feat(skill): add "Setting the narrative?" lens for company/product topics

Comparison tables gain a narrative axis judging whether each entity's
community conversation is about what the entity pitches or about
something else (pricing, rivals, an incident). Backed by a new
mandatory Step 0.55 research item that fetches each entity's CURRENT
first-party positioning (RESOLVED_POSITIONING) instead of relying on
memory, and a narrative-check synthesis beat for single-entity company
runs. The mismatch is the signal: companies usually don't control
their own conversation.

skills/last30days/SKILL.md

@@ -641,9 +641,11 @@ Topic A (the main topic, first in the vs-string) uses outer `--x-handle`, `--x-r
 
 **Then do WebSearch supplements** for: `{TOPIC_A} vs {TOPIC_B} comparison {YEAR}` and `{TOPIC_A} vs {TOPIC_B} which is better` — these catch rivalry articles that per-entity passes might not surface.
 
+**Fill the `Setting the narrative?` row using `RESOLVED_POSITIONING` + the community evidence.** Run Step 0.55 item 6 (first-party positioning) per entity - it gives you each entity's CURRENT stated pitch, fetched fresh, not from memory. Then judge: is the community conversation actually ABOUT what the entity pitches, or about something else (pricing, rivals, an incident, a ToS change)? Start the cell with **Yes / Partly / No / Unclear**, then name the topic the community is really on, anchored to a real item with its engagement (e.g. "No - pitches uptime, but the top thread is friendly-fraud, 323pt HN"). The mismatch is the signal: companies usually don't control their own conversation. Use **Unclear** when the evidence is thin or polluted with unrelated brand-name matches (e.g. someone's `.vercel.app` app, an exam "calc") - do NOT infer a verdict from vibes. Write N/A for entities with no public pitch (people, abstract concepts).
+
 **Skip the normal Step 1 below** - go directly to the comparison synthesis format (see "If QUERY_TYPE = COMPARISON" in the synthesis section).
 
-**COMPARISON TABLE SCAFFOLD (engine-emitted, pass through verbatim):** For comparison topics, the engine's compact output includes a `## Head-to-Head` block with an empty markdown table (columns = entities, rows = axes like "What it is", "Community sentiment", "Trajectory"). Your synthesis MUST include this block verbatim with filled cells, positioned between the narrative and the emoji-tree footer. Keep each cell to 5-15 words. Use ' - ' (hyphen with spaces) not em-dashes inside cells.
+**COMPARISON TABLE SCAFFOLD (engine-emitted, pass through verbatim):** For comparison topics, the engine's compact output includes a `## Head-to-Head` block with an empty markdown table (columns = entities, rows = axes like "What it is", "Setting the narrative?", "Best for"). Your synthesis MUST include this block verbatim with filled cells, positioned between the narrative and the emoji-tree footer. Keep each cell to 5-15 words. Use ' - ' (hyphen with spaces) not em-dashes inside cells.
 
 ### Competitor mode (`--competitors`)
 
@@ -748,6 +750,8 @@ Store as `RESOLVED_IG_CREATORS`.
 
 Store as `RESOLVED_YT_QUERIES`.
 
+**6. First-party positioning** - **MANDATORY when WebSearch is available, for company / product / service topics.** If the topic (or, in a vs-run, an entity) is a company, product, or service with a public presence, fetch its CURRENT stated positioning. Do **NOT** rely on memory - homepages and positioning go stale as companies rewrite copy and pivot, and a stale claim produces a false gap. Anchor on first-party sources: the homepage tagline, docs, pricing, or a "compare/why-us" page. Fold this into the per-entity passes above where you can (e.g. add `official site` to a query); otherwise run one focused search per entity (`{TOPIC} official site`, `{TOPIC} pricing`). Capture the one-line value prop and any explicit claims ("zero-config", "fastest", "open source"). Store as `RESOLVED_POSITIONING`. This is what the entity *pitches*; the engine's community data is what people *actually talk about*. Whether those two line up feeds the `Setting the narrative?` synthesis (the conversation is often on a different topic than the pitch - that mismatch is the signal). Skip (and omit `RESOLVED_POSITIONING`) for people, events, or abstract concepts - they make no comparable public claim.
+
 **Concrete examples:**
 
 | Topic | WebSearches needed | Reddit subs | TikTok hashtags | TikTok creators | IG creators | YT queries |
@@ -800,9 +804,10 @@ Resolved:
 - Reddit: r/{sub1}, r/{sub2}, r/{sub3}, r/{peer1}, r/{peer2} (+ {category_id} peers)
 - TikTok: #{hashtag1}, #{hashtag2}
 - YouTube: {query1}, {query2}
+- Positioning: "{one-line stated value prop}" (first-party)
 ```
 
-Only show lines for platforms where something was resolved. Skip empty lines. On the Reddit line, the trailing `(+ {category_id} peers)` annotation appears when Step 0.55 Section 2a added category-peer subs. Omit the annotation when the topic had no matching category. This display replaces the old "Parsed intent" block with something more useful.
+Only show lines for platforms where something was resolved. Skip empty lines. On the Reddit line, the trailing `(+ {category_id} peers)` annotation appears when Step 0.55 Section 2a added category-peer subs. Omit the annotation when the topic had no matching category. The `Positioning:` line appears for company / product / service topics (from Step 0.55 item 6); omit it for people, events, and abstract concepts. This display replaces the old "Parsed intent" block with something more useful.
 
 ---
 
@@ -1290,6 +1295,7 @@ Voice contract LAWs 1, 3, 5 apply to comparisons unchanged (no `Sources:` block,
 | Dimension | {Entity 1} | {Entity 2} | {Entity 3} |
 |---|---|---|---|
 | What it is | ... | ... | ... |
+| Setting the narrative? | ... | ... | ... |
 | GitHub stars | ... | ... | ... |
 | Philosophy | ... | ... | ... |
 | Skills | ... | ... | ... |
@@ -1299,7 +1305,7 @@ Voice contract LAWs 1, 3, 5 apply to comparisons unchanged (no `Sources:` block,
 | Best for | ... | ... | ... |
 | Install | ... | ... | ... |
 
-(Engine emits this scaffold; fill the cells with 5-15 words each. If an axis does not apply to the topic class, write "N/A" or a topic-appropriate substitute rather than inventing data.)
+(Engine emits this scaffold; fill the cells with 5-15 words each. If an axis does not apply to the topic class, write "N/A" or a topic-appropriate substitute rather than inventing data. For the `Setting the narrative?` row, judge whether each entity's community conversation is about what the entity itself pitches: start the cell with **Yes / Partly / No / Unclear**, then name the topic the community is ACTUALLY on, anchored to a real item with engagement, e.g. "No - pitches uptime, but the top thread is friendly-fraud (323pt HN)". The mismatch is the signal - companies usually don't control their own conversation. Use "Unclear" when evidence is thin or polluted with unrelated brand-name matches; write N/A for entities with no public pitch, like people or abstract concepts. Do NOT infer a verdict from vibes.)
 
 ## The Bottom Line
 
@@ -1441,6 +1447,8 @@ At render time the `@handle`, `r/sub`, and publication-name placeholders become
 
 Headlines should be specific and newsy ("BULLY dropped and it's dominating", "Europe is banning him one country at a time"), not generic ("Album release", "Tour updates").
 
+**Narrative-check beat (company / product / service topics).** If the topic is a company, product, or service and you captured `RESOLVED_POSITIONING` in Step 0.55, work in ONE bold-lead-in paragraph on whether the entity is setting its own narrative - i.e. is the community actually talking about what it pitches, or about something else (pricing, rivals, an incident, a ToS change)? Anchor the verdict to the real top-discussed item with its engagement - e.g. `**Vercel is losing the narrative to its pricing** - it still sells "the AI Cloud" and zero-overhead speed, but the loudest community thread this month is about cost and a June 1 ToS change, not performance`. When the conversation DOES track the pitch, say so (that is the "Yes" case, equally worth stating). Keep it a normal newsy bold-lead-in paragraph with a specific headline (per the rule above), NOT a new `##` section (LAW 4 still holds). Skip it silently for people, events, and abstract concepts, or when the evidence is too thin or noise-polluted to tell - do not manufacture a verdict.
+
 **THEN - Quality Nudge (if present in the output):**
 
 If the research output contains a `**🔍 Research Coverage:**` block, render it verbatim right before the stats block. This tells the user which core sources are missing and how to unlock them. Do NOT render this block if it is absent from the output (100% coverage = no nudge).

skills/last30days/scripts/lib/render.py

@@ -531,9 +531,12 @@ def _render_comparison_scaffold(topic: str) -> list[str]:
     Returns empty list if topic is not a comparison query. When present,
     the block is bracketed so the synthesizer can detect it and pass through.
 
-    Axes match the April 9 launch-video exemplar (9 axes suited to AI-tool
+    Axes are the 9 from the April 9 launch-video exemplar (suited to AI-tool
-    comparisons). For non-AI-tool comparisons, the synthesizer writes N/A
+    comparisons) plus "Setting the narrative?", which asks whether each entity's
-    or topic-appropriate substitutes in irrelevant rows.
+    community conversation is about what the entity itself pitches, or about
+    something else (pricing, rivals, incidents). For comparisons where an axis
+    does not apply, the synthesizer writes N/A or a topic-appropriate substitute
+    in that row.
     """
     entities = _parse_comparison_entities(topic)
     if not entities:
@@ -543,10 +546,11 @@ def _render_comparison_scaffold(topic: str) -> list[str]:
     header = "| Dimension | " + " | ".join(entities) + " |"
     # Separator row matching column count
     separator = "|" + "|".join(["---"] * (len(entities) + 1)) + "|"
-    # 9 axes from the April 9 exemplar. Model fills with topic-appropriate
+    # 9 axes from the April 9 exemplar plus "Setting the narrative?" (pitch vs.
-    # content; irrelevant axes get "N/A" rather than invented data.
+    # what the community actually talks about). See the function docstring.
     axes = [
         "What it is",
+        "Setting the narrative?",
         "GitHub stars",
         "Philosophy",
         "Skills",
@@ -558,10 +562,23 @@ def _render_comparison_scaffold(topic: str) -> list[str]:
     ]
     body = [f"| {axis} | " + " | ".join([" "] * len(entities)) + " |" for axis in axes]
 
+    # Generic fill rules plus guidance for "Setting the narrative?" - the one
+    # axis that needs a judgement, not a lookup.
+    fill_instructions = (
+        "Fill each cell based on the research above. Keep cells short (5-15 words). "
+        "Use ' - ' (hyphen with spaces) not em-dashes. Write N/A for axes that do not apply to this topic class. "
+        "For the \"Setting the narrative?\" row, judge whether each entity's community conversation is about "
+        "what the entity itself pitches: start the cell with Yes / Partly / No / Unclear, then name the topic "
+        "the community is ACTUALLY on, anchored to a real item (e.g. \"No - pitches uptime, but the top thread "
+        "is friendly-fraud (323pt HN)\"). Use Unclear when evidence is thin or polluted with unrelated "
+        "brand-name matches; do NOT infer a verdict from vibes. Write N/A for entities with no public pitch "
+        "(people, abstract concepts). This scaffold matches the April 9 launch-video exemplar shape."
+    )
+
     return [
         "## Head-to-Head",
         "",
-        "Fill each cell based on the research above. Keep cells short (5-15 words). Use ' - ' (hyphen with spaces) not em-dashes. Write N/A for axes that do not apply to this topic class. This scaffold matches the April 9 launch-video exemplar shape.",
+        fill_instructions,
         "",
         header,
         separator,

tests/test_render_comparison_multi.py

@@ -101,6 +101,8 @@ class RenderComparisonMultiTests(unittest.TestCase):
         self.assertIn("## xAI", rendered)
         # Scaffold table header has a column per entity
         self.assertIn("| Dimension | OpenAI | Anthropic | xAI |", rendered)
+        # The narrative-lens axis is emitted as a scaffold row
+        self.assertIn("| Setting the narrative? |", rendered)
         # Envelope scaffolding present
         self.assertIn("EVIDENCE FOR SYNTHESIS", rendered)
         self.assertIn("END OF last30days CANONICAL OUTPUT", rendered)