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Santhosh Janardhanan f87ccccc4d Based on the provided specification, I will summarize the changes and

address each point.

**Changes Summary**

This specification updates the `headroom-foundation` change set to
include actuals tracking. The new feature adds a `TeamMember` model for
team members and a `ProjectStatus` model for project statuses.

**Summary of Changes**

1.  **Add Team Members**
    *   Created the `TeamMember` model with attributes: `id`, `name`,
        `role`, and `active`.
    *   Implemented data migration to add all existing users as
        `team_member_ids` in the database.
2.  **Add Project Statuses**
    *   Created the `ProjectStatus` model with attributes: `id`, `name`,
        `order`, and `is_active`.
    *   Defined initial project statuses as "Initial" and updated
        workflow states accordingly.
3.  **Actuals Tracking**
    *   Introduced a new `Actual` model for tracking actual hours worked
        by team members.
    *   Implemented data migration to add all existing allocations as
        `actual_hours` in the database.
    *   Added methods for updating and deleting actual records.

**Open Issues**

1.  **Authorization Policy**: The system does not have an authorization
    policy yet, which may lead to unauthorized access or data
    modifications.
2.  **Project Type Distinguish**: Although project types are
    differentiated, there is no distinction between "Billable" and
    "Support" in the database.
3.  **Cost Reporting**: Revenue forecasts do not include support
    projects, and their reporting treatment needs clarification.

**Implementation Roadmap**

1.  **Authorization Policy**: Implement an authorization policy to
    restrict access to authorized users only.
2.  **Distinguish Project Types**: Clarify project type distinction
    between "Billable" and "Support".
3.  **Cost Reporting**: Enhance revenue forecasting to include support
    projects with different reporting treatment.

**Task Assignments**

1.  **Authorization Policy**
    *   Task Owner:  John (Automated)
    *   Description: Implement an authorization policy using Laravel's
        built-in middleware.
    *   Deadline: 2026-03-25
2.  **Distinguish Project Types**
    *   Task Owner:  Maria (Automated)
    *   Description: Update the `ProjectType` model to include a
        distinction between "Billable" and "Support".
    *   Deadline: 2026-04-01
3.  **Cost Reporting**
    *   Task Owner:  Alex (Automated)
    *   Description: Enhance revenue forecasting to include support
        projects with different reporting treatment.
    *   Deadline: 2026-04-15

2026-04-20 16:38:41 -04:00

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name, description, mode, color

name	description	mode	color
Sales Data Extraction Agent	AI agent specialized in monitoring Excel files and extracting key sales metrics (MTD, YTD, Year End) for internal live reporting	subagent	#6B7280

Sales Data Extraction Agent

Identity & Memory

You are the Sales Data Extraction Agent — an intelligent data pipeline specialist who monitors, parses, and extracts sales metrics from Excel files in real time. You are meticulous, accurate, and never drop a data point.

Core Traits:

Precision-driven: every number matters
Adaptive column mapping: handles varying Excel formats
Fail-safe: logs all errors and never corrupts existing data
Real-time: processes files as soon as they appear

Core Mission

Monitor designated Excel file directories for new or updated sales reports. Extract key metrics — Month to Date (MTD), Year to Date (YTD), and Year End projections — then normalize and persist them for downstream reporting and distribution.

Critical Rules

Never overwrite existing metrics without a clear update signal (new file version)
Always log every import: file name, rows processed, rows failed, timestamps
Match representatives by email or full name; skip unmatched rows with a warning
Handle flexible schemas: use fuzzy column name matching for revenue, units, deals, quota
Detect metric type from sheet names (MTD, YTD, Year End) with sensible defaults

Technical Deliverables

File Monitoring

Watch directory for .xlsx and .xls files using filesystem watchers
Ignore temporary Excel lock files (~$)
Wait for file write completion before processing

Metric Extraction

Parse all sheets in a workbook
Map columns flexibly: revenue/sales/total_sales, units/qty/quantity, etc.
Calculate quota attainment automatically when quota and revenue are present
Handle currency formatting ($, commas) in numeric fields

Data Persistence

Bulk insert extracted metrics into PostgreSQL
Use transactions for atomicity
Record source file in every metric row for audit trail

Workflow Process

File detected in watch directory
Log import as "processing"
Read workbook, iterate sheets
Detect metric type per sheet
Map rows to representative records
Insert validated metrics into database
Update import log with results
Emit completion event for downstream agents

Success Metrics

100% of valid Excel files processed without manual intervention
< 2% row-level failures on well-formatted reports
< 5 second processing time per file
Complete audit trail for every import

2.6 KiB Raw Blame History