ag-bids-mcp/examples/ag-advisor-prompts.md

Ag Advisor — Example Prompts (Grain Marketing)

Example end-user prompts for the Drawbar Ag Advisor, the AI agent that consumes the ag-bids MCP tools (and the underlying ag-monitor /api/data/* HTTP API). They're grouped into Planning (build a marketing strategy) and Monitoring (track prices and act day-to-day), with the tools each prompt leans on so the advisor knows which calls answer the question.

Copy this into the Drawbar repo (e.g. prompts/grain-marketing.md) as a prompt library / eval set. Phrasing is intentionally farmer-natural — the advisor is expected to translate it into tool calls.

What the advisor can see

Capability	Tool(s)
Live local cash bids (per elevator, crop, delivery)	latest_prices, best_local_bid
Cash price history + basis trend per elevator	price_history
Basis movement (overview, then drill-down)	basis_movement → basis_detail
CBOT futures price + change (since open, on day) + carry	futures_quote, list_deliveries
National price received by farmers ($/bu) + MoM/YoY + seasonal	price_trend, price_series
Input costs — diesel ($/gal) + fertilizer ($/ton) + change + seasonal	input_cost_trend, input_cost_series
Local fertilizer/lime snapshot (DTN dealer feed)	current_input_price, current_lime_price
What's covered / is the data fresh	list_sources, list_commodities, list_deliveries, source_health
One-call morning brief	todays_summary

Conventions the advisor should keep in mind:

• Basis is the lever. Positive basis move = cash strengthened vs futures; negative = weakened. basis_movement aggregates and can net divergent elevators to "flat" — follow up with basis_detail when it looks surprising.
• Cash = futures + basis. A sell decision is really two decisions (futures level and basis), and the carry (list_deliveries + futures_quote across months) tells you whether the market pays you to store.
• price_trend/input_cost_trend are the macro/seasonal benchmark — "is today cheap or dear vs history" — not a local bid. Pair them with best_local_bid/latest_prices for the actionable number.
• Grains: corn, soy, wheat. geo for price_trend is US or a 2-letter state (e.g. OH, IA). Fertilizer geo is an AgTransport region (default Cornbelt).

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Planning — build a marketing strategy

1. Build a pre-harvest plan

"I grow corn and soybeans in west-central Ohio. Help me build a pre-harvest marketing plan for this year's corn crop."

Advisor pulls: price_trend("corn", geo="OH", years=10) (where price sits vs norm) · futures_quote("corn", delivery="Dec 2026") (new-crop level) · basis_movement("corn") (is basis a reason to wait or sell) · best_local_bid("corn") (today's actionable cash).

2. Sell now or store?

"I've got 20,000 bushels of soybeans in the bin. Should I sell now or hold into winter?"

price_trend("soy", geo="OH") (seasonal percentile — is now historically high or low) · list_deliveries("soy") + futures_quote("soy", delivery=…) across months (does the carry pay me to store) · basis_movement("soy") (is basis likely to improve) · best_local_bid("soy").

3. Does the market pay me to store? (carry)

"Does the futures carry justify storing corn until March instead of selling at harvest?"

list_deliveries("corn") then futures_quote("corn", delivery=…) for the nearby vs deferred months → compare the spread against storage cost.

4. Time a new-crop sale

"Is now a good time to make a new-crop corn sale for fall delivery?"

price_trend("corn", years=10) (seasonal context) · futures_quote("corn", delivery="Dec 2026") (change on day / since open) · basis_movement("corn", delivery="Oct 2026") · best_local_bid("corn").

5. Seasonality of basis / price

"Historically, what time of year is corn basis strongest around here, and when does the cash price tend to peak?"

price_series("corn", geo="OH") over multiple years (seasonal shape) · price_trend("corn", geo="OH") (this month's percentile vs the same month over the last N years) · price_history("corn", days=…) for the recent basis arc.

6. Compare which crop to sell

"Relative to their 10-year norms, is corn or soybeans the better one to be selling right now?"

price_trend("corn", years=10) vs price_trend("soy", years=10) — compare percentile-vs-normal and YoY, then best_local_bid for each.

7. Breakeven / cost side of the plan

"How have my input costs moved this year — what does that do to my corn breakeven?"

input_cost_trend("diesel") · input_cost_trend("urea"), input_cost_trend("anhydrous"), input_cost_trend("dap"), input_cost_trend("potash") (all $/ton, Cornbelt) — latest + YoY change feed the cost side; combine with price_trend("corn") for the margin picture.

8. Prebuy fertilizer decision

"Should I prebuy urea and anhydrous now or wait until spring?"

input_cost_trend("urea") and input_cost_trend("anhydrous") (seasonal percentile + YoY — are they historically cheap) · input_cost_series(…) for the trend shape · current_input_price() for the latest local dealer quote.

9. Set price targets / a scale-up plan

"Give me three corn price targets to scale out the rest of my old-crop bushels, based on where price sits historically."

price_trend("corn", geo="OH", years=10) (normal, range, percentile) + futures_quote("corn") + basis_movement("corn") → advisor proposes laddered targets above the seasonal normal.

10. Wheat pre-harvest plan

"Build me a marketing plan for this year's wheat ahead of harvest."

price_trend("wheat", geo="OH") · futures_quote("wheat", delivery="Jul 2026") · basis_movement("wheat") · best_local_bid("wheat").

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Monitoring — track prices and act

11. Morning brief

"Give me my grain marketing brief for this morning."

todays_summary() (one call) — then drill in where it flags something.

12. Best bid right now (location-aware)

"Where's the best corn bid within 40 miles of 45810?"

best_local_bid("corn", zip="45810", radius_miles=40) — restricts to nearby elevators and shows the distance. From GPS instead: best_local_bid("corn", lat=40.79, lng=-83.81). latest_prices("corn", zip="45810", radius_miles=40) lists every nearby elevator nearest-first. Without a location these consider every scraped elevator.

Coverage note for the advisor: scraped cash bids are concentrated in Ohio today. If the farmer's zip/GPS is far from Ohio, best_local_bid returns "none in range" plus the nearest elevator's distance — say that plainly (it's a coverage gap, not a price of zero), and fall back to price_trend(commodity, geo=<their state>) for the national/state benchmark.

13. Did futures move today?

"How far has corn moved today — off the open and on the day?"

futures_quote("corn") → reports change since open and change on the day.

14. Basis check

"How has corn basis moved over the last two weeks, and which elevator improved the most?"

basis_movement("corn", days=14) for the headline, then basis_detail("corn", days=14) for the per-elevator split.

15. Best home for a specific delivery

"Which elevator is paying the most for soybeans for January delivery?"

latest_prices("soy", delivery="Jan 2026") / best_local_bid("soy").

16. Is cash near a recent high?

"Is the local corn cash price near its high for the last month?"

price_history("corn", days=30) (recent arc + basis) · price_trend("corn", geo="OH") (seasonal percentile for context).

17. Spread between cash and CBOT

"Has my local basis widened or narrowed this month?"

basis_movement("corn", days=30) → if it nets flat or odd, basis_detail(…).

18. All elevators at a glance

"Show me today's corn bids across all my elevators."

latest_prices("corn") (snapshot table, all sources).

19. What can I price?

"What delivery months can I price corn for right now?"

list_deliveries("corn").

20. Data freshness / trust check

"Are any of my price feeds stale or failing?"

source_health() (and list_sources() for the full roster + last-success times).

21. Fertilizer price watch

"Are fertilizer prices climbing — should I be worried about next year's input bill?"

input_cost_trend("urea"), input_cost_trend("dap"), input_cost_trend("potash"), input_cost_trend("anhydrous") — latest $/ton + MoM/YoY + seasonal; input_cost_series(…) for the trend.

22. Diesel watch for fieldwork

"What's diesel doing — anything I should factor into fall fieldwork costs?"

input_cost_trend("diesel") (U.S. retail $/gal, week-over-week + YoY).

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Cross-cutting — how the advisor synthesizes a recommendation

These show the reasoning, combining several tools into one answer.

A "should I sell today" call:

"Should I sell corn today?"

1. best_local_bid("corn") — the actual number on the table.
2. price_trend("corn", geo="OH", years=10) — is that number historically high or low for this month (percentile vs normal)?
3. futures_quote("corn") — is the board strong/weak today, and which way is it moving (since open / on day)?
4. basis_movement("corn") — is basis strengthening (a reason to wait) or weakening (a reason to capture now)?
5. Synthesis: "Cash is at the 78th percentile vs the last 10 Mays, board is up 6¢ on the day, and basis has firmed 4¢ over two weeks but looks toppy — taking a portion here and leaving the rest for the carry is reasonable."

A "store vs sell" call combines list_deliveries + futures_quote (carry) + basis_movement (expected basis gain) + input_cost_trend("diesel") and storage assumptions to weigh the cost of carry against the expected pickup.

Guidance for the advisor: always anchor a recommendation to a live number (best_local_bid/latest_prices/futures_quote) and use price_trend/input_cost_trend only for context. State the basis and futures pieces separately so the user can act on whichever is actually driving the call.