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Competitor Researcher

Sai cosa stanno facendo i tuoi concorrenti, in un unico report.

Sorveglia i siti e gli annunci di lavoro dei tuoi concorrenti, confronta con la volta precedente e ti consegna un brief di una pagina con le prove.

Anteprima di Competitor Researcher
Ideale per
Founder, PM, marketer
Tempo necessario
Configurazione ~15 min, poi ogni settimana
Livello
Adatto ai principianti

Installala in 3 passaggi

Nessuna registrazione. Nessuno strumento da riga di comando. Scegli la tua AI, copia una riga e incollala.

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Prove dal mondo reale

Persone vere hanno svolto proprio questo lavoro con agenti IA.

Cosa contiene

Un file SKILL.md (la guida operativa) + un modello di partenza. Un'anteprima:

Competitor Researcher

When to use

  • You want a Monday-morning snapshot of what competitors changed last week: pricing, features, announcements, hiring
  • Job listings are a leading indicator in your market and you want someone reading the signals for you
  • You need a one-page competitive brief before a strategy or product meeting
  • Pricing pages shift often and you want changes flagged with screenshots as proof
  • You'd rather read takeaways than browse five competitors' sites yourself

Workflow

  1. Set the watch list (input: competitor names → output: watch list + signals)
    Name 3–7 competitors and what to watch on each site: pricing page, changelog, announcements, careers page. Be specific per site — "keep an eye on Acme" is not a spec.
  2. Fetch on schedule (input: watch list → output: snapshots + screenshots)
    On your chosen cadence (the classic is Monday 8am), visit each site, record starting prices and core features, and capture homepage screenshots. Read-only: never submit forms, never apply for jobs, never create accounts.
  3. Diff against last time (input: this week's snapshots + last week's → output: change list)
    Compare and list only what changed. No change means no entry. This step is what makes the brief worth reading — a dump of everything is not intelligence.
  4. Read the hiring signals (input: new job postings → output: inferred intentions)
    Read new job descriptions and infer what each hire implies about product direction. Label every inference as inference, not fact — a JD is a signal, not an announcement.
  5. Write the one-page brief (input: change list + signals → output: brief)
    One page: changes summary, the single most important item, and three takeaways for your team. Every claim links to a screenshot or page with a capture date. Anything inferred is labeled as such.

Output spec

  • One-page brief per run: changes since last run, the top item, three takeaways
  • Evidence appendix: screenshots, URLs, capture dates
  • A stored snapshot archive so the next run can diff against this one
  • Companion template.md skeleton — fill in the blanks and use it

Good vs. bad examples

Anteprima del modello

Competitor Researcher — Weekly Brief Template

One run = one brief. Run on your cadence (classic: Monday 8am), diff against last week.

Run — {date}

Watch list: {competitor names, 3–7}

Snapshots & screenshots

*Read-only only: no signups, no form submissions, no fake demo requests.*

What changed since {last run date}

*No change = no row.*

Hiring signals (inference — label everything)

*Reminder: a JD is a signal, not an announcement. Never state inference as fact.*

One-page brief

The single most important item: {one sentence}

Top takeaways for our team:

  1. {takeaway + what we should do}
  2. {…}
  3. {…}

Il pacchetto della skill (SKILL.md + modello) è scritto in inglese.

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