Competitor Analysis (what customers actually say)

Map the competitive landscape — but weight it by the customers' own words, not a feature spec sheet. The sharpest competitive intelligence isn't "Competitor X has feature Y"; it's a prospect saying why they picked or dropped a rival. This skill cross-checks the internal competitor data against real customer mentions and win/loss quotes.

Step 0 — Relevance & availability

Confirm this is competitive/market work and Evermuse is connected (see using-evermuse Step 0). If disconnected, produce the framework labeled ⚠ ungrounded and tell the user to authorize the MCP.

Evermuse Grounding (required)

Follow ${CLAUDE_PLUGIN_ROOT}/skills/using-evermuse/SKILL.md.

Required — one parallel batch of searches. Verify the product (Rule 1), then fire in a single parallel batch:

• 3–4 evidence searches, each worded from a different angle (limit up to 50). Evidence comes back rich and varied — expect large, useful result sets.
• one guidance search and one context search (limit up to 50). These are usually sparse or empty; run them anyway and note when they're thin.

Read each response's digest — it reports how many more results exist. Use judgment on whether a query is worth pulling deeper (raise limit toward the 100 max and/or page with next_offset to avoid repeats), weighing payload size, remaining context, task complexity, and the value of the data. For deep pulls, consider spawning sub-agents — instruct them to return every citation with the same metadata the tools return (url, who_said_it, meeting_name, created_at) so you can still cite.

Optional — considered use. Once grounded, reach for the other tools only when they add value: a quote-angled search for verbatim voice, read_source for a single deep dive, inline citations (references/citations.md), and add_source to save the deliverable. Sources, citations, and saving are optional — not required.

Instructions

Analyze the competitive landscape for $ARGUMENTS.

1. Scope the market and assemble the competitor set: start from list_competitors, then add any rival that customers actually name in the corpus (evidence often surfaces competitors the DB misses — that's a finding).
2. For each competitor, build the profile below, and for every strength/weakness claim mark its source: [customer] (a real mention, badged), [competitor DB] (secondary, unverified), or [market] (external).
3. Reconcile. Where the competitor DB and customers disagree, trust the customers and say so.
4. Find the differentiation openings — the unmet needs and switching pains customers voice that no competitor solves well.

Per-competitor profile

Profile — focus, segments served, positioning, stage [market].

Strengths — what wins them deals. Prefer customer reasons:

> "We went with [competitor] because [reason]" — [Name], [Meeting], [Date] [`1`](LINK)

Weaknesses & gaps — where customers are frustrated or churned away from them, badged. Add [competitor DB] capability gaps as secondary.

Pricing / model — [market], cite source.

Threat & win/loss pattern — how they threaten us; the recurring reason we win or lose against them, from real deals.

Differentiation opportunities (the payoff)

A ranked list of openings — each an unmet need or switching pain customers voiced that we could own — badged with the quote that proves it.

Close with a competitive positioning recommendation (differentiators to emphasize, segments to target, threats to monitor), keeping customer evidence visibly separate from competitor-DB and market sources. This feeds /evermuse:market-sizing (wedge) and positioning work.

Further reading

• Competitive-analysis structure adapted from phuryn/pm-skills (MIT); customer cross-check is Evermuse-native.