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 macro-regimegit 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/macro-regime)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/macro-regime"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/macro-regime/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/macro-regime"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/macro-regime.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 | $0.00059 | $0.00821 |
| Opus 5 | $0.00030 | $0.00411 |
| Sonnet 5 | $0.00012 | $0.00164 |
| Haiku 4.5 | $0.00006 | $0.00082 |
Grade A, and why
macro-regime 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 yesterday.
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.
Defaults
| Parameter | Default Value | Rationale |
|---|---|---|
| lookback_quarters | 8 | 2yr captures cycle inflection while remaining responsive |
| regime_indicators | yield_curve, credit_spreads, PMI, VIX, fed_posture | Standard macro regime detection set |
| probability_weighting | bear/base/bull | Three-scenario framework per institutional standard |
Preflight
Run the canonical pre-flight sequence: MCP health probe, ticker resolution, workspace style override, memory load, and coverage check. See contracts/preflight.md. Propagate X-Agentii-Trace header per contracts/x-agentii-trace-header.md.
Data Source Priority (mandatory order)
- Knowledge entries FIRST — query gold.knowledge_entries for L1 regime frameworks
- Historical analogues SECOND — query search_by_analogue(market_regime) for matching cases
- Real-time data LAST — supplemental only
Methodology
Retrieval Scope
structured_only
Retrieval Strategy
- Query knowledge entries for L1 frameworks via search_knowledge_entries
- Query search_by_analogue for historical regime precedents
- Supplement with real-time data
Temporal Scope
See frontmatter temporal_scope block.
Tool Allowlist
See frontmatter allowed_tools.
Protocol
- Regime Detection — classify current macro environment using yield curve, credit spreads, PMI, VIX, Fed posture
- Framework Application — apply relevant L1 framework from references/knowledge-frameworks.md
- Analogue Retrieval — query search_by_analogue(market_regime) for historical precedents
- Probability Weighting — Bear/Base/Bull scenarios with transition catalysts
Output File
{ticker}/{YYYY-MM-DD_HHMM}_macro-regime_{affix}.md
Output Structure
- Executive Summary — current regime with probability weights
- Regime Indicators — yield curve, credit spreads, PMI, VIX with readings
- Framework Analysis — applied L1 frameworks with evidence
- Historical Analogues — matched cases with /v/cases/ citations
- Scenario Matrix — Bear/Base/Bull with catalysts
- Risk Factors and Coverage Gaps
What ships with it
2 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.
- yesterday Changed · +1 lines 87d617a2c767
- 6d ago First seen · 100 lines · 59 tokens per session scan A 0369ac35a7f1
macro-regime is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed today), licensed Apache-2.0. It adds 59 tokens to every session and 821 once invoked, about $0.0003 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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