Sales Report PDF

Professional Sales Report PDF Generator

Tier 0 Doctrine

• Tier: Master (standalone skill; depends on /sales report output for SALES-REPORT.md input)
• Authority: Invoked via /sales report-pdf; reads SALES-REPORT.md + prospect files from current directory; produces dated PDF
• Determinism first: PDF layout, section structure, color scheme, page spec, and JSON schema are locked constants. The Python script renders deterministically from JSON input. No LLM interpretation of layout or scores.
• No fabrication: Every data point in the PDF originates from SALES-REPORT.md or prospect files. Missing fields are marked "N/A", never invented. Scores pass through unmodified.

IMO (Top-Level)

Constants

Variables

Workflow

BLOCK 1: Prerequisite Verification

Governed by: C&V

Constants: Input source (SALES-REPORT.md), dependencies (Python 3, reportlab, script), script search order (3-step) Variables: report_source, python3_available, reportlab_available, script_path

IMO:

• Ingress: Check current directory for SALES-REPORT.md existence; validate file is non-empty
• Middle:
  • If SALES-REPORT.md does not exist: inform user "No SALES-REPORT.md found. Run /sales report first to generate the pipeline report, then run /sales report-pdf to create the PDF version." — halt
  • If SALES-REPORT.md exists: read contents into report_source; scan for additional prospect files (PROSPECT-ANALYSIS.md, COMPANY-RESEARCH.md, etc.) via Glob
  • Check Python 3 availability: python3 --version — if unavailable, inform user "Python 3 is required for PDF generation. Please install Python 3 and then run: pip install reportlab" — halt
  • Check reportlab: python3 -c "import reportlab; print(reportlab.Version)" — if not installed, inform user and offer to run pip install reportlab; after install, continue
  • Locate script: search 3-step order (ai-sales-team-claude project dir, current working dir, one level up) for scripts/generate_pdf_report.py — if not found, inform user "The PDF generation script was not found at scripts/generate_pdf_report.py. Please ensure the project is properly installed." — halt
• Egress: Confirmed: report_source loaded, python3_available = true, reportlab_available = true, script_path resolved

Go/No-Go: All four prerequisites must pass. Any single failure halts with a specific error message. No partial execution.

BLOCK 2: Data Extraction & JSON Assembly

Governed by: IMO

Constants: JSON root schema, prospect JSON schema, component score keys, action item schema, score distribution schema, weekly focus schema, methodology weights Variables: pipeline_data, prospect_data[], top_prospects_data, action_items, pipeline_health, score_distribution, json_input, report_date

IMO:

• Ingress: report_source content + any discovered prospect files from Block 1
• Middle:
  • Set report_date from system date
  • Parse SALES-REPORT.md to extract:
    • Pipeline overview: total prospects, average score, overall health rating
    • Per-prospect data: name, url, score, grade, stage, next_action, est_value, component_scores (5 keys), key_pain_point, key_contact, risk_factors — missing fields default to "N/A"
    • Top 5 prospects with full component score breakdown, contacts, pain points, approach, risks
    • Action items: priority, company, action, urgency, reason — grouped by timeframe
    • Pipeline health metrics: total, average, grade counts + percentages, highest/lowest scores, health rating
    • Score distribution: per grade band (A+, A, B, C, D) with count, percentage, prospect names
    • Weekly focus: ranked prospects with score, reason, actions list
  • Enrich prospect data from any additional prospect files found in Block 1
  • Assemble methodology block from constant weights
  • Build complete JSON object matching root schema
  • Validate JSON is well-formed before writing
  • Write _pdf_input.json to current working directory
• Egress: _pdf_input.json file on disk; json_input validated

Go/No-Go: JSON must be valid and match root schema. If SALES-REPORT.md parsing yields zero prospects, include an empty prospects array and note in pipeline_health. Proceed unconditionally — partial data is acceptable with "N/A" markers.

BLOCK 3: PDF Generation & Validation

Governed by: Circle

Constants: PDF sections (6), page size, orientation, font, margins, expected length, color scheme (grades + theme), script command pattern Variables: pdf_output_path, script_path, report_date

IMO:

• Ingress: _pdf_input.json on disk + resolved script_path from Block 1
• Middle:
  • Compute output filename: SALES-REPORT-{YYYY-MM-DD}.pdf using report_date
  • Execute: python3 {script_path} _pdf_input.json "SALES-REPORT-{date}.pdf"
  • Capture stdout and stderr from script execution
  • If script exits non-zero: capture full error output, check for common issues (invalid JSON, file permissions, disk space, reportlab version incompatibility), report specific error with suggested fix — do NOT delete _pdf_input.json — halt
  • If script exits zero: verify PDF file exists at expected path
  • Check file size > 0 bytes
  • Check page count is within expected range (4-8 pages nominal; warn if outside but do not fail)
• Egress: pdf_output_path confirmed on disk; file size and page count recorded

Go/No-Go: PDF file must exist and have size > 0. Script non-zero exit halts pipeline. Page count outside 4-8 range triggers warning but does not block.

BLOCK 4: Cleanup & Delivery

Governed by: CTB

Constants: Temp file (_pdf_input.json), cleanup rule (delete on success, keep on failure) Variables: pdf_output_path, json_input

IMO:

• Ingress: PDF generation status from Block 3 (success or failure)
• Middle:
  • If Block 3 succeeded:
    • Delete _pdf_input.json from current directory
    • Compute final file size (human-readable: KB or MB)
    • Read page count from PDF metadata if available
  • If Block 3 failed:
    • Keep _pdf_input.json intact for debugging
    • Report failure details from Block 3 error capture
• Egress: Report to user: PDF file name, location, file size, page count, brief summary of contents

Go/No-Go: Always produces output — either success report (file path + size + pages) or failure report (error details + preserved _pdf_input.json path for debugging).

Rules

1. Never generate a PDF without SALES-REPORT.md present in the current directory — direct user to run /sales report first.
2. Never run the PDF script without checking for reportlab — provide install instructions (pip install reportlab) if missing.
3. Never delete _pdf_input.json on failure — keep for debugging.
4. Never modify the original SALES-REPORT.md during PDF generation.
5. Never generate a PDF from scratch without the markdown report — the report is the single source of truth.
6. Never fail silently — provide full error output from the Python script for debugging.
7. Never skip file size and page count verification after generation.
8. Never omit incomplete prospect data — mark missing fields as "N/A" rather than failing or fabricating.

Reference Pointers