Guide · Agent skill
How to use the Revenue Operations Analyzer agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The revenue-operations skill gives an AI agent a set of repeatable checks on a sales team's numbers: pipeline coverage, forecast accuracy measured with MAPE, and go-to-market efficiency metrics such as Magic Number, LTV:CAC and CAC Payback. It is written for revenue or sales operations staff, finance people and analysts working with SaaS data. After this guide you will know what the skill does, how to install it, how to ask for it in plain language, and what data and safety checks to keep in mind.
Revenue Operations Analyzeralirezarezvani/claude-skills · MIT Download the skill Quick start
- 1Download and unzip. Download the ZIP from this page and unzip it so the revenue-operations folder contains SKILL.md.
- 2Place the skill. Move the folder to ~/.claude/skills/ for personal use or to a project's .claude/skills/ folder, or upload the ZIP under Settings → Capabilities → Skills in the Claude apps.
- 3Confirm Python 3. Make sure Python 3 is available, since the scripts use only standard library modules.
- 4Test with sample data. Run the three scripts on the sample pipeline, forecast and GTM files in assets/ to confirm the output looks right.
- 5Format your JSON. Reshape your CRM or finance export into the JSON schema shown in SKILL.md, with all required fields populated.
- 6Ask the agent. Describe the analysis you want in plain language, naming your file and the outcome you need.
- 7Verify and document. Cross-check totals against your source system, then record the results in the matching template.
What is an agent skill and what does this one do?
An agent skill is a folder of instructions, reference files, templates and scripts that an AI agent can load when a task matches its description. This skill's description covers pipeline analysis, forecast tracking and GTM efficiency for SaaS teams, so the agent uses it when you ask about those topics.
Once loaded, the agent can run three Python scripts on JSON files you provide. The pipeline analyzer checks coverage ratios, stage conversion, sales velocity, aging and concentration risk. The forecast accuracy tracker computes MAPE, bias, trends and category breakdowns. The GTM efficiency calculator reports Magic Number, LTV:CAC, CAC Payback, Burn Multiple, Rule of 40 and Net Dollar Retention with ratings. The agent can then explain the results against the skill's benchmarks and fill in report templates for weekly pipeline reviews, forecast reports and GTM dashboards.
Install the revenue-operations skill
Download the ZIP for the revenue-operations skill from this page. Unzip it so the folder is named revenue-operations and contains SKILL.md at its top level. For a personal install, put it in ~/.claude/skills/. For a single project, put it in that project's .claude/skills/ folder.
You can also upload the ZIP in the Claude apps under Settings → Capabilities → Skills.
- Personal install: ~/.claude/skills/
- Project install: .claude/skills/ inside your project folder
- Claude apps: Settings → Capabilities → Skills, then upload the ZIP
Prepare your input files
The scripts read JSON files in the schema the skill describes. They do not read arbitrary spreadsheets. Each tool expects specific fields: the pipeline analyzer needs quota, stages, average cycle days and a list of deals with stage, value, age, close date and owner; the forecast tracker needs forecast periods with forecast and actual values; the GTM calculator needs revenue, cost and customer figures.
The skill ships sample files you can use to test before using real data: assets/sample_pipeline_data.json, assets/sample_forecast_data.json and assets/sample_gtm_data.json. The assets/expected_output.json file shows example output for comparison.
- Export from your CRM or finance system, then reshape the export into the skill's JSON schema
- Start with the sample files to confirm the workflow works before using live data
- Check that every required field is populated
Run the scripts directly
You can run the scripts yourself from the skill folder, or let the agent run them. All scripts support --format text for human-readable output and --format json for dashboards or integrations. Python 3 is required; the scripts use only standard library modules.
python scripts/pipeline_analyzer.py --input assets/sample_pipeline_data.json --format text
python scripts/forecast_accuracy_tracker.py assets/sample_forecast_data.json --format text
python scripts/gtm_efficiency_calculator.py assets/sample_gtm_data.json --format textAsk for it in natural language
You do not need to type commands. The skill triggers on requests about pipeline coverage, forecast accuracy, GTM performance, sales metrics, MAPE, GTM efficiency and unit economics for SaaS teams. Name the file and the outcome you want, and say which template you want filled in if you have one.
Good requests name the data and the goal. For example, ask the agent to run the pipeline analyzer on your pipeline file and flag aging deals, or to calculate MAPE across your forecast history and rate it.
- Check my pipeline coverage against 3x quota using current_pipeline.json
- Calculate MAPE and bias for our last eight quarters of forecasts and rate the accuracy
- Compute Magic Number, LTV:CAC and CAC Payback from this quarter's GTM data and compare them to targets
- Fill in the pipeline review template with this week's numbers
Follow the built-in workflows
The skill includes three workflows. The weekly pipeline review verifies the export, generates the pipeline report, cross-checks totals against your CRM, reviews coverage, aging and concentration, then documents the result in the pipeline review template. The forecast accuracy review runs the tracker, checks actuals against closed-won records, and looks for trends and bias. The GTM efficiency audit calculates metrics, benchmarks them against targets and fills in the GTM dashboard template.
Each workflow asks you to verify and cross-check against your source system before drawing conclusions. Keep that step: the agent works only from the files you give it.
- Weekly pipeline review: assets/pipeline_review_template.md
- Forecast accuracy review: assets/forecast_report_template.md
- GTM efficiency audit: assets/gtm_dashboard_template.md
Safety notes: scripts, network and confidential data
The skill runs scripts, so review them before you trust them with real data. Per the skill's assessment, it runs scripts and does not use the network. The agent does, however, send conversation content to its provider, so check your company's data policy before pasting confidential financial data into a cloud agent.
The benchmarks and rating thresholds are generic rules of thumb, not audited standards. Have a person review any figure used for board-level or audited financial decisions, and confirm the agent has not misread your inputs.
- Runs scripts: yes. Review the three Python files in scripts/ first if your policy requires it.
- Uses network: no
- Confidential data: follow your data policy before sharing financial exports with a cloud agent
What people use it for
- A revenue operations lead runs the weekly pipeline review, checking coverage against 3x quota and flagging deals aging beyond threshold.
- A finance lead measures how far past quarterly forecasts missed, using MAPE and bias to see whether the team systematically over-forecasts.
- A founder checks SaaS unit economics by calculating Magic Number, CAC Payback and Net Dollar Retention before a planning meeting.
- An analyst compares forecast accuracy by rep or segment using the category breakdown output.
- A team prepares a quarterly GTM dashboard by filling in the template with calculated metrics and ratings.
Frequently asked questions
How do I install the revenue-operations agent skill?
Download the ZIP from this page and unzip it so the folder contains SKILL.md. Put it in ~/.claude/skills/ for personal use or in a project's .claude/skills/ folder, or upload the ZIP in the Claude apps under Settings → Capabilities → Skills.
What do I need to run this skill?
You need Python 3, since the scripts use only standard library modules, and JSON input files in the schema the skill describes. The scripts do not work on arbitrary spreadsheets, so export your pipeline, forecast or GTM data and format it to match the sample files.
Is the revenue-operations skill free?
The skill is published under the MIT licence, as stated on this page. Check the licence text in the source repository for the full terms.
What is MAPE and how does the skill calculate it?
MAPE is mean absolute percentage error. The skill calculates it as the mean of |actual minus forecast| divided by |actual|, multiplied by 100. Under 10% is rated Excellent, 10-15% Good, 15-25% Fair, and above 25% Poor.
Does the skill send my data anywhere?
The skill itself is listed as not using the network, but the agent sends conversation content to its provider. Check your company's data policy before pasting confidential financial data into a cloud agent.
Why does the script fail on my spreadsheet?
The scripts expect specific JSON fields, such as quota, stages and deal values for the pipeline analyzer. Reshape your export into the schema shown in SKILL.md, then compare it with the sample files in assets/.
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Our verdict
Use this skill if you are a revenue operations, finance or analytics person who needs repeatable pipeline, forecast accuracy and SaaS unit economics checks from exported JSON data. Pick something else if your data lives only in spreadsheets or CRM exports you cannot reshape, or if you need audited financial conclusions, since the benchmarks are generic and need human review.
Download the skill