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 agentii-ai/agentii-investment-intelligence --skill leading-indicatorsgit clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligenceWrote 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/agentii-ai/agentii-investment-intelligence/leading-indicators)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/leading-indicators"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/leading-indicators/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/agentii-ai/agentii-investment-intelligence/leading-indicators"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/leading-indicators.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.01967 |
| Opus 5 | $0.00018 | $0.00983 |
| Sonnet 5 | $0.00007 | $0.00393 |
| Haiku 4.5 | $0.00004 | $0.00197 |
Grade A, and why
leading-indicators 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 6d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Methodology inspired by publicly taught trading frameworks; all text is an original paraphrase.
Defaults
| Parameter | Default Value | Rationale |
|---|---|---|
| lookback_quarters | 4 | Standard window for leading-indicators |
| gdp_forecast_lag | 6 months | S&P 500 leads GDP with maximum statistical significance at the 6-month horizon (10-year rolling correlation avg: 0.56, 1960–2020) |
| indicator_frequency | weekly | Money-market and survey indicators are tracked weekly; GDP is quarterly |
| portfolio_bias | long / neutral / short | Macro view resolves to one of three biases governing portfolio construction |
Preflight
Run canonical pre-flight per contracts/preflight.md. Propagate X-Agentii-Trace per contracts/x-agentii-trace-header.md.
Data Source Priority
- Leading indicators framework —
references/leading-indicators-framework.md(bundled methodology) - Knowledge entries — query
search_knowledge_entriesfor supplementary L1 frameworks - Historical analogues — query
search_by_analogue(market_regime, event_type) - Real-time data — FRED (real rates, yield curve, money supply, credit spreads), ISM PMI, UMCSI, jobless claims, building permits, commodity prices, DXY
Methodology
Retrieval Scope
structured_only
Retrieval Strategy
This skill follows Branch (d) Simple Lookup from contracts/retrieval.md: query knowledge entries for L1 macro and leading-indicator frameworks; query search_by_analogue for historical regime analogues resolved from the indicator panel. No unstructured document retrieval.
Temporal Scope
See frontmatter temporal_scope block.
Tool Allowlist
See frontmatter allowed_tools.
Protocol
The Pro-Trader Systematic macroeconomic framework: predict GDP → predict stock-market returns. S&P 500 leads GDP by 6 months (10-year rolling correlation avg 0.56). Two analytical axes: Growth drives earnings (E); Liquidity drives price (P). Detailed indicator methodology, thresholds, and decision rules are in references/leading-indicators-framework.md.
What ships with it
4 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.
- 6d ago First seen · 135 lines · 36 tokens per session scan A 7b210a5f2b71
leading-indicators is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed today), licensed Apache-2.0. It adds 36 tokens to every session and 1,967 once invoked, about $0.0002 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 2026-09-05.
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