Peer Readacross
Compare two tickers and surface the cross-read between them using the AlphaAI MCP. Use when the user asks to "compare X and Y", "NVDA vs AMD", "what does <peer>'s news mean for <ticker>", or wants the read-across between two related names (competitors, supplier/customer, same theme).
Install
$ agentstack add skill-makeev-alphai-claude-skills-peer-readacross ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-makeev-alphai-claude-skills-peer-readacross) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
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 →About
Peer read-across
When two names are linked — competitors, a supplier and its customer, two plays on one theme — the interesting signal is the read-across: a peer's print that resets the other's setup. alphai_pair_analysis is built for exactly this.
Steps
- Resolve both tickers. If given company names, map them with
alphai_tickers(q=...). Any symbol that isn't a recognized active ticker comes back in unknown_tickers and contributes no rows — surface that.
- Run the comparison. Call
alphai_pair_analysis(ticker_a, ticker_b). It
returns three things: news naming both companies (the shared read-across), plus each ticker's own recent news for context.
- Tighten on request. Raise
min_relevance(default 4) for only the
strongest items, or limit for more rows per list.
Output
- Shared story — the news naming both names: what links them right now and
which way the read-across cuts (does A's news help or hurt B?).
- {Ticker A} — 2–3 of its own top stories, one-liners.
- {Ticker B} — same.
- Net read — one or two sentences: are they moving together or diverging, and
what's the single linking factor (a shared customer, a sector catalyst, a head-to-head product)?
Guardrails
- If
alphai_pair_analysisreturns no shared rows, say so — the two names may
simply not be in the same story flow right now; fall back to summarizing each side's own news rather than forcing a connection.
- Lead with
relevance_score. - Describe the read-across the reporting supports; don't manufacture a causal
link. News, not advice.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: makeev
- Source: makeev/alphai-claude-skills
- License: MIT
- Homepage: https://alphai.io/mcp
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.