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 rules/homenshum/nodebenchai/forecasting_osgit clone --depth 1 https://github.com/HomenShum/NodeBenchAIWhat 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 | $0.00000 | $0.00992 |
| Opus 5 | $0.00000 | $0.00496 |
| Sonnet 5 | $0.00000 | $0.00198 |
| Haiku 4.5 | $0.00000 | $0.00099 |
Grade A, and why
forecasting_os 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forecasting OS
Architecture
Three surfaces, one data spine
- LinkedIn posts: Signals surface as Δ badges (Post 1), evidence→forecast links (Post 2), delta + trace breadcrumbs (Post 3)
- Dashboard (ForecastCockpit): CalibrationPlot, BrierTrendChart, ForecastCard with evidence timeline, TraceBreadcrumb
- MCP tools: 9 tools (create_forecast, refresh_forecast, resolve_forecast, get_forecast, list_forecasts, add_forecast_evidence, get_forecast_track_record, compute_calibration, create_forecast_from_signal)
Cross-reference engine (deterministic, no LLM)
signalMatcher.ts: keyword overlap (+1/token), entity match (+3), tag match (+2), driver match (+2). Threshold: score ≥ 3- Exports:
matchSignalsToForecasts,matchFindingsToForecasts,formatDeltaBadge,formatEvidenceLink
TRACE wrapping
- Every forecast refresh is TRACE-audited: 6 steps (query → fetch → match → score → update → complete)
- Every LinkedIn post is TRACE-audited: 5 steps (digest → explanations → cross-ref → format → post)
workflowTaglinks steps across an execution (e.g.forecast_refresh_2026-02-15)
Key files
| File | Purpose |
|---|---|
convex/domains/forecasting/forecastManager.ts |
CRUD + 6 public dashboard queries |
convex/domains/forecasting/signalMatcher.ts |
Deterministic signal↔forecast cross-reference |
convex/domains/forecasting/traceWrapper.ts |
TRACE-wrapped forecast refresh (6 audit steps) |
convex/domains/forecasting/scoringEngine.ts |
Brier + log scoring, proper scoring rules |
convex/domains/forecasting/schema.ts |
5 tables: forecasts, forecastEvidence, forecastResolutions, forecastUpdateHistory, forecastCalibrationLog |
convex/workflows/dailyLinkedInPost.ts |
LinkedIn pipeline with Δ badges, evidence links, TRACE |
src/features/research/components/ForecastCockpit.tsx |
Dashboard assembler (CalibrationPlot, BrierTrendChart, ForecastCard) |
packages/mcp-local/src/tools/forecastingTools.ts |
9 MCP tools |
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 · 60 lines · 0 tokens per session scan A eda2b05045e7
forecasting_os is a cursor rule published in the GitHub repository HomenShum/NodeBenchAI (14 stars, last pushed 18d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 992 tokens. 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.
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