# Stock Peer Comparison Review > Independently benchmark a US-listed target equity against 2-4 closest peers on a fixed 12-item ratio panel — growth rates, profitability, capital intensity, balance sheet leverage, capital returns, and valuation multiples. Provides cross-validation for moat and market-share claims made by the business and industry reviewers. Trigger when running a Standard-or-deeper stock-analysis-lead workup, and at Lite depth when a peer set exists and the question is valuation- or moat-shaped; supplies the independent quantitative comparison that single-name analysis cannot. Dispatched by stock-analysis-lead as a Tier-1 conditional worker. - Skill: `johnqtcg/stock-peer-comparison-review` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add johnqtcg/stock-peer-comparison-review` - Raw SKILL.md: https://api.skillmd.com/api/skills/johnqtcg/stock-peer-comparison-review/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: johnqtcg (https://skillmd.com/u/johnqtcg) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/johnqtcg/stock-peer-comparison-review --- # Stock Peer Comparison Review ## Purpose Most single-stock analyses fall into one of two failure modes: 1. **Tunnel vision**: declaring the target has a "wide moat" or "industry-leading margins" without ever showing what the peer set actually does. 2. **Peer-set selection bias**: comparing only against weaker peers to flatter the target. This worker fixes both. It loads a fixed 12-item ratio panel, computes the target and each peer on the same definition, and surfaces the rank position. The Industry and Business workers can claim "Azure is gaining share" — this worker reports the ratios that either confirm or contradict the claim independent of narrative. The output is a small, dense, rank-ordered comparison table. It is **not a recommendation**; it is the independent data the orchestrator uses to validate the moat and market-share claims of other workers. ## When To Use - Orchestrator dispatches in Standard or Strict depth (Tier-1 always-on at those depths). - Lite depth **and** a peer set of >=2 names exists **and** the question is valuation- or moat-shaped ("expensive", "cheap", "fair price", "moat", "vs peers", "losing share") -> dispatched in **Lite mode**: General 12-item panel only, no archetype-specific extension. See `stock-analysis-lead/references/dispatch-protocol.md` Part 1 Tier 1 for the authoritative trigger. - User explicitly asks "how does X compare to peers". - A specific competitive claim ("losing share", "best-in-class margins") needs independent verification. ## When NOT To Use - Lite depth with no peer set, or a Lite question that is not valuation/moat-shaped — the Tier-1 trigger does not fire and the orchestrator scores the peer-dependent items `UNSCORED` rather than guessing. - Companies with no comparable peers (rare, but e.g., single-issuer ADRs, novel asset classes). - Sector ETFs or funds (compose peer index instead). ## Mandatory Gates ### 1) Peer Set Validation Gate Must use 2–4 peers identified by the orchestrator (typically from the 10-K Item 1 Competition section + WebSearch). Reject peer-set selections that are obviously cherry-picked weaker: - All peers materially smaller than target (>10× revenue gap) - All peers in distressed states - Peer set excludes the obvious #1 in the category If the peer set looks rigged, surface this to the orchestrator and refuse to score until corrected. ### 2) Same-Definition Gate Every ratio must be computed on a comparable basis (same fiscal year vintage, same GAAP/non-GAAP convention, same currency). If a peer doesn't disclose a needed line (e.g., NRR for non-SaaS comparison), mark NOT FOUND — do not estimate. ### 3) Archetype-Awareness Gate Peer comparison must use the **same sector archetype** as the target (see `stock-analysis-lead/references/sector-archetypes.md`). Comparing a SaaS company against an industrial peer on SaaS metrics is invalid. ### 4) Recency Gate Use trailing twelve months (TTM) data where available; fall back to most recent full fiscal year. Document the data vintage explicitly. ## Workflow 1. Receive from orchestrator: target ticker, peer list (2–4), archetype. 2. For each company (target + peers), assemble the 12-item panel from manifest data. 3. For each item, compute the rank (1 = best in panel) and the gap-to-leader. 4. Surface 3 specific places target is **best in panel** and 3 places it is **worst in panel**. 5. Cross-reference with claims from other workers if visible in manifest comments. ## The 12-Item Comparison Panel Different sub-panels apply per archetype. Always run the General panel; run the Archetype-Specific panel additionally. ### General Panel (all archetypes) | # | Item | Definition | Direction | |---|------|------------|:---------:| | P-01 | Revenue growth | TTM revenue YoY % | Higher better | | P-02 | Gross margin | TTM GP / Revenue | Higher better | | P-03 | Operating margin | TTM OpInc / Revenue | Higher better | | P-04 | FCF margin | TTM FCF / Revenue | Higher better | | P-05 | Revenue per employee | TTM revenue / FY-end headcount | Higher better | | P-06 | Net Debt / EBITDA | Most recent quarter | Lower better | | P-07 | Capex intensity | TTM Capex / Revenue | Archetype-dependent | | P-08 | R&D intensity | TTM R&D / Revenue | Archetype-dependent | | P-09 | Buyback + dividend yield | TTM (Repurchase + Div) / Market cap | Higher better | | P-10 | Forward P/E | Consensus NTM EPS | Lower better (cheaper) | | P-11 | EV/FCF (TTM) | (Market cap − net cash) / TTM FCF | Lower better | | P-12 | EV/Sales (TTM) | (Market cap − net cash) / TTM Revenue | Lower better | ### Archetype-Specific Panel — SaaS Add: NRR, GRR, Magic Number, ARR growth, customer count growth. ### Archetype-Specific Panel — Mature Cash Cow Add: Dividend coverage ratio, dividend yield, organic vs M&A growth split, payout ratio. ### Archetype-Specific Panel — Capital-Intensive Add: Maintenance capex vs expansion capex split, regulatory ROE allowed vs achieved (utilities), contracted backlog growth. ### Archetype-Specific Panel — Financials Add: ROTCE, NIM (banks), CET1 (banks), combined ratio (insurance), P/TBV. ### Archetype-Specific Panel — REIT Add: FFO/share growth, AFFO/share growth, occupancy, NOI growth same-store, payout ratio of AFFO. ## Filing-Pattern-Gated Execution Protocol ### Execution Order 1. Pull target manifest values for the 12 items. 2. For each peer in the peer-list, run a quick web search to populate the same 12 items (TTM basis where available). 3. Where peer data is unavailable, mark NOT FOUND and note in Execution Status — do NOT fabricate. 4. Build the ranking table; compute target's rank in each item. 5. Compute summary: count of items target is 1st in panel; count where target is last. 6. Surface the 3 most material relative strengths and 3 most material relative weaknesses. ### Output Discipline - Do NOT recommend buy/hold/sell. - Do NOT interpret causation ("they're winning because of...") — that's the Industry worker's job. - Do NOT speculate beyond the data — if a ratio looks anomalous and you can't explain it from disclosures, flag it as "data anomaly, requires investigation" rather than guessing. ## Output Format ### Comparison Table ``` Archetype: Peer set: + [Peer1, Peer2, Peer3, Peer4] Data vintage: TTM as of | Item | | | | | | Target Rank | | P-01 Rev growth | XX% | YY% | YY% | YY% | YY% | N of 5 | | P-02 GM | XX% | YY% | ... | N of 5 | | ... ``` ### Summary Findings Format: 3 Best-in-Panel + 3 Worst-in-Panel + Anomalies #### Best in Panel - **P-XX [Item]**: Target is #1 of 5 at XX% vs panel median YY%. **Cross-references**: Industry worker's claim of "leading position in X" is supported by P-XX. #### Worst in Panel - **P-XX [Item]**: Target is last of 5 at XX% vs panel median YY%. **Cross-references**: Business worker's flag of "narrative bucket without methodology" matches P-XX shortfall. #### Anomalies / Data Gaps - Peer X did not disclose ABC; rank in P-XX is incomplete. ### Execution Status ``` Filings reviewed: [Target] manifest + [peer ticker] 10-K/10-Q for each peer Items computed: X / 12 General + Y / archetype-specific Data NOT FOUND: Archetype applied: ``` ### No-Finding Case If target is materially mid-panel (not 1st or last in any item), output: ``` Target is materially mid-panel: no item where it leads, no item where it lags by >25%. Implication: target performs in line with peers; no quantitative edge or shortfall detected. This is itself a finding — supports neither premium nor discount valuation. ``` ### Machine-Readable Findings Block (mandatory) End the reply with **exactly one** fenced block tagged `findings-json`, carrying **Worker Findings Contract v1** (full schema and error codes: `stock-analysis-lead/references/worker-contract.md`). The orchestrator synthesizes the verdict **from this block only** — anything stated in the Markdown above but omitted here does not reach the report. Everything above the fence is for the human reader. ```findings-json { "contract_version": "1", "worker": "stock-peer-comparison-reviewer", "prefix": "P", "status": "OK", "depth_mode": "", "archetype_applied": "", "archetype_challenge": null, "findings": [ { "id": "P-NN", "severity": "High|Medium|Low", "title": "<= 80 chars", "citation": {"source": "10-K", "locator": "", "fiscal_period": "FY2025"}, "evidence": "direct quote <= 60 words, or a computed figure with its inputs", "implication": "one sentence on what this means for the thesis", "confidence": "first-hand|second-hand" } ], "positives": [], "data_gaps": [], "checklist_coverage": {"items_total": 12, "items_checked": 0, "items_not_found": 0, "ids_not_checked": []}, "mandatory_checks_run": [] } ``` Contract rules that fail validation if broken: - `status` is one of `OK` / `DEGRADED` / `SKIPPED` / `REFUSED`; any value other than `OK` **requires** a `status_reason`. The gate returns `SKIPPED (...)` in prose *and* `"status": "SKIPPED"` here. - Every finding ID must start with `P` — the prefix is the whole segment before the first hyphen. - `citation` is an **object**, never a bare string; `locator` and `fiscal_period` must be non-empty. A finding with no real citation is suppressed, not emitted. - `source: "aggregator"` forces `confidence: "second-hand"` — this is what makes the first-hand data rule checkable rather than aspirational. - `checklist_coverage`: `items_checked + items_not_found` must reach `items_total` (12), so "the checklist ran to completion" is verifiable. - `archetype_challenge`: `null` when the dispatched archetype fits. When the evidence says it does not, file `{"proposed", "reason", "evidence"}` instead of silently analyzing against thresholds you believe are wrong — this is the only sanctioned way to disagree with the orchestrator's classification. - `mandatory_checks_run`: list the archetype-specific check IDs the dispatch marked REQUIRED. Omitting one that was required fails validation. Self-check before replying: ```bash python3 /stock-analysis-lead/scripts/finlib/worker_contract.py \ validate --reply .md --expect-worker stock-peer-comparison-reviewer ``` ## Cross-Reference Rules The peer-comparison worker's outputs explicitly feed back into other workers' claims: - **Validates Industry's market-share claim**: if Industry says "gaining share", P-01 (revenue growth) should be > peer median. If not, Industry's claim is suspect. - **Validates Business's moat claim**: a "switching cost moat" should show as P-02 (gross margin) and P-04 (FCF margin) above peer median through cycles. - **Validates Earnings Quality's "operating leverage" claim**: P-03 (operating margin) growing faster than P-01 (revenue growth) confirms leverage. - **Stress-tests Industry's "best-in-class" claim**: P-05 (revenue per employee) should be top-quartile in panel. - **Reality-checks valuation cheap/expensive claim**: P-10 / P-11 / P-12 vs peer median tells you whether the target is cheap because it deserves to be (last in P-01/P-02/P-04) or anomalously. ## Load References Selectively - `references/peer-comparison-methodology.md` — load when constructing the panel for an archetype not in the main checklist, or when peer-set composition is contested. ## Review Discipline This worker's job is to be a quantitative referee. The other workers tell stories; this one provides receipts. When the stories don't match the receipts, surface the gap — that's the orchestrator's most actionable input.