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 commands/arome3/code-to-content/product-launchgit clone --depth 1 https://github.com/arome3/code-to-contentWhat 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 | $0.00008 | $0.00813 |
| Opus 5 | $0.00004 | $0.00407 |
| Sonnet 5 | $0.00002 | $0.00163 |
| Haiku 4.5 | $0.00001 | $0.00081 |
Grade A, and why
product-launch 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.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Product Launch Content
Create comprehensive launch content for Product Hunt, Hacker News, Twitter, and LinkedIn.
Differentiation Discovery (offer; never blocking): Before generating, offer to make this unmistakably theirs — ask for the WHY (the thesis/stakes), one defensible opinion, a road not taken, or a rough draft to polish ("write it ugly; I'll keep your voice"). Rank raw material (Slack threads, support tickets, a voice-memo transcript) above clean specs. If declined, proceed on code alone and flag
Distinctiveness: AT RISK. At delivery, run the swap-the-name test + AI-tells blocklist fromreferences/differentiation.md.
Process
-
Analyze the Project Analyze the codebase Claude-natively (read dependency files, detect architecture, grep story hooks like TODO/FIXME, mine
git log) — seereferences/analysis-prompts.md. No scripts required. -
Load Skill Context Read these files:
skills/code-to-content/SKILL.mdskills/code-to-content/references/differentiation.md(WHY / opinion / roads-not-taken)skills/code-to-content/references/product-launch.mdskills/code-to-content/references/posting-plan.md
-
Build Launch Inventory Extract from analysis:
- One-line description (< 10 words)
- Value proposition (problem → solution)
- Target audience
- Key features (3-5 bullets)
- Differentiator (what makes it unique)
- Social proof (users, stars, testimonials)
-
Generate Product Hunt Content
Tagline (60 chars max): "[Action verb] [outcome] with [method]"
Maker Comment:
- Personal greeting
- Why you built it (personal problem)
- 1-2 sentences on the journey
- What you're launching today (features)
- What's coming next (roadmap)
- "I'll be here answering questions"
-
Generate Hacker News Post
Title: "Show HN: [Project] – [One-line description]"
Body:
- What it does (1-2 sentences)
- Why you built it (motivation)
- Technical approach (2-3 sentences)
- Key features (bullets)
- Demo + Code links
- "Would love feedback on [specific aspect]"
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 · 89 lines · 8 tokens per session scan A 9819ceaf452c
product-launch is a command published in the GitHub repository arome3/code-to-content (6 stars, last pushed 2mo ago), licensed MIT. It adds 8 tokens to every session and 813 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
speckit.verify-tasks
Verify tasks marked [X] in tasks.md are implemented, not phantom completions (marked done but backed by missing or dead code).
archive
Archive merged feature specs into project memory with provenance, sweep discovery, and gated cleanup.
verify
Perform a non-destructive post-implementation verification gate validating the implementation against spec.md, plan.md, tasks.md, and constitution.md.
retrospective
Perform a post-implementation retrospective analysis measuring spec adherence, implementation deviations, and lessons learned.
doctor
Validate project health: templates, agent config, Python runner/helpers, constitution, and feature artifacts.
validate
Verify spec-to-task traceability and check that completed tasks produced expected files.