weekly-signal-diff

name	weekly-signal-diff
description	Use when the user wants a weekly structural diff on AI, software, or another fast-moving market. Starts from 10 suggested categories and 30 suggested companies when no watchlist exists, then adapts the scan using Open Brain memory, current priorities, and prior digests. Best for prompts like "run my weekly signal diff", "what changed this week that matters to me", "track this market", or "turn this week's news into structural shifts". Optional live search upgrade: if OpenRouter access is available, prefer the Perplexity Sonar family for fresh web-grounded retrieval with citations.
author	Jonathan Edwards
version	1.0.0

Weekly Signal Diff

Problem

A wall of news does not tell the user what structurally changed. Most weekly roundups over-index on headlines, underweight economics and dependency shifts, and ignore what the user actually cares about. This skill turns a noisy week into a small set of structural changes, weighted by Open Brain memory.

When to Use

• Weekly market review or Sunday/Friday ritual
• "Run my weekly signal diff"
• "What changed this week that matters to me?"
• "Track this market and tell me the structural shifts"
• "Turn this pile of news into a decision-grade diff"
• Ongoing automation that writes a weekly digest back to Open Brain

Required Context

Gather as much as the environment allows:

• the user's active projects, bets, and recurring interests
• prior weekly digests or adjacent summaries stored in Open Brain
• the desired freshness window (default: last 7 days)
• any preferred outlets, banned sources, or explicit watchlist entities

If the user has not provided categories or companies, read references/starter-universe.md and use it as a bootstrap layer only.

If live web access is available and the user wants current coverage, read references/live-search-upgrade.md and use the strongest search mode the environment supports.

Process

1. Establish the frame.

   • Confirm the topic space, freshness window, and whether the goal is personal awareness, operator strategy, investor tracking, or content prep.
   • If the user says nothing, default to a 7-day operator-style review.

2. Pull Open Brain context first.

   • Search for active projects, current priorities, recurring entities, recent captures, and the last 2-4 weekly digests.
   • Tool names vary by client. Use the available Open Brain search, list, and capture tools in the environment rather than assuming fixed names.
   • Extract a short relevance profile: what the user is building, what they keep revisiting, what they are worried about, and what they are trying to learn.

3. Build the watchlist.

   • Start from the suggested 10-category / 30-company starter universe if the user has not defined a watchlist.
   • Treat the starter list as a scaffold, not a contract.
   • Re-rank or replace items using Open Brain context:
     • promote companies, categories, or themes the user mentions often
     • demote low-signal items
     • add personal-priority entities even if they are outside the starter set
   • Preserve some baseline discovery. Personalization should shape the scan, not collapse it into only known favorites.

4. Gather the week's evidence.

   • Prefer fresh, source-backed information with links or citations.
   • If live search is available, perform a broad sweep first, then targeted follow-ups on the top candidate shifts.
   • If live search is not available, work from the user's provided sources and say that the diff is source-bounded.
   • Ignore pure announcement theater unless it changes economics, distribution, regulation, dependency, geography, or buyer behavior.

5. Ask the structural questions on every candidate signal.

   • What constraint shifted?
   • Who gained or lost leverage?
   • What got cheaper, harder, faster, or more defensible?
   • What dependency got exposed?
   • What business model or pricing assumption weakened?
   • What changed in regulation, geography, or distribution?
   • Why does this matter for the user's actual projects, workflows, or market view?

6. Score before writing.

   • Keep only the few signals that represent real change.
   • A good weekly diff usually has 3-7 structural shifts.
   • Merge duplicates, drop weak stories, and explicitly label speculation as speculation.

Use this default structure:

• Coverage note — what was scanned, how it was personalized, and the date window
• Structural shifts — 3-7 items, each with:
  • what changed
  • why it matters in general
  • why it matters to this user
  • supporting evidence or citations
• What changed from last week — new, rising, fading, or resolved themes
• Watch next — entities, constraints, or questions to monitor
• Actions — optional follow-ups, only if the evidence supports them

1. Capture the durable output.
   • Save the final digest back into Open Brain when capture tools are available.
   • Prefer one durable weekly summary plus separate captures only for truly important follow-up items.
   • Include provenance: week ending date, topic scope, and major entities covered.

Output

When this skill works correctly, the user gets:

• a concise weekly structural diff instead of a headline roundup
• a clear explanation of why the shifts matter to them specifically
• citations or source links when live search is available
• a durable weekly digest saved back into Open Brain for future comparison

Guardrails

• The goal is diff, not digest.
• Do not force all 30 suggested companies into the final output. They are there to prevent blank-page syndrome, not to create fake coverage.
• Do not mistake product launches, benchmark screenshots, or funding headlines for structural change unless they move a real constraint.
• Keep general market analysis separate from personalized implications.
• If evidence is thin, say the week was thin.
• If the environment lacks live search, be explicit about the freshness limitation.
• If the user's interests are unclear, use the starter universe and explain that it is a bootstrap pass.

Notes for Other Clients

• This skill is portable across Claude Code, Codex, Cursor, and similar clients because the core behavior is procedural.
• Adapt Open Brain tool names to the local environment.
• For scheduled runs, pair the skill with the user's automation system and keep the same structure every week so diffs stay comparable.
• If OpenRouter is available, prefer a Perplexity Sonar web-search model for the retrieval pass, then use the local AI client or model to do the actual synthesis if that split is more ergonomic.