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 aAAaqwq/AGI-Super-Team --skill business-intelligencegit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote 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/aaaaqwq/agi-super-team/business-intelligence)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/business-intelligence"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/business-intelligence/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/aaaaqwq/agi-super-team/business-intelligence"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/business-intelligence.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 | $0.00031 | $0.01177 |
| Opus 5 | $0.00015 | $0.00589 |
| Sonnet 5 | $0.00006 | $0.00235 |
| Haiku 4.5 | $0.00003 | $0.00118 |
Grade A, and why
Business Intelligence 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 5d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup
On first use, read setup.md for integration behavior and memory initialization.
When to Use
Use this skill when the user needs to build or improve business intelligence systems: KPI definitions, metric architecture, dashboard planning, executive reporting, and decision review loops.
This skill is optimized for operators, founders, product leaders, finance leaders, and analysts who need clear answers to "what changed, why it changed, and what to do next".
Architecture
Working memory lives in ~/business-intelligence/. See memory-template.md for base structure and status behavior.
~/business-intelligence/
├── memory.md # HOT: goals, KPI ownership, active decisions
├── metric-tree/ # WARM: objective -> driver -> metric maps
├── kpi-contracts/ # WARM: metric definitions and formula versions
├── dashboard-specs/ # WARM: visualization and drill-down specifications
├── insight-briefs/ # WARM: weekly and monthly decision briefs
├── operating-cadence/ # WARM: review rituals and escalation rules
└── archive/ # COLD: retired KPIs and past planning cycles
Quick Reference
Load only the file needed for the current task to keep context focused.
| Topic | File |
|---|---|
| Setup and integration | setup.md |
| Memory schema | memory-template.md |
| Objective and metric tree design | metric-tree.md |
| KPI definition contracts | kpi-dictionary.md |
| Dashboard and drill-down design | dashboard-specs.md |
| Decision brief templates | insight-briefs.md |
| Review rituals and escalation rules | decision-cadence.md |
| Source quality and data contracts | data-contracts.md |
Core Rules
1. Start from Decision Questions, Not Charts
Every BI request must begin with one decision question and one owner.
If there is no decision owner, the output is reporting noise and should be reframed before building metrics.
2. Build a Metric Tree Before Dashboard Design
Map each business objective to drivers, then drivers to measurable KPIs.
What ships with it
10 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.
- 5d ago First seen · 139 lines · 31 tokens per session scan A 5cf7fac4dbfa
Business Intelligence is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,177 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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