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Research company

Skill jain777/jobclaw-skills/skills/research-company

Build a structured company × role brief — compensation, day-to-day, career growth, recent news, community sentiment (Reddit / Blind / Glassdoor), red flags, and a "fit for this user" view. Heavy reasoning — runs forked. Writes companies/<slug>.{md,json} sidecars consumed by prep-interview and coach-negotiation.From its SKILL.md

Install
npx -y skills add jain777/jobclaw-skills --skill research-company

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.8 KB, as published. Nobody here has run it

research-company

A 360° brief on a company × role, grounded in real sources — every claim cites a URL. Hard rules: ../_shared/RULES.md.

Inputs

  • company (required) — name or canonical key. Known-info gate (RULES §6): if not given inline, read jobs/current.json for company/role before asking.
  • role (optional but strongly recommended) — title at the target level.
  • Profile: profile/master-profile.md for the fit_for_user view (read context: for direction only; never echo).

Method (forked context — be liberal with WebSearch / WebFetch)

  1. Region pack. Read knowledge/regions/<code>.md — comp norms (USD base+equity vs INR LPA CTC fixed+variable) and which community sources to weight (Glassdoor.com vs Glassdoor.in, r/india for IN-only).

  2. Discovery sweep — site-restricted WebSearch queries (run a handful, don't be precious):

    • "<company>" compensation "<role>" levels.fyi OR teamblind OR glassdoor
    • "<company>" "<role>" "day-to-day" OR responsibilities OR "what we do"
    • "<company>" career growth OR promotion OR ladder OR "career path"
    • "<company>" news (last 12 months) — site:news.ycombinator.com OR site:techcrunch.com OR site:bloomberg.com OR site:theinformation.com

  3. Community sentiment. Up to 5 results each from:

    • Reddit — r/cscareerquestions, r/ExperiencedDevs, r/csMajors, r/recruitinghell, and r/india / r/developersIndia for IN.
    • Blind (teamblind.com) — when accessible.
    • Glassdoor (regional). Each = { content (≤ 20 words), link, source, date? }. WebFetch the promising ones; quote sparingly.

  4. News pass — WebSearch last-90-days news; surface 4–6 items with date + 1-line summary + link.

  5. Compose the report per reference/report-schema.md:

    • compensation — salaryBenchmarks.{baseSalary, totalCompensation} (verbatim source strings) + benefitsOverview[].
    • jobSummary.{jobDescriptionSummary[], dayToDayResponsibilities[], careerGrowthOpportunities[]} — 4–6 bullets each, drawn from sources (not invented).
    • news.recentNews[] — 4–6 items.
    • discussions.{reddit[], blind[], glassdoor[]} — what people who work there say. Honest: positive AND negative.
    • red_flags[] — 0–4 specific, sourced concerns. "Glassdoor 2.8 with consistent WLB complaints (link)"; "Two CFOs in 18 months (TechCrunch, 2026-03)". Skip if nothing material.
    • fit_for_user[] — 2–3 bullets each linking a profile fact to a company fact. Reads context: for direction; never echoes.

  6. Cite everything. Markdown report has links inline; JSON has explicit link / source fields per item, and a deduped sources[] at the root.

Output

  • companies/<slug>.md — human-readable; sections mirror the JSON; "Sources" footer lists every URL.
  • companies/<slug>.json — schema-compliant per reference/report-schema.md. Consumed by prep-interview, coach-negotiation.
  • Console: 5-line summary — comp band · growth signal · top red flag · top fit · next suggested skill (prep-interview if pre-interview, coach-negotiation if pre-offer).

Anti-patterns

  • Compensation ranges without a source. If none found, set to null; don't write "$180k–$220k" with no link backing it.
  • News older than 18 months (unless the user is researching a founding / legal / deal story).
  • Empty arrays filled with placeholder strings ("No information found"). Use [].
  • Echoing context.career_goal / context.additional_info into fit_for_user.
  • Pretending small samples are representative ("everyone on Blind says X" when there are 3 posts).
  • Emoji.

Rubric

  • Every claim in the markdown has a source URL.
  • salaryBenchmarks are verbatim from sources; if absent, null, not invented.
  • Sentiment is balanced (positive + negative) where both exist.
  • red_flags are specific and sourced (or absent).
  • fit_for_user cites both a profile fact and a company fact per bullet.
  • sources[] at root deduplicates every URL used.

Next steps

Brief saved. Next: /prep-interview (pre-interview) or /coach-negotiation (pre-offer).

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.