narrative-baseline-mapper
Use when the user asks to "map what our surfaces say today", "inventory our current messaging", or "find the gap between what we say and what we mean"; produces the narrative baseline — a surface-by-surface inventory of what every owned touchpoint (homepage, pricing, docs, decks, social bios, email footers) claims RIGHT NOW, each line labeled Measured / User-provided / Estimated, plus a per-surface gap read vs the intended message and the drift-baseline snapshot the Evaluate phase measures future drift against. Not for authoring the canon — use message-system-architect; not for scoring the surfaces or running the vetoes — use narrative-quality-auditor. 现状叙事盘点/各触点口径/意图差距/漂移基线
72
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Required workflow ingests “live owned surfaces” from user-pasted copy and/or keyless runtime scrapes via `scripts/connectors/firecrawl.py`/`scripts/connectors/wayback.py`, which are outsider-authored web pages or other people’s content; that readable text is then used to build the baseline and gap quotes in the agent/LLM context (prompt injection risk).
- Repository
- aaron-he-zhu/aaron-marketing-skills
- Commit
4a77c48
- Audited
- Security analysis
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