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Agent skill

Link Prospecting

by petera2c in petera2c/simple-table

Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.

MITAuto-check passedMarketing & SEO

Install Link Prospecting

skills CLI
$ npx skills add petera2c/simple-table --skill link-prospecting -a claude-code

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

GitHub CLI
$ gh skill install petera2c/simple-table link-prospecting --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/petera2c/simple-table.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/link-prospecting .claude/skills/link-prospecting && 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
link-prospecting
GitHub stars
229
Used in
3 other repos
Token cost
~1.2k tokens
SKILL.md length
562 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.

  • Works in 9 steps: Clarify the linkable asset and the… → Build 5-10 prospecting queries by default. → Call get_serp_results for those queries. → …
  • Tasks that involve Link building
  • SKILL.md covers Goal, Required inputs, OpenSEO MCP tools and Contact discovery tools, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Link Prospecting is an agent skill from petera2c/simple-table. Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Link building. The repository describes itself as: Lightweight data grid/table for fast, modern web apps. The licence is MIT.

When your agent uses it

  • Tasks that involve Link building

Example prompts

  • “/link-prospecting”

Workflow steps

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

  1. Clarify the linkable asset and the reason someone would reference it.
  2. Build 5-10 prospecting queries by default.
  3. Call get_serp_results for those queries.
  4. If competitors are provided, call get_backlinks_overview for the strongest competitor domains or pages first. Continue without backlink…
  5. For local SEO, use search_local_businesses and get_local_serp_results around priority locations to identify nearby competitors…
  6. Filter prospects
  7. For each good prospect, define the outreach angle
  8. For the strongest prospects, visit or search the prospect site to find the best contact path.
  9. Draft outreach messages. If contact details were found, include the source. If not, list the next best contact-discovery path.

What it can do on your machine

Read from SKILL.md and the folder at commit df2dda2. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Link Prospecting loads about 1.2k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 562 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~28
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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 petera2c/simple-table at commit df2dda2, republished under its MIT licence (© petera2c). 562 words, ~1,180 tokens.

Download SKILL.mdSave it as .claude/skills/link-prospecting/SKILL.md (or your agent's skills folder).
name
link-prospecting
description
Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.

Goal

Find realistic pages, sites, and authors that might reference the user's page, product, study, guide, or tool. Use OpenSEO for prospect discovery, then use available web/search/browser tools for contact discovery.

Required inputs

  • projectId
  • User domain or target URL
  • Linkable asset, page, product, study, tool, or topic
  • Optional competitors
  • Optional market/location/language

OpenSEO MCP tools

  • get_serp_results: find ranking articles, listicles, resource pages, comparisons, and topical publishers.
  • get_backlinks_overview: inspect competitor domain or page backlink/referring-domain patterns.
  • get_domain_overview: qualify important prospect domains.
  • get_ranked_keywords: understand what a prospect or competitor ranks for when topical fit matters.
  • search_local_businesses and get_local_serp_results: use for local SEO link prospecting when nearby businesses, local competitors, or Maps/category signals can reveal partnership targets.
  • research_keywords: expand prospecting queries.

Contact discovery tools

After OpenSEO identifies good prospects, use available non-OpenSEO browsing or search tools for public contact discovery. Depending on the client, this may be web search, page fetches, browser automation, or a search API.

Look for:

  • Author byline pages
  • Contact pages
  • Editorial guidelines
  • About/team pages
  • LinkedIn, X, Bluesky, or other professional profiles
  • Newsletter or publication masthead pages
  • Public email addresses in page HTML or visible page text
  • Structured data such as Person, Organization, sameAs, or email

Only record contact details that were actually found. Include the source URL for any email, profile, or contact form.

Prospecting query patterns

Build queries from the asset/topic:

  • <topic> resources
  • best <category> tools
  • <competitor> alternatives
  • <topic> statistics
  • <topic> guide
  • <topic> examples
  • <topic> templates
  • <topic> software
  • <topic> for <audience>

Use get_serp_results in batches for the most relevant patterns. Send at most 10 queries per call.

Show full SKILL.md (302 more words)Show less

Workflow

  1. Clarify the linkable asset and the reason someone would reference it.
  2. Build 5-10 prospecting queries by default.
  3. Call get_serp_results for those queries.
  4. If competitors are provided, call get_backlinks_overview for the strongest competitor domains or pages first. Continue without backlink evidence if it is unavailable.
  5. For local SEO, use search_local_businesses and get_local_serp_results around priority locations to identify nearby competitors, categories, and local SERP evidence before searching for local chambers, associations, campus resources, community pages, and directories.
  6. Filter prospects:
    • Keep topical relevance and editorial pages.
    • Prioritize articles, directories, resource pages, comparisons, statistics pages, templates, and curated lists.
    • Deprioritize homepages, login pages, thin affiliate pages, spam, unrelated forums, and direct competitors unless a comparison angle is valid.
  7. For each good prospect, define the outreach angle:
    • Broken/missing resource
    • Better current data
    • Useful tool/template
    • Alternative or comparison inclusion
    • Expert quote or supporting reference
  8. For the strongest prospects, visit or search the prospect site to find the best contact path.
  9. Draft outreach messages. If contact details were found, include the source. If not, list the next best contact-discovery path.

Output format

Start with:

  • Best outreach angle
  • Highest-priority prospect type
  • Any data limitations

Then include:

Prospect URLSite/domainSourceRelevanceSuggested angleContact pathPriority

Then provide 2-3 reusable outreach drafts:

  • Resource/list inclusion
  • Article update/reference suggestion
  • Competitor alternative/comparison angle

Guardrails

  • Do not invent email addresses, social handles, or contact names.
  • Do not say OpenSEO found contact details unless an OpenSEO tool returned them. Attribute contact discovery to the web/search/browser source used.
  • If contact details are not available after a reasonable search, recommend specific discovery steps such as checking the author page, contact page, LinkedIn, X, or a reputable contact-enrichment tool.
  • Avoid spammy mass outreach. Personalize by page and reason.
  • Flag prospects that are direct competitors or likely paid placements.

© petera2c, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/link-prospecting of petera2c/simple-table.

Open the folder on GitHubat commit df2dda2

Used in 3 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in petera2c/simple-table, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Link Prospecting 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.

Link Prospecting compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Link Prospecting this skillpetera2c/simple-table2293 repos~1.2kAutomated safety check: PassMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo18k2 repos~1.4kAutomated safety check: PassMIT
SEO DataforseoAgriciDaniel/codex-seo7872 repos~4.6kAutomated safety check: PassMIT
Backlink CheckRyze-AI-Adgent/open-seo-mcp-skills4.4k—~515Automated safety check: PassMIT
Beyondseobeyondtahir/beyondseo155—~4.3kAutomated safety check: PassMIT
Webobsidianxnohat/webobsidian268—~2.1kAutomated safety check: PassMIT

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Categories

Questions about Link Prospecting

What does Link Prospecting do?

Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals. Link Prospecting is an agent skill from petera2c/simple-table. Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.

When should I use Link Prospecting?

Link Prospecting fits situations like: tasks that involve Link building.

How do I install Link Prospecting in Claude Code?

Run `npx skills add petera2c/simple-table --skill link-prospecting -a claude-code`. Or copy the skill folder (.agents/skills/link-prospecting in petera2c/simple-table) into .claude/skills/link-prospecting in your project. Claude Code loads it when a task matches its description.

How do I install Link Prospecting in Codex?

Run `npx skills add petera2c/simple-table --skill link-prospecting -a codex`. Or copy the skill folder (.agents/skills/link-prospecting in petera2c/simple-table) into .agents/skills/link-prospecting in your project. Codex loads it when a task matches its description.

Can I use Link Prospecting 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 petera2c/simple-table --skill link-prospecting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/link-prospecting, .gemini/skills/link-prospecting, .github/skills/link-prospecting and .opencode/skills/link-prospecting in your project.

What does Link Prospecting need to run?

SKILL.md names no scripts, command-line tools or credentials: Link Prospecting is instructions for the agent only.

Does Link Prospecting 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 Link Prospecting 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 Link Prospecting use?

Link Prospecting 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 Link Prospecting use?

About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Link Prospecting?

Skills that share tags, products or a category with Link Prospecting: FLOW SEO Framework (AgriciDaniel/claude-seo, 18k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 787 stars), Backlink Check (Ryze-AI-Adgent/open-seo-mcp-skills, 4.4k stars) and Beyondseo (beyondtahir/beyondseo, 155 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Link Prospecting?

petera2c (a GitHub user) maintains it in petera2c/simple-table, which has 229 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 4, 2026.

Source: petera2c/simple-table on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.