agentleFS
spiralcrew-ouspiralcrew-ou/profilespider-agent-skills/lead-research-workflow-planner/SKILL.md

lead-research-workflow-planner

Skill9 starsChanged 5 months agoMITView on GitHub

Designs an end-to-end process for finding, extracting, enriching, qualifying, and exporting leads. Use when the user wants a repeatable lead workflow plan rather than a single source plan.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep the plan tool-agnostic unless tools are given.

    line 50

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Lead Research Workflow Planner

Purpose

Design an end-to-end process for finding, extracting, enriching, qualifying, and exporting leads.

When to use this skill

  • Standing up a repeatable lead process
  • Documenting a pipeline for a team
  • Scoping a list-build project end to end
  • Aligning sourcing, enrichment, and QC

When not to use this skill

  • You only need to choose sources (use Directory Research Planner)
  • You want the work executed now (this plans it)
  • The goal is undefined

Required inputs

  • A lead-generation goal or ICP

Optional inputs

  • Tools available
  • Output/CRM requirements
  • Volume targets

Rules

  1. Cover the full pipeline, not just sourcing.
  2. Order stages logically with QC before export.
  3. Tie fields to the qualification goal.
  4. State risks and assumptions.
  5. Keep the plan tool-agnostic unless tools are given.

Process

  1. Parse the goal and constraints.
  2. Define ordered workflow stages.
  3. Specify sources, fields, and enrichment.
  4. Add quality-control steps.
  5. Define output and list risks.

Output format

Return a workflow plan with the following fields:

  • workflow_stages
  • source_types
  • extraction_fields
  • enrichment_steps
  • quality_control_steps
  • output_format
  • risks_and_assumptions

Validation

  • Confirm stages are ordered and complete.
  • Confirm QC precedes export.
  • Confirm fields support qualification.

Limitations

  • A plan is not execution; results depend on tooling.
  • Volume targets may need source validation.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.