5 realistic interactions showing how agent-skill-creator must work
with inarticulate, messy human input — not clean specifications:
1. The File Dump — analyst drags 5 files and types "here"
2. The URL Dump — half-sentence with 2 URLs and "same thing as wasde"
3. The Screenshot + Complaint — Paint-annotated Bloomberg screenshot
and "this is ridiculous" (reveals the workflow was unnecessary —
data already existed in Databricks)
4. The Forwarded Email — 6-message chain with legal disclaimers,
agent extracts the one useful paragraph from Oliver in London
5. The One Word — analyst types "freight", agent infers from desk
context, Databricks catalog, and colleague skills
Closes with 6 design principles: file interpretation over requirements
gathering, context inference, progressive refinement, discovery over
assumption, confirm don't interrogate, fail forward not fail safe.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Full 7-phase simulation of a 25-person ag research team (Ag Modelling,
S&D, Price Assessment) going from 8% tool adoption to 76% via
agent-skill-creator as the on-ramp. Covers: champion discovery,
colleague-to-colleague spread, team lead rollout strategy, MATLAB
model wrapping for PhD quants, Copilot CLI for terminal-shy analysts,
Databricks bridge for shared data infrastructure, and CTO dashboard
metrics 3 months later. Five new skills: export-inspections, wasde-
extractor, yield-model wrapper, daily-assessment, databricks-bridge.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Skill 18: agdb-query-assistant-skill — non-technical analysts ask
questions in plain English, get safe read-only SQL with explanation
before execution. Covers onboarding (new hire learning the schema),
simple queries (trading volume), complex business logic (crush margin
with unit conversions), follow-ups (12-month trends), and security
guardrails (client PII redaction, audit logging, query validation).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The simulations hardcoded ~/.claude/skills/ as the install path even
though the users are on VS Code Copilot. Replaced all 18 occurrences
with the universal ~/.agents/skills/ path, which is the canonical
location that gets symlinked to tool-specific paths by the installer.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Four new data pipeline skills: NOAA satellite crop monitor (4km GeoTIFF
ingestion for VHI/VCI/NDVI), NASA FIRMS fire-to-acreage signal (Brazil
Cerrado burning → soy acreage prediction), vessel grain tracker (AIS bulk
carrier departures → real-time export estimates 3 weeks before official
data), and Copernicus Sentinel-2 field-level NDVI (10m resolution
within-field variability maps). Final library: 16 skills, 8 data sources.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Four new skills: yield predictor (40yr weather-yield regression), Parana
River drought logistics risk (watershed lag model), global crop anomaly
scanner (32 regions, 30yr climatology), and planting window advisor
(farmer-facing GO/WAIT/RISK decision tool). Updated team skill library.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Simulated interactions showing agent-skill-creator in action: WASDE analyzer,
crop/weather monitor, basis/export tracker, and coffee fundamental skills
for a 6-person trading research team.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add overview infographic to README, consultant training presentation
(24 slides), and comprehensive project brief for NotebookLM
infographic generation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
24-slide presentation covering skills definition, agent ecosystem,
problem framing, agent-skill-creator solution, and compounding vision.
Designed for teams with no prior AI agent knowledge.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
