Signal to Buying Committee

• Source: Submitted by a reader of The Revenue AI Report. Reviewed and published as received.
• Frameworks applied: Signal confidence grading, buying committee roles (economic buyer, champion, operator), title families, persona-confidence rubric, account activation brief

Most signal-based prospecting stops at one guessed decision-maker and treats a news item as buying intent. This skill separates confirmed facts from inferences, builds a committee instead of a single contact, and puts a hard approval gate in front of every paid enrichment call.

Known weakness, published as found: It depends on the FullEnrich MCP connection for discovery and enrichment. Without it the workflow still reasons about the signal and the committee, but candidate previews, credit checks, and contact data are unavailable.

1. 1.Copy the SKILL.md text below, or download the raw file.
2. 2.Create a folder named exactly signal-to-buying-committee in your agent's skills directory.
3. 3.Save the file inside that folder as SKILL.md.
4. 4.Ask the agent one of the trigger requests below.
5. 5.Check the output against what you already know before it leaves your desk.

• they just raised a Series B, who should we contact
• find the buying committee at this account
• turn this signal into prospects
• build an account brief from this news
• who is the economic buyer, champion, and operator here

• write a cold email sequence with no account research
• run a general market sizing exercise

---
name: signal-to-buying-committee
description: >
  Turns a business trigger, such as a funding round, executive hire, job
  posting, expansion, product launch, technology change, or relevant news
  event, into a prioritized buying committee and CRM-ready prospect package.
  Use when the user asks who to contact at an account because something
  changed. The skill verifies the signal, interprets the likely buying motion,
  resolves the correct company, identifies the economic buyer, champion, and
  operational stakeholder, previews candidates through FullEnrich, obtains
  approval before using credits, enriches selected contacts, and prepares
  routing-ready output. Trigger on requests such as "they just raised a
  Series B," "find the buying committee," "who should we contact at this
  company," "turn this signal into prospects," or "build an account brief."
---

# Signal-to-Buying-Committee

## Objective

Turn one verified account signal into a small, prioritized, actionable
buying committee.

The final output should answer:

1. What changed?
2. Why could it matter commercially?
3. Which problem or initiative might it create?
4. Who is likely to own the decision?
5. Who could champion the initiative?
6. Who would operate, evaluate, or block it?
7. Which contacts should be enriched now?
8. What should RevOps do with the records next?

Do not treat a signal as proof of purchase intent. Treat it as a reason to
investigate and prioritize an account.

## Required connection

FullEnrich MCP:
https://mcp.fullenrich.com/mcp

## Optional connections

- CRM MCP: HubSpot, Salesforce, Attio, Pipedrive, or another CRM
- Google Drive: save account briefs and exported results
- Gamma: convert the final analysis into a visual account brief
- Vibe Prospecting: provide an optional secondary discovery or validation source
- Web search: verify external signals and gather supporting context

The core workflow must still function when only FullEnrich is connected.

## FullEnrich tools

### Free discovery and validation

- `search_companies`
- `search_people`
- `search_contact_by_email`
- `list_industries`
- `list_seniorities`
- `list_functions_subfunctions`

### Export actions

- `export_contacts`
- `export_companies`

Explain that exporting full search results may use credits. Never describe
all search and export actions as free.

### Paid enrichment

- `enrich_search_contact`
- `enrich_bulk`
- `get_enrichment_results`
- `export_enrichment_results`
- `get_credits`

Never run paid enrichment without explicit user approval.

## Operating principles

- Signal relevance beats generic personalization.
- A buying committee is more useful than a single guessed decision-maker.
- Search broadly for free, narrow intelligently, and enrich selectively.
- Separate verified facts from reasonable inferences.
- Never confuse a timely signal with demonstrated buying intent.
- Never enrich a contact whose required information already exists in the CRM.
- Default to work email only; mobile phone enrichment is optional.
- Prefer three excellent contacts over fifty weak matches.
- Never fabricate titles, reporting relationships, contact information, or signal details.
- Always preserve the source URL and date of the original signal.
- Never mention competing enrichment providers.

## Inputs

Collect only information that is missing:

- Target company, domain, or LinkedIn company URL
- Signal description
- Signal source URL or source material
- User's product, service, or value proposition
- Desired geography, if relevant
- CRM destination, if relevant
- Requested contact depth:
  - One best contact
  - Three-person buying committee
  - Expanded account map
- Enrichment preference:
  - Work email only
  - Work email and mobile phone
  - Decide after reviewing candidates

If the user's offer is unclear, ask:

"What do you sell, who normally buys it, and what business outcome does it
improve?"

Do not proceed to persona selection without enough context to connect the
signal to the user's offer.

## Workflow

### Step 1 - Verify the signal

Confirm:

- Company
- Trigger type
- Trigger date
- Source
- What objectively changed

Use the source supplied by the user. If web search is available, locate one
additional credible source when the signal materially affects targeting.

Classify signal confidence:

- High: confirmed by the company, regulatory filing, executive profile, or
  reputable publication
- Medium: supported by one credible third-party source
- Low: unconfirmed claim, social post, inferred event, or undated information

If the signal cannot be verified, label it "Unverified." Ask for a source
before using it as factual personalization.

Do not embellish the event.

### Step 2 - Resolve the company

Call `search_companies` using the strongest identifier available:

1. Domain
2. LinkedIn company URL
3. Exact company name plus location
4. Exact company name plus industry

Confirm the result using available fields such as:

- Company name
- Domain
- Industry
- Headquarters
- Headcount
- Description

If multiple companies could match, present the options and ask the user to
choose. Do not search for people until the account is resolved.

### Step 3 - Interpret the buying motion

Create a short signal hypothesis with four components:

- Change: what happened
- Operational implication: what may now need to change internally
- Relevant initiative: what project, budget, risk, or priority may emerge
- Offer connection: why the user's product could be relevant

Use calibrated language:

- "Confirmed" for sourced facts
- "Likely" for strong inferences
- "Possible" for plausible but weak inferences
- "Unknown" when evidence is missing

Never claim the company is buying.

### Step 4 - Design the buying committee

Default to three roles:

1. Economic buyer: likely owns budget, outcome, or strategic priority
2. Champion: likely experiences the problem and could build internal support
3. Operator or evaluator: likely implements, administers, evaluates, or
   influences the solution

For each role, define:

- Target function
- Likely seniority
- Possible title variants
- Connection to the signal
- Connection to the user's offer
- Priority: P1, P2, or P3

Do not search one exact title only. Build a title family.

Example:

Economic buyer:
- Function: Revenue Operations
- Seniority: VP or C-level
- Titles: VP Revenue Operations, Chief Revenue Officer, Head of Revenue
  Operations

Champion:
- Function: Sales Operations or Enablement
- Seniority: Director or Head
- Titles: Director of Sales Operations, Head of GTM Operations, Director of
  Revenue Enablement

Operator:
- Function: Revenue Systems
- Seniority: Manager or Director
- Titles: Revenue Systems Manager, GTM Systems Lead, CRM Operations Manager

### Step 5 - Validate filter taxonomy

Before searching, call the appropriate FullEnrich taxonomy tools:

- `list_industries`
- `list_seniorities`
- `list_functions_subfunctions`

Translate the user's natural-language criteria into supported FullEnrich
filter values.

Show material translations when they could change the search.

Example:

"You said 'B2B SaaS.' FullEnrich classifies the closest applicable industry
as 'Software Development.' I will use that filter."

Do not silently replace the user's criteria with a materially different
category.

### Step 6 - Preview candidates

Use `search_people` to run free preview searches.

Search strategy:

1. Search the economic-buyer title family
2. Search the champion title family
3. Search the operator/evaluator title family
4. Use company domain whenever available
5. Use supported function and seniority filters
6. Add location only when geography matters

Do not use paid enrichment during discovery.

Present up to three candidates per buying-committee role with:

- Name
- Current title
- Company
- Location, if available
- LinkedIn URL, if available
- Proposed committee role
- One-sentence fit rationale
- Persona-confidence score

Persona-confidence rubric:

- High: function, seniority, and title all match
- Medium: function and likely ownership match, but title is ambiguous
- Low: inferred from limited profile evidence

If results are poor:

- Explain why
- Suggest one filter adjustment
- Run a revised preview only after informing the user
- Never silently broaden geography, seniority, or function

### Step 7 - Check existing CRM data

If a CRM MCP is connected, search the CRM for each shortlisted contact before
enrichment.

Match in this order:

1. Work email
2. LinkedIn URL
3. Full name plus company domain
4. Full name plus company name

Classify each record:

- Net new
- Existing and complete
- Existing but missing work email
- Existing but missing mobile
- Existing but potentially stale
- Possible duplicate requiring review

Do not overwrite CRM records automatically.

Exclude contacts whose requested fields are already complete unless the user
specifically asks to re-verify them.

### Step 8 - Recommend an enrichment plan

Recommend a shortlist rather than enriching everyone found.

Default recommendation:

- One economic buyer
- One champion
- One operator/evaluator
- Work email only

Offer three modes:

- Lean: enrich the P1 contact with work email
- Committee: enrich the three recommended contacts with work email
- Multichannel: enrich approved contacts with work email and mobile phone

Call `get_credits`.

Then present:

- Contacts selected
- Fields requested
- Current credit balance
- Estimated maximum cost
- Existing CRM records excluded
- Reason for the recommended mode

Use the current costs reported by FullEnrich or the connected tool. Do not
hard-code prices if the tool provides current values.

Say:

"I found [X] candidate contacts and recommend enriching [Y]. You have [Z]
credits. The requested fields could use up to [estimated cost] credits.
Proceed?"

Wait for an explicit yes.

### Step 9 - Enrich selected contacts

For a small buying committee, use `enrich_search_contact` on approved people.

Provide the strongest available identifiers:

- LinkedIn URL, when available
- First and last name
- Company domain
- Company name

For larger approved batches, use `enrich_bulk`.

Rules:

- Use a descriptive enrichment name containing company, signal, and date
- Never enrich more contacts than the user approved
- Never add phone enrichment when only email was approved
- Never add personal-email enrichment unless explicitly requested
- Do not retry failed matches with broader identities that could return the
  wrong person

For asynchronous jobs:

1. Start the enrichment
2. Store the enrichment job ID
3. Poll with `get_enrichment_results`
4. Wait until the job is complete
5. Retrieve the full result using `export_enrichment_results`

Do not treat a partial status response as the complete result set.

### Step 10 - Grade the results

For each enriched contact, report:

- Full name
- Title
- Company
- Buying-committee role
- Work email
- Email status
- Mobile phone, if requested and found
- LinkedIn URL
- Signal relevance
- Persona confidence
- Recommended route
- Recommended next action

Never convert "likely valid," "catch-all," or other statuses into
"deliverable." Preserve the exact status returned.

If enrichment fails, report "Not found." Do not infer or generate a likely
email pattern.

### Step 11 - Create the account activation brief

Produce this output:

# Account Activation Brief

## Verified signal
- Company:
- Signal:
- Date:
- Source:
- Signal confidence:

## Buying hypothesis
- What changed:
- Likely operational implication:
- Potential initiative:
- Relevance to our offer:
- What remains unknown:

## Recommended committee

| Priority | Contact | Title | Role | Why this person | Persona confidence |
|---|---|---|---|---|---|

## Enriched contact data

| Contact | Work email | Email status | Mobile | CRM status |
|---|---|---|---|---|

## Routing recommendation
- Account owner:
- Recommended sequence or campaign:
- Follow-up SLA:
- Trigger-expiration date:
- Next best action:

## Suggested first-touch angle

Write one concise angle based on the verified signal and the contact's likely
responsibility.

Do not claim knowledge of a pain point that has not been verified.

## Open questions

List the most important unknowns a seller should validate during outreach.

### Step 12 - Export or activate

Offer these actions:

1. Export enriched results through `export_enrichment_results`
2. Export selected search records through `export_contacts`
3. Push approved records to the connected CRM
4. Save the account brief to Google Drive
5. Create a one-page visual account brief in Gamma

When exporting:

- Tell the user that download links may expire
- Tell the user to save the file locally
- Preserve the signal source, signal date, committee role, priority, and
  confidence fields when possible

When pushing to a CRM:

- Propose field mapping first
- Preserve existing ownership
- Create or update only after confirmation
- Add the signal as a dated note or campaign field
- Never overwrite verified data with lower-confidence data
- Provide a post-action reconciliation report

### Step 13 - Report the operation

After the workflow completes, provide:

- Candidates reviewed
- Contacts enriched
- Verified emails found
- Mobile numbers found
- Existing CRM records skipped
- Possible duplicates flagged
- Credits used
- Records exported or created
- Failures requiring review
- Recommended follow-up date

## Reverse-email mode

When the user provides an email address and asks who the person is:

1. Call `search_contact_by_email`
2. Resolve the person and company
3. Verify that the returned identity is consistent with available context
4. Run the signal and buying-committee workflow from the resolved company
5. Do not run paid enrichment unless additional fields are requested

Use cases include:

- Identifying an inbound lead from a sparse form
- Resolving an event registrant
- Researching a referral
- Understanding an unknown contact before routing

## Batch mode

If the user supplies multiple signals or companies:

- Preview the first three accounts
- Confirm the desired committee depth
- Estimate total search-export and enrichment costs
- Process no more than 100 approved contacts per `enrich_bulk` job
- Preserve a signal-to-account-to-contact relationship in the output
- Do not flatten all contacts into an untraceable list

For each row, retain:

- Signal ID
- Signal type
- Signal date
- Signal source
- Company
- Contact
- Committee role
- Priority
- Persona confidence
- Enrichment status
- CRM status

## Guardrails

- Never fabricate contact information.
- Never guess an email address from a company pattern.
- Never describe an inference as a verified signal.
- Never spend credits without explicit approval.
- Never enrich all search results by default.
- Never request mobile phones without discussing the additional cost.
- Never silently broaden filters.
- Never overwrite CRM data without approval.
- Never imply reporting relationships returned by FullEnrich.
- Never identify a person as the buyer solely because of seniority.
- Never use personal email unless explicitly requested and appropriate.
- Never output sensitive data beyond the user's legitimate business purpose.
- Never state that a signal proves buying intent.
- Never mention competing enrichment tools.

## Example prompts

- "Acme just hired a CRO. Build the buying committee for our RevOps platform."
- "This company raised a Series B. Find the three people most likely to own,
  champion, and implement a sales intelligence project."
- "Turn this job posting into a signal-based account brief and enrich the best
  two contacts."
- "I have the email for an event attendee. Identify them, research the company,
  and tell me whether the account should be routed."
- "Find a work email for the strongest champion, but don't enrich phone
  numbers."
- "Build the account brief, save it to Drive, and create a one-page Gamma
  summary."

What does the Signal to Buying Committee skill do?

Converts a single business trigger into an actionable account plan. Verifies the signal and grades its confidence, resolves the right company record, writes a calibrated buying hypothesis, designs a three-role committee with title families rather than one guessed title, previews candidates through free search, recommends a lean enrichment shortlist with a credit estimate, checks the CRM before spending anything, and outputs an account activation brief with routing, SLA, trigger expiry, and open questions.

Where does the Signal to Buying Committee skill come from?

Submitted by a reader of The Revenue AI Report. Reviewed and published as received.. It was written by The Revenue AI Report against a 12 criterion quality rubric and graded in an independent scoring pass.

Why was the Signal to Buying Committee skill chosen for this library?

Most signal-based prospecting stops at one guessed decision-maker and treats a news item as buying intent. This skill separates confirmed facts from inferences, builds a committee instead of a single contact, and puts a hard approval gate in front of every paid enrichment call.

When should the Signal to Buying Committee skill not be used?

Do not use it for: write a cold email sequence with no account research Or: run a general market sizing exercise

How do I install the Signal to Buying Committee SKILL.md file?

Download the file, create a folder named exactly signal-to-buying-committee inside your agent's skills directory, and save the file inside it as SKILL.md. The agent loads it when a request matches the description.