intel

name	intel
description	Gather and shape intelligence signals from collected feeds (RSS, HackerNews, Lobsters, EDGAR) into audience-aware output. Use when you need current context on a technology, industry trend, or domain — or when you need to present signals to a specific audience. NOT for forward-looking predictions (use forecast); NOT for architecture analysis (use archobs); NOT for writing specs (use spec).
metadata	{"stage":"Define","tags":["intelligence","trends","signals","research","briefing","news","feeds","evidence","audience","executive","engineering","decision","digest","synthesis","presentation","stakeholder"],"aliases":["intel","intelligence","signals","executive-brief","daily-digest","decision-brief"]}

Intel (Intelligence Briefs)

Overview

Produce focused intelligence briefs on a topic by querying the intel CLI against locally collected feeds (RSS, HackerNews, Lobsters, EDGAR). Briefs combine trending signals, full-text search hits, and topic breakdowns into a concise, evidence-backed summary an agent or human can act on.

Use this skill when you need current signal on a technology, vendor, standard, or industry trend — or when you need to present signals to a specific audience.

Success looks like: a brief with ranked signals, source citations, and a clear "so what" tailored for the target audience — readable in under 2 minutes and actionable without needing to parse raw data.

Prerequisites

1. Build the tool:

   cd tools/intelligence && npm install && npm run build
   

2. Make intel available on PATH:

   npm link          # from tools/intelligence/
   

3. Create a config file:

   mkdir -p ~/.config/intel ~/.local/share/intel
   cp config/feeds.example.yaml ~/.config/intel/config.yaml
   # Edit ~/.config/intel/config.yaml to customize feeds
   

4. Seed the database (first run):

   intel collect --once
   

5. Install the collector as a background service so data stays fresh:

   ./service/install.sh        # macOS (launchd) / Linux (systemd)
   

   This installs a LaunchAgent (macOS) or systemd user unit (Linux) that starts on login and restarts on crash. Verify it's running:

   # macOS
   launchctl print gui/$(id -u)/com.intel.collector
   tail -f ~/Library/Logs/intel-collector.log
   
   # Linux
   systemctl --user status intel-collector
   journalctl --user -u intel-collector -f
   

   To uninstall: ./service/install.sh uninstall

6. Verify: intel stats — check events_total > 0 and newest_event is recent.

Chooser

Content type (what data to gather)

Type	When to use
Topic brief (default)	"What's happening with X?"
Trend scan	General landscape check
Evidence pack	Feeding context into another skill
Source check	Verify data quality

Audience (how to present — default: practitioner)

Audience	Shape	When to use
Practitioner (default)	Ranked signals, trend context, gaps, so what	Feeding into your own work
Executive	3-5 bullet TL;DR, "so what", recommended action, risk flags	Status updates, steering meetings
Engineering	Signals mapped to stack, migration/deprecation implications	Sprint planning, tech radar
Decision	Evidence mapped to options, recommendation	Buy-vs-build, adopt-vs-wait, vendor selection
Daily digest	Top-5 signals, one-line commentary	Morning standup, async channel
Architecture decision	Archobs risk + forecast lifecycle × decision options	Technology adoption, boundary redesign

Clarifying Questions

• What topic or domain do you want a brief on?
• What time horizon matters? (last few hours, last week, last month)
• Is this for general awareness or feeding into a specific decision?
• Any particular sources or subtopics to prioritize?
• Who is the audience for this brief?
• Which brief type fits? (practitioner, executive, engineering, decision, daily digest, architecture decision)

Workflow

1. Determine content type and audience — ask or infer from context. If unclear, default to practitioner audience with topic brief.

2. Verify data freshness:

   intel stats
   

   Check total_events and newest_event — if the database is empty or stale, run intel collect --once first.

3. Gather signals (choose based on content type):

   Topic brief — run in parallel:

   intel search "<topic>" --since 7d --limit 20
   intel trends --window 60m --top 10
   intel topics --active
   

   Trend scan:

   intel trends --window 60m --top 15
   

   Evidence pack:

   intel pack --since 6h --top 10 --max-events 5
   

   Source check:

   intel sources
   

4. Audience-specific signal gathering (in addition to content type above):

   Executive / Daily digest:

   intel pack --since 24h --top 10 --max-events 5
   

   Engineering — run in parallel:

   intel pack
   intel search "<stack-relevant terms>"
   intel topics --active
   

   Decision — run in parallel:

   intel search "<decision topic>"
   intel trends
   

   Architecture decision — requires archobs + forecast data:

   archobs show clusters --format json
   archobs show risks --format json
   intel forecast    # lifecycle phases for relevant technologies
   

5. Deepen on high-signal hits — for the most relevant results, fetch full event detail:

   intel events --id <event_id>
   

6. Filter and rank — select the top signals by relevance to the audience:

Guardrails

• Do not present intel output as authoritative fact — these are signals from configured feeds, not exhaustive research.
• Do not skip the freshness check — stale data produces misleading briefs.
• Do not dump raw JSON to the user — always synthesize into the output template.
• Do not run intel collect in long-running daemon mode during a brief — use --once if a refresh is needed.
• Do not mix brief types — pick one audience and commit.
• Do not fabricate signals — only use data returned by intel commands.
• Executive briefs must be readable by non-technical stakeholders — no jargon, no acronyms without expansion.

Output Template

Practitioner (default)

• Topic: the subject of the brief
• Data window: time range covered, event count, source count
• Top signals (3-5): title, source, timestamp, why it matters
• Trend context: what's rising/falling, velocity of change
• Gaps: stale sources, missing coverage areas, low-confidence signals
• So what: 1-2 sentence synthesis of what this means for the user's context
• Next skill: where to go from here (plan, spec, architecture, etc.)

Executive

• Headline: 1 sentence — what's the most important thing to know
• Top signals (3-5 bullets): plain language, no jargon, each with why it matters
• So what: 1-2 sentences — implication for us specifically
• Recommended action / next step: what to do with this information
• Risk flags (if any): things that could go wrong if we ignore this

Engineering

• Data window: time range covered, event count, source count
• Signals by relevance to our stack: grouped by topic (e.g., runtime, framework, infra, tooling)
• Migration / deprecation watch: things to track that may force future work
• New tools / releases worth evaluating: notable releases relevant to our stack
• Security advisories (if any): CVEs, supply-chain risks, dependency alerts
• Links to deeper reads: URLs from source events for follow-up

Decision

• Decision statement: what we're choosing between (frame as a clear question)
• Evidence for each option: sourced from signals, with citations
• Gaps in evidence: what we don't know and how it affects confidence
• Recommendation: selected option with confidence level (high / medium / low)
• Next skill: plan or spec to act on the decision

Daily Digest

• Date + data window: date, time range, source count
• Top 5 signals: title + one-line take for each
• One thing to watch: emerging trend that hasn't peaked yet
• Source health note (if degraded): flag stale or unreachable sources

Architecture Decision

• Decision statement: what we're choosing between
• Structural context (from archobs): cluster coupling, boundary health, risk scores for affected areas
• Ecosystem context (from forecast): lifecycle phase, chain activity, system dynamics for relevant technologies
• Cross-domain synthesis: where structural reality and ecosystem signals align or conflict
• Options matrix: each option scored against structural + ecosystem evidence
• Recommendation: selected option with confidence level
• Next skill: plan or spec

References

• Forward-looking predictions: forecast
• Architecture observability: archobs
• Implementation planning: plan
• Spec-driven development: spec
• Architecture decisions: architecture