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 Sttrevens/4dgames-skills --skill steam-launch-forecastgit clone --depth 1 https://github.com/Sttrevens/4dgames-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/sttrevens/4dgames-skills/steam-launch-forecast)<a href="https://agentmods.dev/skills/sttrevens/4dgames-skills/steam-launch-forecast"><img src="https://agentmods.dev/badge/skills/sttrevens/4dgames-skills/steam-launch-forecast/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/sttrevens/4dgames-skills/steam-launch-forecast"><img src="https://agentmods.dev/badge/skills/sttrevens/4dgames-skills/steam-launch-forecast.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00041 | $0.00914 |
| Opus 5.5 | $0.00016 | $0.00366 |
| Sonnet 5.5 | $0.00008 | $0.00183 |
| Haiku 4.5 | $0.00004 | $0.00091 |
Grade A, and why
steam-launch-forecast 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.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Steam Launch Forecast
Use this skill to produce a market-research style forecast for Steam launch performance. It is strongest when the user provides a Steam page, wishlist count, launch date, price, publisher, social links, trailer data, or a list of comparable games.
Workflow
- Parse the target game or game set.
- Names, release dates, prices, wishlist counts, publishers, regions, notes.
- Treat relative dates using the current date and verify fast-moving data online.
- Set the forecast boundary before interpreting signals.
- Declare
Forecast mode:blind_prelaunch,retrospective_backcast, orpost_launch_nowcast. - Record a
Knowledge cutoff: the latest instant at which a permitted input was public or available. Onlyblind_prelaunchis eligible to be described or scored as a blind forecast. - A date-only source captured on release day is not blind-prelaunch evidence unless its order relative to the release is demonstrated with a timestamp and IANA time zone.
- Declare
- Build a game profile.
- Genre, tags, production scale, IP status, localization, demo/Next Fest history, publisher credibility, and main audience regions.
- Collect permitted signals.
- Steam page, SteamDB followers, wishlist rank when visible, discussions, reviews/CCU if released, launch discount, supported languages.
- YouTube, Bilibili, Reddit, Discord, creator coverage, press, and community heat when relevant.
- Mark each material input as verified, provisional, unverified, or disputed; exclude disputed inputs from the estimate.
- In
blind_prelaunchmode, do not use post-launch reviews, CCU, sales, or any signal published after the knowledge cutoff.
- Build a dynamic comparable set.
- Use 3-7 recent comparables, preferably within 6-24 months.
- Match genre, price, scale, audience region, visibility path, and launch condition.
- Model the funnel.
- Wishlists are an input, not the answer.
- Adjust by wishlist freshness, genre conversion, price, review risk, Steam visibility, creator coverage, localization, and regional split.
- If calculating
first-week units / prelaunch wishlist snapshot, call it a snapshot-normalized sales ratio, not cohort conversion.
- Output a forecast.
What ships with it
6 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.
- 2mo ago First seen · 101 lines · 41 tokens per session scan A b9f88e7d2d0b
steam-launch-forecast is a skill published in the GitHub repository Sttrevens/4dgames-skills (4 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 914 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
playtest-report
Structured playtest report template, or turn existing playtest notes into structured feedback.
godot-signals-groups
Build event-driven, decoupled Godot 4.7 gameplay with signals and node groups: declare and emit custom signals, connect with Callables (incl. bind/one-shot), and broadcast to many nodes via groups and callgroup. Use when wiring node communication in a Godot project, replacing tight references with signals…
motion
Reconstruct a skeleton from calibrated mesh projections and sequential VLM joint annotations, then fit joints and skin weights. Generate motion from joint-position trajectories, rhythm and contact constraints through IK; refine bone orientation against the action, then export, retarget and validate on the target mesh.
unity-addressables
Manage Addressables groups, entries, profiles and content builds (com.unity.addressables, reflection-based).
unity-manual-component
Manually add, configure, reorder, and copy components on GameObjects using Unity Editor UI. For one-off Inspector workflows that do not need REST automation.
scenario-unreal-gameplay
Use when building or debugging UE5 gameplay: a character with double jump or dash, abilities with cooldowns, enemy AI that patrols, chases and attacks, a health bar or HUD; choosing Blueprint vs C++, GAS or not, StateTree vs Behavior Tree, EQS or Mass; setting up Enhanced Input, Common UI or UMG; replication…