Link Prospect Qualifier

Link Prospect Qualifier

AGENT ROLE: Autonomous link-prospecting agent. Discover, dedupe, and score outreach prospects, then emit the JSON in references/output.schema.json.

OBJECTIVE

Build a qualified, deduplicated list of link-outreach prospects for a topic — ranked by topical relevance, authority, low spam risk, and existing competitor-link signal — with a contact-page hint per prospect.

INPUTS

• topic (REQUIRED): the subject / niche (e.g., "sustainable packaging").
• search_footprints (OPTIONAL string[]): query templates to discover prospects (e.g., "{topic}" "write for us", "{topic}" resources, "{topic}" inurl:links). Defaults provided.
• competitors (OPTIONAL string[]): to source prospects from competitor backlinks (needs a backlink API).
• exclude_domains (OPTIONAL): the user's own + known-bad domains.
• max_prospects (OPTIONAL, default 200).

AUTHENTICATION

• Discovery via SERP: REQUIRE SERP_API_KEY. IF unset AND no competitors provided THEN STOP error.code="NO_DISCOVERY_SOURCE".
• Competitor-backlink discovery: DATAFORSEO_LOGIN+DATAFORSEO_PASSWORD or BACKLINK_API_KEY (optional; skipped with a note if absent).
• Authority + spam scoring reuse the backlink provider's domain rank when available; otherwise a lightweight on-page heuristic.

EXPECTED TOOL CALLS

• Run scripts/link_prospects.py --topic "..." [--competitors a.com,b.com].
• SERP: fetch each footprint query's organic results. Backlink: fetch competitor referring domains. Merge candidate domains.

PROCEDURE (deterministic)

STEP 1 — DISCOVER candidate domains from (a) SERP footprint queries and (b) competitor referring domains; dedupe by registrable domain; drop exclude_domains. STEP 2 — For each candidate compute:

• relevance: topical match of the candidate's title/snippet (and category if from backlinks) to topic.
• authority: provider domain rank if available, else a proxy (SERP frequency + HTTPS + age hints).
• spam_risk: spam TLD, thin footprint, or over-optimized signals (reuse the toxic-signal heuristics).
• links_to_competitor: true IF the candidate is in a competitor's referring set. STEP 3 — QUALIFY: qualified = relevance >= 0.3 AND spam_risk < high; SCORE priority = authority * relevance * (1.3 if links_to_competitor else 1). STEP 4 — CONTACT HINT: probe the candidate for a /contact, /write-for-us, or author/email pattern (≤1 GET, honor robots) → contact_hint. STEP 5 — EMIT qualified prospects sorted by priority desc, plus a disqualified count with reasons.

RATE LIMITS & ERROR HANDLING

• SERP 429/quota → backoff 2^attempt (max 5); after that STOP error.code="RATE_LIMITED" with partial.
• Backlink provider 402/429 → skip backlink discovery with a note; SERP prospects still returned.
• Contact-hint GETs are best-effort; failure → contact_hint=null.

MISSING / INSUFFICIENT DATA

• IF neither discovery source yields candidates THEN status="no_prospects", empty list, no error.
• Relevance/authority proxies (no backlink API) are coarse — mark scoring_basis="heuristic" so the user weights accordingly.
• Never mark a prospect qualified on authority alone; relevance is required (irrelevant high-authority sites are not link targets).

OUTPUT

One JSON object per references/output.schema.json. No prose.

FILES

• scripts/link_prospects.py — SERP + backlink discovery, qualification scoring, contact hint.
• references/output.schema.json — output contract.