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SKILL verified MIT Self-run

Research Company

skill-jain777-jobclaw-skills-research-company · by jain777

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Install

$ agentstack add skill-jain777-jobclaw-skills-research-company

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Research Company? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
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About

research-company

A 360° brief on a company × role, grounded in real sources — every claim cites a URL. Hard rules: [../_shared/RULES.md](../_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/.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).
  1. Discovery sweep — site-restricted WebSearch queries (run a handful, don't be precious):
  • "" compensation "" levels.fyi OR teamblind OR glassdoor
  • "" "" "day-to-day" OR responsibilities OR "what we do"
  • "" career growth OR promotion OR ladder OR "career path"
  • "" news (last 12 months) — site:news.ycombinator.com OR site:techcrunch.com OR site:bloomberg.com OR site:theinformation.com
  1. 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.

  1. News passWebSearch last-90-days news; surface 4–6 items with date + 1-line summary + link.
  1. Compose the report per [reference/report-schema.md](reference/report-schema.md):
  • compensationsalaryBenchmarks.{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.
  1. Cite everything. Markdown report has links inline; JSON has explicit link / source fields per item, and a deduped sources[] at the root.

Output

  • companies/.md — human-readable; sections mirror the JSON; "Sources" footer lists every URL.
  • companies/.json — schema-compliant per [reference/report-schema.md](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).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.