business-edgeUse when a business needs end-to-end analysis and a strategy, not a single-domain fix — "how do we grow", "audit my business", "why aren't we selling", "what should we do next", "review our website and marketing", "find our gaps". Runs a phased engagement — scope, scan, diagnose, position, plan, dispatch, measure — that analyses a business across all dimens…
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The analyst-and-mentor layer. It diagnoses a business, decides what matters, and hands specific work to specialists. It does not do the specialist work itself.
Boundary. This skill produces analysis, strategy and a dispatched action list. The actual changes are made by the specialist skills in §6 and executed by
bob. If you find yourself writing schema markup or CSS here, you have left your lane.
P0 SCOPE ─► P1 SCAN ─► P2 DIAGNOSE ─► P3 POSITION ─► P4 PLAN ─► P5 DISPATCH ─► P6 MEASURE ─► P7 LEDGER
Each phase has a required output. Do not skip forward — P3 without P2 produces generic advice, which is the failure this skill exists to prevent.
Roles are data, not skills: roster/*.yaml. Load the relevant role's card when working its
phase. Seven roles, zero additional SKILL.md files.
Establish what the business is and how it makes money. Fifteen minutes here prevents a whole engagement of wrong-denominated advice.
| Question | Why it changes everything |
|---|---|
| How is profit earned per sale? % margin · fixed fee per unit · subscription · blended | A fixed fee detaches profit from price — AOV becomes a vanity metric and premium-mix advice becomes worthless |
| Gross profit per order, in currency | The only number that prices any proposed action |
| Channel fee load (marketplace %, payment %, financing %) | A 12.8% marketplace fee on a high-ticket item can exceed a fixed per-unit profit — making those sales value-destroying |
| Orders per month | Decides whether experiments are statistically possible at all (§7.1) |
| Category paid CAC (estimate is fine) | Affordability ratio = GP-per-order ÷ CAC. Below ~1.5 the paid auction is foreclosed and non-auction distribution is the only distribution |
Record every figure as measured / operator-stated / estimated. State assumptions inline and flag the most load-bearing one.
Flagging an assumption does not license concluding from it (S074). Before stating any directional recommendation, re-run it at the plausible range of every assumed input. If the direction flips anywhere in that range, you do not have a recommendation — you have an open question, and it must be reported as one.
This is not hypothetical. A real engagement assumed a 15% gross margin, correctly flagged it as the single most load-bearing assumption, and still concluded "paid advertising is arithmetically foreclosed" — a conclusion that reverses at 25%. The assumption was labelled and the conclusion was stated anyway, which is how a flag becomes decoration.
UNGROUNDED — direction depends on an assumed input
claim: paid acquisition is foreclosed
hinges on: gross margin (ASSUMED 15%, never measured)
flips at: ~20%
to resolve: one COGS figure from the operator
Report it in that shape. UNGROUNDED is a first-class outcome, never a weaker PASS: it names the
one number that would settle the question, which is far more useful to an operator than a confident
answer derived from a guess. Only an input recorded as measured can carry a directional claim on
its own.
Goal and time horizon · constraints (budget, operator hours/week, technical capability) · what has already been tried · the competitor set · what the operator believes is true (to be tested, not assumed).
Spawn the scout agent for the off-site half — it owns surface intelligence and enforces the
probe rules. Browser-first; APIs are a fallback, never the sole source. Record probe status on every
probe via scripts/probe_ledger.py, and run probe_ledger.py coverage before writing any finding.
Full method: references/probe-protocol.md.
scoutreports what exists and what could not be seen. It does not diagnose or recommend — it hands the surface map back here, where P2 owns diagnosis.
Dimensions — sweep all, mark NOT_PROBED explicitly where skipped:
| Dimension | Look for | |
|---|---|---|
| 1 | Offer & positioning | What is sold, to whom, at what price, vs whom |
| 2 | Catalogue integrity | Wrong/missing category-defining attributes, unclear variants, comparability |
| 3 | Pricing & fee load | §2.1 |
| 4 | Discovery | Organic, AI answers (ChatGPT/Gemini/Perplexity/Copilot/AIO), communities, marketplaces, social, referral |
| 5 | Selection | Comparison support, spec clarity, configurator, the verification path (§5.3) |
| 6 | Purchase | Checkout, payment methods, wallets, financing, failure/decline rates |
| 7 | After-sales | Delivery, support, warranty, returns, review capture, repeat/referral |
| 8 | Content & presence | What exists, what gets read, what gets cited |
| 9 | Brand/entity footprint | Third-party corroboration, review platforms, marketplace history |
| 10 | Technical site health | Speed, mobile, crawlability, structured data |
| 11 | Measurement | Attribution coverage, unattributed share, instrumentation gaps |
| 12 | Compliance | Regulatory exposure for the category |
Also scan what AI says about the business. Ask the major assistants the buying questions a real customer would, and record the answer and its cited sources. The AI's brand summary is now a public artifact the operator does not control and often has never read — it frequently contains their defects verbatim.
Most audits only find faults. That is a defect: the thing worth compounding is usually already working and invisible on a gap list. Name each strength, why it exists, and whether a competitor could copy it. Founder-level expertise, response speed, and genuine technical specificity are routinely the most valuable and most under-used assets a small operator has.
Mine real objections from calls, reviews, community threads, support tickets, configurator drop-off and abandonment — not from keyword tools, which only see demand that already exists. For each: is it resolved anywhere a buyer or an AI can find, and who custodies that resolution (you, or a third party)?
Map every finding to found → selecting → buying → after-sales, then identify the binding constraint — the one stage where fixing anything else changes nothing. Say which it is and why.
An action qualifies as edge only if a larger competitor cannot easily copy it — usually for organisational or economic reasons rather than technical ones. Incumbents can copy any tactic; what they cannot do is justify small, specific, unscalable work.
Test each candidate: could a competitor with 50× the budget do this tomorrow? If yes, it is hygiene — do it if cheap, but never call it strategy.
Structurally asymmetric for a small operator: publishing verifiable operational specifics · correcting a defect publicly and fast · genuine named-expert participation · direct human access at the moment of doubt · learning latency (days, not quarterly cycles) · owning narrow segments an incumbent finds economically trivial.
Commodity theatre — reject by default: generic content calendars · "get more reviews" as strategy · schema markup as a moat · posting-frequency retainers · dashboards with no intervention attached · cosmetic CRO while speed/clarity/payment are broken · paid retargeting labelled as edge.
Creating an artifact is legitimate. Manufacturing apparent independence is not. Required: identity and commercial relationship disclosed where the answer appears · a real pre-existing question · falsifiable claims backed by records · first-party statements clearly separated from independent corroboration · correction when facts change · standalone usefulness even if no AI ever retrieves it.
Prohibited: fake personas · planted questions · undisclosed compensation · vote rings · fabricated customers · presenting the operator's own claims as community consensus. Beyond the ethics: fake signals are removed and take their citations with them, so the tactic is self-erasing.
Design what happens when a prospect leaves to check whether the business is real. Route them to records the operator does not control — marketplace transaction history, independent review platforms, company registration, dated evidence. Third-party custody is what makes a claim credible to both humans and retrieval systems; a policy page on your own domain is not corroboration.
Every action gets: owner skill · effort · expected effect in PROFIT terms · evidence grade · kill criterion. Rank by (profit impact ÷ operator-hours), never by revenue.
| Action concerns | Route to |
|---|---|
| AI-answer visibility, citation, crawler policy, feeds | ai-search-optimizer |
| Schema, site architecture, internal linking, Core Web Vitals | seo-structure-architect |
| Keywords, content strategy, topical coverage, decay | seo-content-strategist |
| Titles, meta, SERP presentation | seo-meta-optimizer |
| Off-site authority, entity building | seo-authority-builder |
| GSC/GA4/Clarity analysis, measurement design | seo-data-analyst |
| Agent transaction, ACP/AP2, agent-readable feeds | agentic-commerce-readiness |
| Page/journey UX, layout, information architecture | audience-experience-design |
| Built-interface usability + accessibility review | ux-reviewer |
| Persuasion, trust signals, pricing presentation | conversion-psychology |
| Category/PDP/cart/checkout content and structure | ecommerce-growth |
| A/B tests, GA4 events, statistical validity | ecommerce-cro-experimentation |
| WooCommerce/WordPress implementation | woocommerce-developer, wordpress-developer |
| Faceted navigation / filtering | woocommerce-faceted-navigation |
| Written content production | content-writer, human-voice-writing |
| Front-end implementation | modern-frontend |
| Multi-file execution of an approved plan | bob (via forge for anything architectural) |
If no specialist owns an action, say so explicitly and file it as a library gap. Do not silently absorb specialist work into this skill — that is how a 240-line generalist ends up owning five domains it cannot maintain.
Compute what the order volume can actually detect. At single-digit orders per month, order-level A/B testing is impossible — a two-arm conversion test can need years per arm. Saying so is mandatory; proposing a test that cannot conclude is a serious error.
When order volume is too low, move the measurement unit up the funnel to something with hundreds of observations per month — AI-answer composition, citation presence, impressions, quote requests. Orders remain ground truth for profit; they are simply unusable for significance.
Track exposure → visit → enquiry → order → profit after channel fees → returns. Where a large share of sales is untagged, the cheapest fix is a post-purchase "how did you first hear about us?" — zero-party data, and the only instrument that sees zero-click discovery.
Record every action, its prediction, its result — including nulls and adverse effects — and its evidence grade. Promote a method only on replication:
conjecture → single-entity signal → replicated entity result → cross-category pattern
Failed methods stay recorded with their failure evidence rather than being deleted, otherwise the library forgets what does not work and proposes it again.
The same decay applies to this skill family. scripts/claims_lint.py finds a fact owned by several
skills whose verdicts disagree — the state that precedes a confidently wrong recommendation:
python3 ~/.claude/skills/business-edge/scripts/claims_lint.py drift --show-duplicates
python3 ~/.claude/skills/_meta/gates.py G_CLAIM_FRESHNESS --claim-mode strict # exit 2 on drift
Duplication alone is reported, never blocking; contradiction blocks in strict mode. Run it after any change to a fast-moving claim. A contested fact needs one owner; the rest point at it.
| Don't | Why it hurts |
|---|---|
| Report "no presence found" after a blocked or failed probe | Fabricates a negative finding. This has already happened once |
| Give revenue-denominated advice before knowing the profit model | Under a fixed per-unit fee, AOV and premium-mix advice is worthless |
| Recommend paid acquisition without the affordability ratio | Below ~1.5 GP-per-order ÷ CAC the auction is unwinnable by arithmetic |
| Propose an A/B test at single-digit monthly orders | It cannot conclude. Move the measurement unit up the funnel |
| Skip P2 and jump to recommendations | Produces the generic playbook every competitor already has |
| Only list gaps | Strengths are the compounding assets; a fault list misses them |
| Present a conjecture as best practice | n=1 is not evidence. Grade it and test it |
| Do the specialist work inside this skill | Creates an unmaintainable generalist and orphans the real owner |
| Propose seeded "independent" endorsement | Astroturfing. Self-erasing and reputationally fatal |
| Optimise a metric the profit model ignores | The most expensive error available here |