Hire an AI sales pipeline analyst

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A data check that lists stale deals, missing dates and missing values, and how far to trust the rest
• Pipeline coverage against quota left, and a coverage figure adjusted for weak deals
• Conversion by stage and time in stage, when you give history
• A list of deals that need action, each with the risk and one next step
• A forecast with Commit, Best Case and Upside, and the assumptions behind each
• A comparison with your CRM's stage-weighted number

How it does the job well

• Never give a single forecast number without a range.
• Do not state a benchmark you cannot source. Use the user's history or mark it MISSING.
• Prepare the review. Do not email buyers, change CRM stages or send reports.
• Research the buyer and their company before writing. One specific, true detail beats ten generic lines.
• Lead with the buyer's problem and outcome, not your features.
• Give every message one clear, low-effort next step.
• Qualify honestly. Record budget, authority, need and timing as known, unknown or assumed.

Mistakes it avoids

• Making claims about results, prices or terms that are not approved.
• Long first messages that ask for too much.
• Updating pipeline numbers on hope rather than evidence.

What a good result looks like

An example, not your task: Your quarter ends in a few weeks and you need to know whether the pipeline can still reach quota.

• Data check. Stale deals, missing dates and values, and how far to trust the numbers.
• Coverage. Open pipeline against quota left, plus a figure adjusted for weak deals.
• Stage conversion and time in stage. How many deals move on at each stage and how long they wait there, when you give history.
• Deals to act on. At-risk deals with the risk and one next step each.
• Forecast. Commit, Best Case and Upside with assumptions, next to your CRM's number.
• Risks and gaps. Amounts at stake and the data you should collect.

How the work is checked

• Personal details are verifiable and correct.
• Each deal update cites the call, email or note behind it.
• Follow-ups have dates and owners.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way April Dunford would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Check the data. It flags deals with no activity in 30 days, no close date, no value or a stage that never changes.
• Measure coverage. It divides open pipeline by quota left, then adjusts it for deals that look weak, stale or single-threaded.
• Score each deal. It looks at how complete the qualification is, how recently the buyer was in touch and how fast the deal moves.
• Find the stalls. It lists deals stuck in a stage past your usual time, and late-stage deals with gaps.
• Build the forecast. It sorts deals into Commit, Best Case and Upside, and compares the result with your CRM's number.
• Name the actions. It ranks the at-risk deals by value and ease of rescue, and gives one concrete next step for each.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id sales-pipeline-analyst only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/sales-pipeline-analyst/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• A list of open deals, with name, stage, value, expected close date and the date of last activity
• Your quota or target left for the period
• The owner of each deal, and the segment or deal size, if you want a breakdown (optional)
• Closed won and lost deals from the last 6 to 12 months, to work out your own win rates (optional)
• The stage each deal entered, to measure time in stage (optional)
• Which qualification facts you know for each deal, such as who signs and who champions it (optional)

Helpful context (optional)

• Closed deals from the last year, so win rates come from your own history.
• The date each deal entered its current stage.
• Meeting notes or the last email date for your biggest deals.

Tools and access

• Claude, ChatGPT or Gemini: A file upload keeps every deal in view, so none are dropped from a long paste.
• Your CRM: You export the deals from it, and update it after you act on the list.

Functions and deliverables

• Sales pipeline analyst: Find out if your pipeline can hit quota. Get coverage, stalled deals to act on and a forecast range of commit, best case and upside.
  • A data check that lists stale deals, missing dates and missing values, and how far to trust the rest
  • Pipeline coverage against quota left, and a coverage figure adjusted for weak deals
  • Conversion by stage and time in stage, when you give history
  • A list of deals that need action, each with the risk and one next step
  • A forecast with Commit, Best Case and Upside, and the assumptions behind each
  • A comparison with your CRM's stage-weighted number
  Source: Michael Sitarzewski and Agency Agents contributors.
• Sales pipeline stage reviewer: Check CRM deals or file exports for stage totals, stalled deals, gaps, and next steps.
  • Coverage by stage
  • Aging deals listed
  • Conversion between stages
  • At-risk deals with record links
  Source: Anthropic.
• Deal win reason finder: Share won and lost deal notes. Get buyer-stated win reasons, your best-fit buyer and a sales message built on evidence.
  • A deal table with quoted reasons and doubts
  • Win and loss patterns, with thin ones marked
  • Win reasons separated from objections handled
  • Your best-fit buyer, the value line and three proof points
• Forecast narrative writer: Ask for your forecast. Get a commit, best case and pipeline story: what is closing, at risk and changed.
  • Closed won, commit, best case and pipeline totals with deal counts
  • A one-line note for each commit and best case deal, linked to its record
  • What changed since last time, if you share last week's notes
  • Risk to commit, with the deal, the risk and a way to reduce it
  • The asks to bring to your manager or leader
  • Suggested forecast category changes you can accept or skip
  Source: Anthropic.
• Brand profile builder: Share your website. Get a reusable profile covering your products, customers, voice and approved claims, with sources.
  • A folder of eight plain files, from a start file for your AI to a claims list and a change log
  • A tag on every fact, and every claim marked approved, pending or banned
  • A two-sentence diagnosis of your biggest gap, and a list of what's missing and who can answer it
  • A short slice for your next step, if you name one
• April Dunford: Work out why buyers should choose your product. Use April Dunford's positioning method to find real alternatives, buyer value and a clear sales pitch.
  • Your problem worked on the way April Dunford would: their questions, their method, their push-back
  • The answer or the work, in April Dunford's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• Your quarter ends in a few weeks and you need to know whether the pipeline can still reach quota.
• Your forecast call is coming, and you want to see which deals are real before you commit a number.
• Win rates are falling, and you need to know at which stage deals die.
• You want a short list of deals to rescue this week, with an action for each.

Limits to check before starting

• You want a repeat review each Monday from a fresh export: use the Sales pipeline deal priority reviewer.
• You only want a forecast, with the maths shown: use the Bookings forecast builder.
• You want to find where visitors drop off on a website or app: use the Conversion funnel analyst.
• You want live numbers. Use your CRM's own reports, and use this agent to question them.
• You have fewer than about 10 open deals. A short list of deals is easier to review by hand.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Add the pack to your AI as a skill. Or open a new chat and paste SKILL.md, then references/source-agent.md.
• Export your open deals from your CRM. Paste them with the column headings. Add closed deals from the last 6 to 12 months if you can.
• Say the period, your quota left and the date today, such as "Q3, $400,000 left, today is 15 Aug".
• Read the data check first. Fix missing close dates and stale deals in your CRM or accept the limits.
• Take the list of deals to act on into your pipeline review. Do the next step for each, then update the CRM.
• Run it again next week with a new export. Paste last week's report so it can show what changed.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/sales-pipeline-analyst for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.