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/lynqu-lead-research

Build a ranked target account list from an ICP or an event, then create the keepers as leads in Lynqu with the fit rationale attached. Requires the Lynqu MCP server.

From plugin
lynqu-ai-toolkit
617 skills

Claude Code

$ npx -y skills add Gravisun/lynqu-ai-toolkit --skill lynqu-lead-research --agent claude-code

SKILL.md

lynqu-lead-research.SKILL.md
name: lynqu-lead-research
description: Build a ranked target account list from an ICP or an event, then create the keepers as leads in Lynqu with the fit rationale attached. Requires the Lynqu MCP server.

Lynqu Lead Research

You turn a fuzzy "who should we go after?" into a ranked, qualified target list that lands in the pipeline with its reasoning attached. Where `lynqu-prospect` goes deep on one account, this goes wide on many, and the discipline that makes it useful is **ranking and pruning before writing**. A hundred unranked leads is not a target list, it's a chore you handed to a rep.

Invocation

/lynqu research <icp description | event name | "companies like {customer}" | url>

A single URL is usually `/lynqu prospect`. Route there rather than doing a shallow version of it here.

Step 1: Anchor on the ICP (evidence, not vibes)

  • **`list-lead-scoring-rules`**: the org has already encoded what it values.

Score against these, not a generic template

  • If no rules exist, or they look stale, say so and offer `/lynqu icp` first.

Ten minutes there prevents researching fifty of the wrong companies

  • **`list-leads`** filtered to won, plus **`get-lead`** on a few: the fastest

read on what actually closes here

  • **`list-companies`**: the firmographic shape of the existing book

If the user supplies an ICP that contradicts the org's own win data, say so once, plainly, then research what they asked for. It's their call, and they may know something the data doesn't.

Step 2: Know what's already in flight

Research that produces accounts the org is already working wastes everyone's time and creates duplicates.

  • **`get-org-summary`**: current book
  • **`list-campaigns`**: what's already being pursued, and by whom
  • **`search-contacts`** and **`list-leads`** per candidate before it makes the

list: cheap, and it turns "new lead" into "someone here already knows them", which is a better lead

Step 3: Build the candidate set

Use your own web capabilities. Good sources, roughly in order of signal:

  • **Event exhibitor and speaker lists**: the highest-intent list in B2B. Someone

paying for a booth has budget, a field team, and a date

  • **Funding and hiring announcements**: budget plus a trigger
  • **Job postings**: the most honest description of a company's pain that exists.

A posting for three field reps is a Lynqu trigger event

  • **Customer lists of adjacent tools**, published case studies, partner pages
  • **Industry directories and associations**

For each candidate capture: company, why it fits, the trigger, a named decision-maker with their title, a public source link, and anything that suggests timing.

Step 4: Rank, then prune

Score each candidate 1–10 on **fit × timing**. Fit without timing is a nurture list; timing without fit is a distraction.

| Band | Meaning | What happens to it | |------|---------|--------------------| | 8–10 | Strong fit, live trigger | Create as a lead, work now | | 6–7 | Good fit, no urgency | Create, nurture, revisit at trigger | | 4–5 | Plausible | Hold in the list, don't create yet | | < 4 | Wrong shape | Drop, and say why: that's ICP feedback |

**Show the ranked table and let the user prune before anything is written.** Research is cheap to redo; a polluted pipeline is not. This confirmation is the most important step in the skill.

Step 5: Create the keepers

On approval, per approved candidate:

1. **`create-lead`**: name, company, role, `source: "research"`. Only fields you can actually stand behind 2. **`add-lead-note`**: the fit rationale, the trigger, the sources, and the score with its reasoning. Six weeks later this note is the difference between a rep opening the conversation well and opening it cold 3. **`list-lead-pipelines`** + **`get-pipeline-stages`**, then **`update-lead-stage`** to the right entry stage: researched leads rarely belong in the same column as inbound 4. **`attach-leads-to-campaign`** when the research is for a campaign or event 5. **`bulk-update-leads`** (≤ 100) for tags and temperature across the cohort 6. **`add-lead-contact-point`** on the 8–10 band only. A dated first action. Creating fifty leads with no tasks produces a list nobody works 7. **`create-company`** where the account matters enough to hold its own record

Assignment: if the org has territories, `list-team-members` and `assign-lead`. Note that `assign-lead` takes the **user id**, while campaign membership takes the `organization_user_id`. `list-team-members` returns both, so read it rather than assuming.

Output format

# Target List · {ICP or event}

Researched {n} candidates · {n} already known · {n} recommended

## Ranked
| # | Company | Fit | Trigger | Decision-maker | Score | Status |
|---|---------|-----|---------|----------------|-------|--------|
| 1 | … | … | Hiring 3 field reps | VP Sales, {name} | 9 | New |
| 2 | … | … | · | … | 6 | Already a lead (Sara) |

## Dropped, and why
{Feeds the ICP anti-profile.}

## Written to Lynqu
- {n} leads created in {pipeline} at {stage}
- {n} attached to {campaign} · tagged {tag}
- {n} first tasks opened for the 8–10 band

Rules and constraints

  • **Write like a person.** Anything a human reads from this skill (a draft, a

note, a task title) is short, plain and specific: short sentences, one ask, the detail that proves you looked. No warm-up lines, no "circling back", no "leverage", no em dashes. A note is three lines of what happened and what is next, not a report. A task title is the action ("Send the 3-seat pricing by Thu"), not a category.

  • **Never invent contact data.** No pattern-guessed emails, no assumed phone

numbers. Blank and "unverified" is the correct output.

  • **Always show the ranked list before creating anything.**
  • **Check for existing leads and contacts per candidate**, not once for the batch.
  • **Bulk cap is 100** per `bulk-update-leads` call.
  • **Every created lead gets a rationale note.** A lead
Read more
@gravisun
Ships withlynqu-ai-toolkit

Operate your entire lead motion (research → capture → manage → follow up → measure) straight from Claude, ChatGPT, Codex or Cursor. Open-source Claude Skills + MCP for AI lead capture, lead research, sales follow-up, and pipeline management. Powered by Lynqu.

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Questions about lynqu-lead-research.

Which coding agents can use lynqu-lead-research?
lynqu-lead-research installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.