/apify-link-prospecting-outreach

name: apify-link-prospecting-outreach
description: Find sites ranking for target keywords, score every prospect with Ahrefs domain authority and page-level traffic, identify the strongest pitch angle per row ("links to competitor", "mentions brand without linking", "top-3 SERP", "resource page", "outdated content"), generate brand-voice-matched outreach emails using an outreach-type-aware template (unlinked-mention claim, competitor-link replacement, resource-page inclusion, outdated-content replacement, topical niche-edit), and propose a concrete in-article link placement as three artifacts — the verbatim source sentence, the same sentence rewritten with the link spliced in, or a fully-drafted new insertion if no natural fit exists. Use when user asks to find link building opportunities, prospect link partners, recover unlinked brand mentions, replace competitor links, build a tiered outreach list, or run cold email outreach for SEO link building.
author: Daniela Ryplová
author_url: https://github.com/danielarypl
metadata:
  keywords: "link-building, seo, outreach, prospecting, ahrefs, backlinks, cold-email, serp, unlinked-mentions, competitor-links, resource-pages"

Link Prospecting Outreach

Turn a goal + a target keyword + a URL the user wants to promote into a tiered, ready-to-send outreach list: SERP-ranking prospects with Ahrefs-scored authority, the strongest pitch angle per prospect, an outreach-type-matched email draft, and a copy-paste-ready link placement.

Prerequisites

(No need to check it upfront)

• `.env` file with `APIFY_TOKEN`
• Ahrefs MCP available (the skill calls `mcp__claude_ai_Ahrefs__*` tools for prospect scoring)
• Node.js 20.6+ (for native `--env-file` support)
• One-time setup inside the skill's `scripts/` folder: `npm install`

Helper scripts (one config, four steps)

After Step 1–2 inputs are collected, write them to a single **`campaign.json`** (schema in [`campaign.json.example`](campaign.json.example)). Every downstream script reads `--config campaign.json`, so the agent doesn't fork per-campaign copies. Sequence:

# 1. Run the Actor (writes {base}.json + sub-Actor sidecars when --fetch-sub-datasets)
node --env-file=.env scripts/run_actor.js --actor "apify/link-prospecting-tool" --input '<json>' --timeout 1800 --fetch-sub-datasets --output {base}.json --format json

# 2. Build unified prospect table from the sidecars
python3 scripts/build_prospects.py --config campaign.json

# 3. (After Step 5 Ahrefs MCP calls → save to {base}_ahrefs_domain.json + {base}_ahrefs_page.json)
python3 scripts/enrich_prospects.py --config campaign.json

# 4. (After Step 8 sub-agents write outputs to /tmp/placement_outputs/row_*.json)
python3 scripts/merge_subagent_outputs.py --config campaign.json --outputs-dir /tmp/placement_outputs

# 5. Write the final xlsx + metadata sidecar
python3 scripts/write_xlsx.py --config campaign.json

If the runner's client-side wait elapses with the Actor still running on Apify, use `scripts/fetch_run_artifacts.js --run-id <id> --output {base}.json` instead of restarting. If the parent run is missing `SUB_ACTOR_RESULTS` (post-2026-05-20 Actor schema), `scripts/fetch_subactors_from_log.js` resolves sub-Actor runIds from the parent log.

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Collect required anchor inputs incl. goal (block on these)
- [ ] Step 2: Collect brand voice, partnership type, output format
- [ ] Step 3: Run apify/link-prospecting-tool
- [ ] Step 4: Pull leads, mentions, authors, and sub-Actor datasets
- [ ] Step 5: Enrich every domain with Ahrefs metrics, assign Prospect Tier
- [ ] Step 6: Run skip pass — flag rows to drop before drafting
- [ ] Step 7: Compute "Why This Prospect" tag per surviving row
- [ ] Step 8: Compose per-row 3-artifact placement + outreach-type-aware email
- [ ] Step 9: Render output in chosen format

Step 1: Required Anchor Inputs (ask FIRST, before anything else)

Do NOT proceed to Step 2 until every required input is answered. Surface them as the very first interaction. The dedup input (#7) is optional but must still be explicitly asked.

1. **Concrete goal for this campaign** — pick one preset or supply custom text. The goal drives skip-pass filtering, outreach-type template selection, and Prospect Tier thresholds. Required.

| Preset | Effect downstream | |---|---| | `Recover unlinked brand mentions` | Skip pass drops every row where `brand_mentioned_in_source` is `false`. Default outreach type = `unlinked-mention-claim`. | | `Replace competitor links` | Skip pass drops every row not tagged `Links to competitor`. Default outreach type = `competitor-link-replacement`. | | `Topical authority links to specific URL` | No filter. Tier thresholds tighten (DR ≥ 50 for tier A). Default outreach type chosen per-row from `Why This Prospect`. | | `Maximum link volume from any relevant site` | No filter. Tier thresholds relax (DR ≥ 30 for tier A). Default outreach type chosen per-row. | | `Custom` | User-supplied paragraph; biases email tone and tier weights. No automatic skip filter. |

2. **Target keyword(s)** — one or more keywords the user wants their link to appear next to. The skill prospects the SERP for each. At least one required. 3. **Brand name** — the user's brand or product name. The Actor will not run without this (it is the `brand` input field). 4. **Product/category description** — one or two sentences describing what the user sells, who they sell to, and what category their product fits in. Example: *"Apify — web scraping platform that runs serverless scrapers as APIs. We sell to developers and data teams who need scraped data without managing infrastructure."* Required. Used in Step 6 (topical-fit gate) and Step 7 (adversarial-mention detection) to recognise prospects who are in the same product category — those won't link no matter the pitch. Without this, the skill cannot distinguish a genuine editor