intel-scan

A weekly market-intelligence command for a company's content planning. It searches recent competitor, industry, social-media, and visual-trend activity.

In plain words
What is it for?
Scanning the previous week's competitor activity, industry news, LinkedIn posts, X posts, industry leaders, product launches, partnerships, messaging changes, and popular visual formats.
Why use it?
It gathers scattered recent signals before the team plans content, reducing the need to search each source separately.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/saigonxiii/evc/intel-scan
Clone the repo
git clone --depth 1 https://github.com/SaigonXIII/evc
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 579 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00579
Opus 5 $0.00000 $0.00290
Sonnet 5 $0.00000 $0.00116
Haiku 4.5 $0.00000 $0.00058

Measured 2d ago against content hash ea83efcdfd87, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

intel-scan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

_templates/commands/intel-scan.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Intel Scan

Weekly intelligence gathering for the {{COMPANY_NAME}} content engine. Run on Sunday evening or Monday morning before content planning.

Trigger

User invokes /intel-scan or asks to "scan for intel", "research competitors", "what's happening this week"

Steps

1. Market Intelligence

Search web and LinkedIn for recent activity from competitors and industry:

  • Search X/Twitter for posts from accounts listed in content-engine/memory/competitor-watch.md
  • Search for relevant industry keywords and news from the past 7 days
  • Search LinkedIn for competitor company posts using mcp__linkedin__get_company_posts for key competitors
  • Use mcp__linkedin__search_people to find industry leaders posting about relevant topics
  • Identify trending topics, narratives, and announcements in the space
  • Note any competitor product launches, partnerships, or messaging shifts

2. Visual Intelligence

  • Search for high-performing posts in your industry on X from the past week
  • Identify visual trends: formats getting the most engagement (video vs static, dark vs light, stat-led vs story-led)
  • Check if any new X features or formats have launched
  • Compare against our visual style documented in content-engine/memory/visual-log.md

3. Platform Intelligence

  • Search for X/Twitter algorithm updates, developer blog posts, or feature changes
  • Check for any changes to post reach, engagement weighting, or content format preferences
  • Note any new posting best practices from social media marketing sources

4. Compile Report

Write the intel report to content-engine/calendar/ as intel-[date].md with sections:

  • Market Signals — what competitors are doing, industry trends
  • Visual Trends — what's working visually, format insights
  • Platform Updates — algorithm changes, feature updates
  • Recommendations — specific suggestions for this week's content

5. Update Memory Files

Append new findings to:

  • content-engine/memory/competitor-watch.md — new observations
  • content-engine/memory/visual-log.md — new visual insights
  • content-engine/memory/learning-log.md — new learnings

Read the full file on GitHub · 54 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 54 lines · 0 tokens per session scan A ea83efcdfd87

Subscribe to this mod's changes

intel-scan is a command published in the GitHub repository SaigonXIII/evc (56 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 579 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.