name: research-competitors-rival-pass description: >- Step of the research-competitors playbook: the worker brief for profiling one rival at a capped depth, returning a fixed-shape profile. Run research-competitors instead; not for direct use. version: 0.1.1

rival-pass — worker brief

You research one rival for one brand — or our own brand when the brief says so (then "openings" are our own events; skip "where we win"). The main run already chose the rivals and gave you the facts below.

Rules for this worker

• Don't load any skill or playbook, and don't start subagents or workflows. This brief is all you need. If a dimension needs more method, read only that section of ../research-competitors/references/rival-craft.md.
• Depth cap (standard run): about 12 web searches and 12 page fetches in total. Spend them by the company-type weighting below. A deep teardown (quarterly, or when asked) may double it. Stop a dimension when two reads add nothing new.
• Never stop to ask. Public pages only: never log in, sign up, use fake details, or use unofficial mirrors (the Wayback Machine is fine). Never check or repeat a claim about our brand that no source gave you.
• Every fact carries its link and date inline — the report quotes you directly. Say how sure you are in words ("confirmed", "likely", "a guess, because…").
• A page that needs the browser (ad libraries, X, LinkedIn posts, script-only pages, review pages that block fetch) goes on Needs the browser with the exact URL or search — never "none found".

Inputs you get: rival name and site · our brand, what it sells, its approved claims · the frame we compete in · the typical-buyer scenario for pricing · company type · today's date · the rival's last saved snapshot, if any (report what changed since).

Get these, in this order

1. News, last 90 days — 2–3 searches combining: shut down, acquired, raises, layoffs, pricing, launches, CEO. Anything in the last 30 days is a candidate opening, with the window it opens. Say exactly what happened: who bought what (company, or only assets and customers), who now serves the old customers, and on what offer.
2. Launches, last 90 days — changelog or blog; the biggest one's demo, broken into hook · setup · reveal · proof · CTA, labelled from video, from transcript only or from page text only.
3. Founder and exec posts — 1–2 people: site:linkedin.com/posts "<name>", site:x.com "<name>"; their repeated claims and teasers, linked — or "couldn't read (reason)".
4. Ads — Meta, LinkedIn, Google, TikTok libraries, by the advertiser's name: what you could read (top ads, start date, days running, hook) or "couldn't open (reason)" / "Needs the browser". Never spend, return on ad spend or "best ad" as fact.
5. Pricing — plans, price, the unit, free tier or trial, whether read on the vendor's page or third-hand; what a typical buyer like ours would pay a month (the scenario the brief gives you); which tier holds the features buyers care about; hidden costs.
6. Positioning — the homepage headline word for word, who it's for, the lead claims.
7. Buyers — at least one praise and one complaint, quoted verbatim with links, from more than one source where they exist (two review sites, or a review site plus Reddit or community); say which sites and how many you read. One site only (Trustpilot over-represents complaints) → say so. The praise is why their customers stay — never skip it.
8. Hiring, customers and search — open roles by team (one look at the careers page); named customers, logos on the customers page a year ago that are gone now (Wayback, ../research-competitors/references/rival-craft.md §6 for the efficient way), job posts asking for "experience with <rival>"; who ranks or advertises on "<rival> alternative".

Weighting by company type

| Type | Spend most on | Spend least on (still check once) | |---|---|---| | B2B SaaS | LinkedIn ads and posts, founder posts, reviews (G2/Capterra), pricing, launches, comparison searches | Meta, TikTok | | DTC / ecommerce | Meta and TikTok ads, creators, offers, Amazon/Trustpilot reviews | hiring, LinkedIn | | Consumer app | app-store reviews and rank, TikTok/Instagram ads, onboarding and paywall | LinkedIn | | Marketplace seller | listings, price and coupon history, review themes | founder posts, hiring | | Local business | Google Business reviews, local ads, offers | hiring, LinkedIn |

Return this, in this shape (about 400–600 words)

## <Rival> — as of <date>
What they are: <one line> · Frame: <the category they claim>
News (90 days): <dated items with links> · Candidate openings: <event — date — window, or "none">
Launches: <dated> · Biggest launch breakdown (<from video | transcript only | page text only>): hook · setup · reveal · proof · CTA
Founder posts: <name, role — claims and teasers with links> or "couldn't read (reason)"
Ads: Meta <…> · LinkedIn <…> · Google <…> · TikTok <…> — each read (count and what it counts — "active now" or "shown since <date>" — top ads, start dates, days) or "couldn't open (reason)"
Pricing: <plans, price, unit, trial> — <vendor page | third-hand>, <link, date> · a typical buyer pays: <$/month for the scenario> · tier for key features: <…> · hidden costs: <…>
Headline (word for word): "<…>" · for whom · lead claims
Buyers say: praise "<quote>" (<site, link, date>) · complaint "<quote>" (<site, link, date>) · sites read and n per site · main review site: count and rating
Hiring: <roles by team> · Customers: <named, each confirmed / likely / a guess, linked> · likely lost: <logos gone since a year ago> · Search: <who ranks or advertises on "<rival> alternative">
Where we win / where we lose: <points, each with how sure>
Needs the browser: <exact URLs or searches>
Couldn't read: <source — why — what it would change>
Snapshot for next time: <active ads per library + ad ids and start dates, entry price and typical-buyer cost, headline, open roles, review site + count + rating, launches in 90 days — each with its last-read date>