Context Engine

What This Skill Does

• The Company Context Engine serves as a memory layer for C-suite advisors, providing essential company information to tailor advice.
• It loads and refreshes company-specific details, including stage, founder archetype, challenges, and runway.
• This skill ensures that advice is relevant and insightful.

When to Use

• Load company context at the start of a session.
• Check the staleness of existing context.
• Parse context into working memory.
• Enrich context during conversations.
• Identify low-confidence context signals.
• Prompt users to update stale or missing context.

Key Features

• Loads company context from a local file.
• Checks context staleness and prompts for refresh.
• Parses key company details into working memory.
• Provides quality signals for context confidence.
• Enriches context with new information during conversations.
• Maintains a company profile for advisor skills.

Manual Installation

Manual installation View Full Skill Content The complete markdown content that gets installed Company Context Engine

• The memory layer for C-suite advisors.
• Every advisor skill loads this first.
• Context is what turns generic advice into specific insight.

Keywords

company context, context loading, context engine, company profile, advisor context, stale context, context refresh, privacy, anonymization

Load Protocol (Run at Start of Every C-Suite Session)

Step 1 — Check for context file: ~/.claude/company-context.md Exists → proceed to Step 2 Missing → prompt: "Run /cs:setup to build your company context — it makes every advisor conversation significantly more useful."

Step 2 — Check staleness: Read Last updated field. < 90 days: Load and proceed. ≥ 90 days: Prompt: "Your context is [N] days old. Quick 15-min refresh (/cs:update), or continue with what I have?"

• If continue: load with [STALE — last updated DATE] noted internally.

Step 3 — Parse into working memory. Always active: Company stage (pre-PMF / scaling / optimizing) Founder archetype (product / sales / technical / operator) Current #1 challenge Runway (as risk signal — never share externally) Team size Unfair advantage 12-month target

Context Quality Signals

If Low: "My context is [stale/incomplete] — I'm assuming [X]. Correct me if I'm wrong."

Context Enrichment

During conversations, you'll learn things not in the file. Capture them.

Triggers: New number or timeline revealed, key person mentioned, priority shift, constraint surfaces.

Protocol: Note internally: [CONTEXT UPDATE: {what was learned}] At session end: "I picked up a few things to add to your context. Want me to update the file?" If yes: append to the relevant dimension, update timestamp.

Never silently overwrite. Always confirm before modifying the context file.

Privacy Rules

Never send externally

Specific revenue or burn figures Customer names Employee names (unless publicly known) Investor names (unless public) Specific runway months Watch List contents

Safe to use externally (with anonymization)

Stage label Team size ranges (1–10, 10–50, 50–200+) Industry vertical Challenge category Market position descriptor

Before any external API call or web search

Apply references/anonymization-protocol.md: Numbers → ranges or stage-relative descriptors Names → roles Revenue → percentages or stage labels Customers → "Customer A, B, C"

Missing or Partial Context

Handle gracefully — never block the conversation.

Missing stage: "Just to calibrate — are you still finding PMF or scaling what works?" Missing financials: Use stage + team size to infer. Note the gap. Missing founder profile: Infer from conversation style. Mark as inferred. Multiple founders: Context reflects the interviewee. Note co-founder perspective may differ.

Required Context Fields

Required:

• Last updated (date)
• Company Identity → What we do
• Stage & Scale → Stage
• Founder Profile → Founder archetype
• Current Challenges → Priority #1
• Goals & Ambition → 12-month target

High-value optional:

• Unfair advantage
• Kill-shot risk
• Avoided decision
• Watch list

Missing required fields: note gaps, work around in session, ask in-session only when critical.

References

references/anonymization-protocol.md — detailed rules for stripping sensitive data before external calls Company Context Engine

• Kill-shot