmods.dev/badge/skills/fioooooooo/fyllocode/product-writing/github.svg)](https://agentmods.dev/skills/fioooooooo/fyllocode/product-writing)
Your own site
<a href="https://agentmods.dev/skills/fioooooooo/fyllocode/product-writing"><img src="https://agentmods.dev/badge/skills/fioooooooo/fyllocode/product-writing/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-writing

Your own site · 80×15
<a href="https://agentmods.dev/skills/fioooooooo/fyllocode/product-writing"><img src="https://agentmods.dev/badge/skills/fioooooooo/fyllocode/product-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 926 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 $0.00066 $0.00926
Opus 5.5 $0.00026 $0.00370
Sonnet 5.5 $0.00013 $0.00185
Haiku 4.5 $0.00007 $0.00093

Measured 2mo ago against content hash f06c1417676e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

product-writing 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 2mo 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.

.agents/skills/product-writing/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Writing

Turn product facts into natural, actionable writing for a specific reader. The goal is not to make AI assistance undetectable. It is to prevent unsupported certainty, formulaic structure, empty language, and writing without a recognizable authorial voice.

Before Writing

  1. Read the repository AGENTS.md, inspect git status --short, and read the project guidance that applies to the deliverable. For product documentation, read the relevant documentation architecture and style guidance. Ground feature descriptions in merged code, approved specifications, designs, and tests.
  2. Establish the deliverable, target reader, reader task, publication channel, language, length, and desired action. Do not make one generic piece of writing serve incompatible audiences.
  3. Gather source material: behavior, prerequisites, limitations, compatibility, risks, data, examples, customer language, established terminology, and release dates. Keep confirmed facts, plans, and assumptions distinct.
  4. When useful examples of comparable work or brand voice exist, read a small representative sample. Derive voice decisions from it; do not imitate living authors or copy incidental phrasing into a new context.

When essential information is missing, list concise questions or use explicit placeholders. Never invent capabilities, data, customer feedback, quotations, compatibility, release dates, personal experiences, or conclusions.

Select a Mode

  • Draft from scratch: establish the information structure and factual gaps first. Draft short text directly; propose an outline for long or high-risk content.
  • Edit existing copy: diagnose the most consequential one to three AI-writing signals before choosing a light edit or restructuring. Do not mechanically replace words.
  • Review: preserve intended meaning and give actionable feedback on facts, reader task, specificity, structure, voice, and actionability.
  • Localize: preserve intent, terminology, and product facts while writing naturally in the target language. Do not translate sentence by sentence or distort risk disclosure between languages.

Read the full file on GitHub · 57 lines

Files

What ships with it

5 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.

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. 2mo ago First seen · 57 lines · 66 tokens per session scan A f06c1417676e

Subscribe to this mod's changes

product-writing is a skill published in the GitHub repository Fioooooooo/FylloCode (28 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 926 once invoked, about $0.0003 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 2026-08-30.

Related

product-writing compared with skills from other repositories

product-writing next to 6 skills from other repositories
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