SaaS Revenue Operations Analyzer

What it does

When your agent uses it

• Checking sales pipeline coverage and deal aging risk before a forecast call
• Tracking how accurate past revenue forecasts have been with MAPE
• Measuring go-to-market efficiency and unit economics for a SaaS team
• Producing a pipeline or forecast report for a revenue review

Example prompts

• “Run the pipeline analyzer on this quarter's deal data and flag any concentration risk.”
• “Calculate our forecast accuracy with MAPE for the last four quarters.”
• “Generate a GTM efficiency report from this sales and marketing spend data.”

Requirements

• Python for the analysis scripts
• JSON input data describing deals, quota and GTM metrics

Workflow steps

3 steps, taken from the step headings in SKILL.md.

1. 1Pipeline Analyzer
2. 2Forecast Accuracy Tracker
3. 3GTM Efficiency Calculator

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 3 files in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SaaS Revenue Operations Analyzer loads about 2.4k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 109 tokens; SKILL.md has 762 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~109

When it runs · the whole SKILL.md, loaded when a task matches

~2.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~10k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 762 words, ~2,359 tokens.

name

revenue-operations

description

Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.

# Analyze pipeline health and coverage
python scripts/pipeline_analyzer.py --input assets/sample_pipeline_data.json --format text

# Track forecast accuracy over multiple periods
python scripts/forecast_accuracy_tracker.py assets/sample_forecast_data.json --format text

# Calculate GTM efficiency metrics
python scripts/gtm_efficiency_calculator.py assets/sample_gtm_data.json --format text

python scripts/pipeline_analyzer.py --input pipeline.json --format text

{
  "quota": 500000,
  "stages": ["Discovery", "Qualification", "Proposal", "Negotiation", "Closed Won"],
  "average_cycle_days": 45,
  "deals": [
    {
      "id": "D001",
      "name": "Acme Corp",
      "stage": "Proposal",
      "value": 85000,
      "age_days": 32,
      "close_date": "2025-03-15",
      "owner": "rep_1"
    }
  ]
}

python scripts/forecast_accuracy_tracker.py forecast_data.json --format text

{
  "forecast_periods": [
    {"period": "2025-Q1", "forecast": 480000, "actual": 520000},
    {"period": "2025-Q2", "forecast": 550000, "actual": 510000}
  ],
  "category_breakdowns": {
    "by_rep": [
      {"category": "Rep A", "forecast": 200000, "actual": 210000},
      {"category": "Rep B", "forecast": 280000, "actual": 310000}
    ]
  }
}

python scripts/gtm_efficiency_calculator.py gtm_data.json --format text

{
  "revenue": {
    "current_arr": 5000000,
    "prior_arr": 3800000,
    "net_new_arr": 1200000,
    "arpa_monthly": 2500,
    "revenue_growth_pct": 31.6
  },
  "costs": {
    "sales_marketing_spend": 1800000,
    "cac": 18000,
    "gross_margin_pct": 78,
    "total_operating_expense": 6500000,
    "net_burn": 1500000,
    "fcf_margin_pct": 8.4
  },
  "customers": {
    "beginning_arr": 3800000,
    "expansion_arr": 600000,
    "contraction_arr": 100000,
    "churned_arr": 300000,
    "annual_churn_rate_pct": 8
  }
}

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 13 other files (scripts, references, assets) in business-growth/skills/revenue-operations of alirezarezvani/claude-skills.

• SKILL.md
• assets/expected_output.json
• assets/forecast_report_template.md
• assets/gtm_dashboard_template.md
• assets/pipeline_review_template.md
• assets/sample_forecast_data.json
• assets/sample_gtm_data.json
• assets/sample_pipeline_data.json
• references/gtm-efficiency-benchmarks.md
• references/pipeline-management-framework.md
• references/revops-metrics-guide.md
• scripts/forecast_accuracy_tracker.py
• scripts/gtm_efficiency_calculator.py
• scripts/pipeline_analyzer.py

Open the folder on GitHubat commit 19392f7

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in alirezarezvani/claude-skills, which our catalogue first saw on October 7, 2026.

• LeoYeAI/openclaw-master-skillsskills/revenue-operationsskills/business-growth/revenue-operations