Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/WARROOM-CEO/COREnpx agentmods add skills/warroom-ceo/core/forecastWrote 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/warroom-ceo/core/forecast)<a href="https://agentmods.dev/skills/warroom-ceo/core/forecast"><img src="https://agentmods.dev/badge/skills/warroom-ceo/core/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/warroom-ceo/core/forecast"><img src="https://agentmods.dev/badge/skills/warroom-ceo/core/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 | $0.00057 | $0.01662 |
| Opus 5.5 | $0.00023 | $0.00665 |
| Sonnet 5.5 | $0.00011 | $0.00332 |
| Haiku 4.5 | $0.00006 | $0.00166 |
Grade A, and why
forecast-th 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 1mo 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Language: All user-facing output — responses, summaries, and any text the user will read — must be written in Thai (ภาษาไทย). Internal logic, file paths, code snippets, and technical values remain in English.
/forecast-th
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Generate a weighted sales forecast with risk analysis and commit recommendations.
Usage
/forecast [period]
Generate a forecast for: $ARGUMENTS
If a file is referenced: @$1
How It Works
┌─────────────────────────────────────────────────────────────────┐
│ FORECAST │
├─────────────────────────────────────────────────────────────────┤
│ STANDALONE (always works) │
│ ✓ Upload CSV export from your CRM │
│ ✓ Or paste/describe your pipeline deals │
│ ✓ Set your quota and timeline │
│ ✓ Get weighted forecast with stage probabilities │
│ ✓ Risk-adjusted projections (best/likely/worst case) │
│ ✓ Commit vs. upside breakdown │
│ ✓ Gap analysis and recommendations │
├─────────────────────────────────────────────────────────────────┤
│ SUPERCHARGED (when you connect your tools) │
│ + CRM: Pull pipeline automatically, real-time data │
│ + Historical win rates by stage, segment, deal size │
│ + Activity signals for risk scoring │
│ + Automatic refresh and tracking over time │
└─────────────────────────────────────────────────────────────────┘
What I Need From You
Step 1: Your Pipeline Data
Option A: Upload a CSV Export your pipeline from your CRM (e.g. Salesforce, HubSpot). I need at minimum:
- Deal/Opportunity name
- Amount
- Stage
- Close date
What ships with it
1 file 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.
- 1mo ago First seen · 217 lines · 57 tokens per session scan A 17a38c6a115b
forecast-th is a skill published in the GitHub repository WARROOM-CEO/CORE (30 stars, last pushed 6mo ago), licensed MIT. It adds 57 tokens to every session and 1,662 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 2026-09-03.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
twitter-reader
Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about…
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
energy-procurement
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis…
airdrop-hunting-guide
Guide to finding and qualifying for crypto airdrops — eligibility criteria, farming strategies, on-chain activity requirements, Sybil detection avoidance, and tracking tools. Use when helping users understand airdrops, check eligibility, or plan participation strategies.
china-portfolio-monitoring
A monitoring framework for tracking the financial results, operating measures, strategic milestones, and risks of companies held by China-focused private-equity funds. It uses measures such as revenue growth, margins, debt, cash flow, and return on equity.