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win-profile

Build WIN target profiles from public signals.

Skill by andrew-tomago

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/andrew-tomago-win-profile

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Build WIN target profiles from public signals. Use to generate profiles.json, validate target input shape, and extract interests/style before scoring.

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Shell scripts

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/win-profile

What's inside

Skill name
win-profile
Description
Build WIN target profiles from public signals. Use to generate profiles.json, validate target input shape, and extract interests/style before scoring.
License
MIT
Instructions
32 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (3)

  • SKILL.md
  • openai.yaml · agents/
  • run_profile.sh · scripts/

SKILL.md (first lines)

# WIN Profile

## Overview

Run only the profiling stage to produce `data/output/profiles.json`.

## Workflow

1. Validate target input shape using the `targets.json` contract.
2. If required target inputs are missing, please interview the user to acquire the necessary inputs before running commands.
3. Run profiling from `targets.local.json` (or fallback to `targets.json`).
4. Confirm profile count and inspect top interests before evaluation.

## Command

```bash
scripts/run_profile.sh
```

## Input Contract

Expected target schema is documented in:
- `../win-committee/references/data-contracts.md`

## Guardrails

- Use only public or user-provided target signals.
- Do not infer sensitive attributes.
- If required inputs are missing, please interview the user to acquire the necessary inputs.
- Keep personalized data in `*.local.json` files.

From andrew-tomago/weighted-intelligence-nodes, MIT.

More from andrew-tomago/weighted-intelligence-nodes

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Last commit (this folder)
Feb 5, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
Repository
github.com/andrew-tomago/weighted-intelligence-nodes
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
GitHubgithub-graphql

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win-profile skill. Agent Mart. https://agentmart.dev/skills/andrew-tomago-win-profile (last updated 2026-10-24)