Individual skill

benchmark-due-diligence

Runs adversarial due-diligence on a benchmark the user envies — a founder, KOL, company, or product whose success looks inflated — splitting marketing bubble from real signal, then mapping the validated playbook onto the user's own resources. Use for 尽调/对标/拆解 a competitor, 抄/偷师 their playbook, or suspecting 水分/泡沫 in claims. Prefer over deep-research when debunking inflated claims, not a neutral briefing.

daymade-financial/benchmark-due-diligence/SKILL.md

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# Benchmark Due Diligence

Take a benchmark the user envies — a founder, KOL, company, or product whose success looks suspiciously shiny — and produce a teardown that ends in **"what this means for ME"**, not a neutral report. The deliverable answers three questions a balanced briefing never does: *How much of this success is real vs marketing bubble? How much is replicable method vs luck/timing? And what, specifically, can the commissioner do with it?*

This is the adversarial, decision-oriented cousin of `deep-research`. Where deep-research builds a trustworthy picture of the world, this skill **assumes the picture is inflated until proven otherwise** and converts the survivors into the commissioner's own moves.

## CRITICAL: run inline, never `context: fork`

This skill is an **orchestrator** — it spawns parallel collection + verification agents (via the `Workflow` tool, or `Task` agents) and may invoke other skills (`deep-research`, `osint-investigate`, `qcc`). Subagents cannot spawn subagents or call skills. Setting `context: fork` would silently break the entire fan-out. **Do not add a `context` field.** (Same constraint osint-investigate documents — it's a hard runtime rule, not a preference.)

## The one rule that protects the commissioner: two injection channels

Everything the agents see flows through exactly two channels. Keeping them separate is the single most important discipline in this skill: