lessie

Search, qualify, and enrich people and companies. Use this skill whenever the user wants to find professionals, candidates, or KOLs by title, company, locati...

Security Scan

The skill's files and runtime instructions are internally consistent with a people-search/enrichment CLI and MCP client: it asks the agent to install and call a Lessie CLI/MCP server, perform auth via a browser, and store tokens under ~/.lessie — nothing in the package appears disproportionate to its stated purpose.

Purpose & Capability

Name/description (people search, enrichment, company research) match the instructions: CLI and MCP client workflows, web_search/web_fetch, enrich/find tools. No unrelated credentials or unrelated binaries are requested.

Instruction Scope

SKILL.md tells the agent to check for the lessie CLI, run `npm install -g @lessie/cli` if missing, call `lessie` subcommands, or fall back to an MCP server. It also instructs opening a browser for OAuth and caching a token at ~/.lessie/oauth.json. These are expected for a CLI-based enrichment tool but do cause local installs, disk writes, and a browser-based auth flow (user confirmation is mandated in the doc). The fallback generic `lessie tools` + `lessie call` workflow can relay arbitrary parameters to the remote service — expected for a tool client but worth noting because it lets the agent send arbitrary JSON payloads to Lessie's remote API.

Install Mechanism

No compiled code is shipped in the skill; the doc recommends installing the @lessie/cli and/or running npx @lessie/mcp-server. Installing from npm is a standard but nonzero risk (packages execute code during install and may be updated on the registry). This install mechanism is proportionate to a CLI client but you should confirm the npm package reputation before global installation or use a sandbox/container.

Credentials

The skill declares no required env vars or credentials. Examples include an optional LESSIE_REMOTE_MCP_URL for MCP configuration and note that OAuth tokens are cached at ~/.lessie/oauth.json. Those are reasonable for a remote enrichment service; no unrelated secrets (AWS, GitHub, etc.) are requested.

Persistence & Privilege

Skill does not request always:true and does not ask to modify other skills. It will create/modify its own config and token under ~/.lessie and may add an MCP entry if the user follows instructions — that is normal for a CLI/MCP integration and within expected scope.

Assessment

This skill appears to do what it says: act as a client for the Lessie people-search service. Before installing or allowing the agent to auto-install: (1) Verify the npm package @lessie/cli and the domain lessie.ai (check package page, maintainers, and recent versions); (2) Prefer running npm install inside a sandbox/container or use the MCP pattern (npx @lessie/mcp-server) if you want to avoid a global install; (3) Be aware the OAuth token will be stored at ~/.lessie/oauth.json — protect that file and revoke tokens if needed; (4) Understand that calling `lessie call` can send arbitrary JSON to Lessie's servers, so avoid sending sensitive secrets/content to the service; (5) Review Lessie's privacy and terms pages and ensure your use of enriched contact data complies with local laws (GDPR, CAN-SPAM). If you want a higher-assurance verdict, provide the actual npm package contents or the published package URL for a more thorough code-level review.

Lessie — People Search & Enrichment

Setup

Lessie supports two modes: CLI (default, recommended) and MCP Server.

Mode A: CLI (default)

Install the Lessie CLI binary:

npm install -g @lessie/cli

Or use without installing:

npx @lessie/cli --version

First-time authorization:

lessie auth

This opens a browser for login/registration. Token is cached at ~/.lessie/oauth.json.

Verify connection:

lessie status

Mode B: MCP Server

Add to your MCP config (Claude Code ~/.claude/mcp.json, Cursor ~/.cursor/mcp.json, etc.):

{
  "mcpServers": {
    "lessie": {
      "command": "npx",
      "args": ["-y", "@lessie/mcp-server"],
      "env": {
        "LESSIE_REMOTE_MCP_URL": "https://app.lessie.ai/mcp-server/mcp"
      }
    }
  }
}

Uninstall

• CLI: npm uninstall -g @lessie/cli && rm -rf ~/.lessie/
• MCP: Remove the "lessie" entry from your .mcp.json and rm -rf ~/.lessie/

Quick start

After setup, try saying to Claude:

• "Find Engineering Managers at Stripe in San Francisco"
• "Look up Sam Altman's contact info"
• "Research OpenAI — recent news and open job postings"

Mode detection

Determine which mode to use at the start of each session:

1. Check if lessie CLI is available: run lessie status
2. If the command succeeds → use CLI mode (call tools via Bash)
3. If the command fails (not found) → attempt auto-install: npm install -g @lessie/cli
4. After install, run lessie status again to verify
5. If install succeeds → use CLI mode
6. If install fails (no npm, permission denied, network error, etc.) → check if MCP tools are available (authorize, use_lessie)
7. If MCP tools are available → use MCP mode
8. If neither → inform the user that installation failed and suggest manual install or MCP setup

Credits & Pricing

Lessie is a credit-based service.

New accounts receive free trial credits. View your balance and purchase more at https://lessie.ai/pricing.

The agent will disambiguate company names before searching to avoid wasting credits on wrong results.

Data & Privacy

• Data sources: Contact and company information is aggregated from publicly available sources (business directories, social profiles, corporate websites).
• Query logging: Search queries are logged for service improvement and abuse prevention. No query data is shared with third parties.
• Data compliance: Lessie follows applicable data protection regulations. Users are responsible for using retrieved contact data in compliance with local laws (GDPR, CAN-SPAM, etc.).
• Privacy policy: https://lessie.ai/privacy
• Terms of service: https://lessie.ai/terms-of-service

Authorization

CLI mode

1. Run lessie status to check token validity.
2. If authorized: false → run lessie auth to open browser for login.
3. After the user completes login, run lessie status again to confirm.

MCP mode

1. Call authorize to check connection status.
2. If already authorized → proceed to use tools directly.
3. If not authorized → authorize returns an authorization URL. Tell the user you need to open a browser for Lessie login/registration, and open it using the appropriate system command:
   • macOS: open "<url>"
   • Linux: xdg-open "<url>"
   • Windows: start "<url>"
4. Tell the user the browser has been opened and they need to complete login/registration.
5. After the user confirms, call authorize again to verify the connection.
6. If authorization fails (timeout, denied, port conflict), follow the diagnostic hints returned by authorize and retry.

Always inform the user before opening the browser — never silently redirect.

Agent behavior rules

Entity disambiguation

When a user mentions a company name that could refer to multiple entities (e.g., "Manus" could be Manus AI, Manus Bio, Manus Plus, etc.), disambiguate before searching:

1. Ask the user which company they mean, or present the top candidates and let them pick.
2. If context makes it unambiguous (e.g., user previously discussed AI agents), state your assumption and confirm: "你是指做 AI Agent 的 Manus AI (manus.im) 吗？"
3. Never silently assume one entity over another — wrong domain = wasted search credits and irrelevant results.

Tools overview

People

Tool	CLI command	When to use
find_people	lessie find-people	Discover people by title, company, location, seniority, audience. Default strategy is hybrid. If a request times out or fails, retry with --strategy saas_only — it's faster (~30s vs ~60s) and more stable, though recall may be lower
enrich_people	lessie enrich-people	Fill missing profile data for known individuals (email, phone, LinkedIn, work history)
review_people	lessie review-people	Deep-qualify ambiguous candidates via web research — skip for obvious matches/mismatches

Companies

Tool	CLI command	When to use
find_organizations	lessie find-orgs	Discover companies by name, keyword, location, size, funding
enrich_organization	lessie enrich-org	Get full profile for known company domain(s) — industry, employees, funding, tech stack
get_company_job_postings	lessie job-postings	View active job openings (needs organization_id from enrich)
search_company_news	lessie company-news	Find recent news articles (needs organization_id from enrich)

Web research

Tool	CLI command	When to use
web_search	lessie web-search	General web search; cached results make follow-up web_fetch free
web_fetch	lessie web-fetch	Extract specific info from a URL via AI summarization

Detailed references

• CLI command examples & MCP calling: See references/cli-reference.md
• Workflow patterns (domain resolution, company research, search+qualify): See references/workflow-patterns.md
• Domain resolution decision tree: See references/domain-resolution.md

Key constraints

• enrich_people / enrich_organization: max 10 per call; split larger lists into batches
• find_people / find_organizations: paginated — use --page for more results
• web_search caches page content; if a result has has_content: true, calling web_fetch on that URL is instant
• Seniority levels: owner, founder, c_suite, partner, vp, head, director, manager, senior, entry, intern
• For people enrichment, providing domain (company domain) alongside name greatly improves match accuracy
• CLI output is JSON on stdout, status messages on stderr — parse stdout for data