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Agent skill

GitHub Lead Gen

by Ducksss in Ducksss/codex-profiles

A skill your agent uses when running GitHub lead generation for codex-profiles.

MITAuto-check passedMarketing & SEO

Install GitHub Lead Gen

skills CLI
$ npx skills add Ducksss/codex-profiles --skill github-lead-gen -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Ducksss/codex-profiles github-lead-gen --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Ducksss/codex-profiles.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/github-lead-gen .claude/skills/github-lead-gen && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
github-lead-gen
GitHub stars
177
Token cost
~1k tokens
SKILL.md length
438 words
Files
3 (incl. references)
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when running GitHub lead generation for codex-profiles.

  • Works in 7 steps: Search GitHub using the approved lanes… → Keep repository-first candidates only;… → For each candidate, capture the… → …
  • Running GitHub lead generation for codex-profiles
  • SKILL.md covers Purpose, Required Context, Boundaries and Accepted Input, plus 3 more sections
  • Calls node

What it does

GitHub Lead Gen is an agent skill from Ducksss/codex-profiles. Use when running GitHub lead generation for codex-profiles. Finds repository candidates and performs shallow tracker intake before lead qualification. Not for drafting, outreach, or monitoring.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/search-patterns.md`).

It sits in Marketing & SEO, covering Lead generation. It works with GitHub, OpenAI and Bash. The repository describes itself as: Named CODEXHOME profiles and ChatGPT Desktop windows with separate local state, without copying tokens. The licence is MIT.

When your agent uses it

  • Running GitHub lead generation for codex-profiles
  • Tasks that involve Lead generation

Example prompts

  • “/github-lead-gen”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Search GitHub using the approved lanes in references/search-patterns.md.
  2. Keep repository-first candidates only; ignore startup, funding, event, and
  3. For each candidate, capture the repository URL, likely channel, shallow
  4. Search tracker Targets by deterministic key and repository URL using the
  5. If an existing target is found, update only stale lead-gen fields and append
  6. If no target exists, create a Targets record with
  7. Stop after tracker intake. The next workflow is lead qualification.

What it can do on your machine

Read from SKILL.md and the folder at commit 7152cd5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

GitHub Lead Gen loads about 1k tokens when it runs, and up to ~1.4k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 438 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Ducksss/codex-profiles at commit 7152cd5, republished under its MIT licence (© Ducksss). 438 words, ~1,042 tokens.

Download SKILL.mdSave it as .claude/skills/github-lead-gen/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
github-lead-gen
description
Use when running GitHub lead generation for codex-profiles. Finds repository candidates and performs shallow tracker intake before lead qualification. Not for drafting, outreach, or monitoring.

GitHub Lead Gen

Purpose

Find GitHub repository candidates for codex-profiles, dedupe them against the outreach tracker, and hand them off for later qualification. This skill only handles candidate discovery and shallow intake.

Required Context

Before searching, read current product positioning from README.md, policy gates from ops/outreach/launch.md, and live distribution state from the outreach tracker. Load references/search-patterns.md for approved search lanes and example queries.

Boundaries

  • Create or update tracker Targets only.
  • Dedupe against existing tracker targets before creating records.
  • Use Log.Workflow = github-lead-gen for every meaningful intake decision.
  • Set Next Action = Run lead qualification on every accepted candidate.
  • Record only a shallow candidate reason; do not assign final ICP.
  • Do not draft PRs, issues, comments, emails, DMs, forum posts, or listing submissions.
  • Do not contact externally.
  • Do not change ops/outreach/launch.md unless the user explicitly asks for a repo-local handoff.

Accepted Input

  • A new repository candidate with no matching tracker target, or an existing target that needs shallow lead-generation evidence refreshed.
  • Do not overwrite a qualified or submitted target's Status, ICP decision, or phase-specific Next Action.
  • Every accepted new target leaves this phase as Status = Backlog and Next Action = Run lead qualification.

Tracker Protocol

Create one unique run-<UTC-timestamp>-<random-suffix> value and use it as <run-id> for the whole invocation. Start with the complete ledger:

sh
node scripts/outreach-tracker.mjs list --json

For an existing target, claim it before changing fields. For a new target, atomically create the shallow row first, then claim it before adding evidence or logging the handoff:

sh
node scripts/outreach-tracker.mjs upsert <key> --name "<name>" \
  --channel "<channel>" --status Backlog \
  --next-action "Run lead qualification" --notes "<candidate reason and source>"
node scripts/outreach-tracker.mjs claim <key> --by <run-id>

If claim exits 3, skip the target without writing or contacting externally. After a successful claim, record the stable phase label and always release, including on failure:

sh
node scripts/outreach-tracker.mjs log --target <key> \
  --workflow github-lead-gen --action Rechecked \
  --result "Candidate captured for lead qualification" --link "<evidence-url>"
node scripts/outreach-tracker.mjs release <key> --by <run-id>
Show full SKILL.md (172 more words)Show less

Workflow

  1. Search GitHub using the approved lanes in references/search-patterns.md.
  2. Keep repository-first candidates only; ignore startup, funding, event, and social-only surfaces.
  3. For each candidate, capture the repository URL, likely channel, shallow reason, evidence URL, and duplicate key.
  4. Search tracker Targets by deterministic key and repository URL using the tracker; do not maintain a side ledger.
  5. If an existing target is found, update only stale lead-gen fields and append a github-lead-gen log entry.
  6. If no target exists, create a Targets record with:
    • Key: deterministic slug such as gh-owner-repo, awesome-owner-repo, or if-owner-repo.
    • Channel: best existing lead-gen channel, usually Awesome-List PR, Issue-First, Directory, Web, or Manual/Gated.
    • Status: Backlog only for plausible repository leads awaiting qualification; otherwise skip.
    • Priority: leave blank unless the repository is obviously Codex-specific.
    • Next Action: Run lead qualification.
    • Notes: shallow candidate reason and source query.
  7. Stop after tracker intake. The next workflow is lead qualification.

Output

Return a concise handoff:

  • Candidates added.
  • Existing targets updated.
  • Duplicates skipped.
  • Search lanes tried.
  • Any tracker or GitHub access blockers.

© Ducksss, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in .agents/skills/github-lead-gen of Ducksss/codex-profiles.

  • SKILL.md
  • agents/openai.yaml
  • references/search-patterns.md

Open the folder on GitHubat commit 7152cd5

Compare with similar skills

GitHub Lead Gen next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

GitHub Lead Gen compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
GitHub Lead Gen this skillDucksss/codex-profiles177—~1kAutomated safety check: PassMIT
Apify Lead Generationmajiayu000/claude-skill-registry6663 repos~1.1kAutomated safety check: NotesMIT
Generative Engine Optimizationkostja94/marketing-skills1k—~2.9kAutomated safety check: PassMIT
GitHub Project Contributor Finder API Skillbrowser-act/skills6.1k1 repos~1.9kAutomated safety check: PassMIT
Geo Fundamentalswasp-lang/wasp19k9 repos~861Automated safety check: PassMIT
SEO GeoReScienceLab/opc-skills1.8k4 repos~2.1kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about GitHub Lead Gen

What does GitHub Lead Gen do?

A skill your agent uses when running GitHub lead generation for codex-profiles. GitHub Lead Gen is an agent skill from Ducksss/codex-profiles. Use when running GitHub lead generation for codex-profiles.

When should I use GitHub Lead Gen?

GitHub Lead Gen fits situations like: running GitHub lead generation for codex-profiles; tasks that involve Lead generation.

How do I install GitHub Lead Gen in Claude Code?

Run `npx skills add Ducksss/codex-profiles --skill github-lead-gen -a claude-code`. Or copy the skill folder (.agents/skills/github-lead-gen in Ducksss/codex-profiles) into .claude/skills/github-lead-gen in your project. Claude Code loads it when a task matches its description.

How do I install GitHub Lead Gen in Codex?

Run `npx skills add Ducksss/codex-profiles --skill github-lead-gen -a codex`. Or copy the skill folder (.agents/skills/github-lead-gen in Ducksss/codex-profiles) into .agents/skills/github-lead-gen in your project. Codex loads it when a task matches its description.

Can I use GitHub Lead Gen in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Ducksss/codex-profiles --skill github-lead-gen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/github-lead-gen, .gemini/skills/github-lead-gen, .github/skills/github-lead-gen and .opencode/skills/github-lead-gen in your project.

What does GitHub Lead Gen need to run?

Going by SKILL.md and its folder, GitHub Lead Gen needs the command-line tools its instructions call (node).

Does GitHub Lead Gen access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is GitHub Lead Gen safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does GitHub Lead Gen use?

GitHub Lead Gen is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does GitHub Lead Gen use?

About 1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 325 tokens, read only when the agent opens those files.

What are the alternatives to GitHub Lead Gen?

Skills that share tags, products or a category with GitHub Lead Gen: Apify Lead Generation (majiayu000/claude-skill-registry, 666 stars), Generative Engine Optimization (kostja94/marketing-skills, 1k stars), GitHub Project Contributor Finder API Skill (browser-act/skills, 6.1k stars) and Geo Fundamentals (wasp-lang/wasp, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains GitHub Lead Gen?

Ducksss (a GitHub user) maintains it in Ducksss/codex-profiles, which has 177 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 7, 2026.

Source: Ducksss/codex-profiles on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.