Trend Demand Forecaster

Turn sales notes, trend signals, seasonal context, promo plans, and inventory constraints into a practical demand forecast brief with base, upside, and downs...

Security Scan

The skill's code and runtime instructions align with its stated purpose (heuristic demand-forecast briefs), request no credentials or installs, and do not attempt external access.

Purpose & Capability

Name/description map to a lightweight, heuristic forecasting helper. Required env vars, binaries, and config paths are empty and consistent with an offline, input-driven planner.

Instruction Scope

SKILL.md explicitly limits the skill to user-provided notes and disallows live-system access; the handler implementation uses only local text parsing and scenario generation and does not reference files, network endpoints, or environment variables outside its input.

Install Mechanism

No install spec is provided (instruction-only install), and included Python source/tests are self-contained; nothing is downloaded or extracted from external URLs.

Credentials

The skill requires no credentials or secrets and does not access environment variables or config paths, which is proportionate to its stated offline, heuristic role.

Persistence & Privilege

always is false and the skill does not request elevated or persistent system presence. It contains code the agent may execute when invoked, which matches normal behavior for a user-invocable skill.

Assessment

This skill appears coherent and low-risk: it uses only the user's provided notes to produce heuristic forecast briefs, includes self-contained Python code and tests, and requests no credentials or external network access. Before installing, you may still want to: (1) review the full handler.py (the provided snippet is consistent but truncated in the metadata), (2) run the bundled tests locally to confirm behaviour, and (3) remember this is heuristic guidance — do not treat outputs as audited or automatic buy/budget instructions and keep human approval for any purchasing or system updates.

Overview

Use this skill to convert rough demand signals into a practical forecast narrative. It is built for teams that need a fast planning layer for the next few weeks, quarter, or seasonal window.

This MVP is heuristic. It does not pull live sales, ads, weather, ERP, marketplace, or competitor data. It relies on the user's provided notes, exports, and planning context.

Trigger

Use this skill when the user wants to:

• forecast demand for the next month, quarter, or seasonal event
• estimate promo lift or post-promo normalization
• plan replenishment against demand uncertainty
• interpret whether demand is recovering, stabilizing, or softening
• turn messy trend notes into a base, upside, downside planning brief

Example prompts

• "Forecast next month's demand using these sales and inventory notes"
• "Build a base, upside, downside demand view for our holiday campaign"
• "Should we buy deeper inventory or stay cautious?"
• "Help me interpret whether demand is rebounding or just promo noise"

Workflow

1. Clarify the planning question, decision horizon, and risk tolerance.
2. Normalize the strongest signals, such as traffic, orders, conversion, price, inventory, and seasonality.
3. Separate baseline demand from promo distortion, stockout distortion, or one-off events.
4. Build base, upside, and downside scenarios with trigger conditions.
5. Return a markdown brief with indicators, action cues, and assumptions.

Inputs

The user can provide any mix of:

• weekly or monthly sales summaries
• traffic, conversion, pricing, and promo notes
• stockout periods, inventory cover, or inbound timing
• launch, seasonal, holiday, or campaign context
• return rate, customer service, or marketplace feedback
• constraints such as cash, lead time, MOQ, or warehouse limits

Outputs

Return a markdown forecast brief with:

• demand narrative and likely mode
• planning horizon and key signals
• base, upside, downside scenarios
• leading indicators to monitor
• inventory and commercial implications
• risk watchlist and next-step actions
• assumptions, confidence notes, and limits

Safety

• Do not claim access to live systems or external trend feeds.
• Treat all scenarios as planning heuristics, not guaranteed forecasts.
• Do not auto-commit buys, budgets, or inventory transfers.
• Downgrade confidence when the user only provides promo-distorted or stockout-distorted history.
• Keep final purchasing and budget decisions human-approved.

Best-fit Scenarios

• ecommerce teams planning 2 to 16 weeks ahead
• operators working from rough exports instead of a forecasting platform
• founders who need a quick demand-planning memo before placing inventory bets
• consultants preparing scenario-based planning recommendations

Not Ideal For

• formal statistical forecasting that requires model calibration and backtesting
• highly granular store-SKU-day forecasting at enterprise scale
• workflows that require automatic PO creation or system sync
• regulated forecasts that need audited financial controls

Acceptance Criteria

• Return markdown text.
• Include scenario, indicator, implication, and risk sections.
• Make the advisory and heuristic framing explicit.
• Keep the output practical for planning and replenishment decisions.