context-engine
Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls.
Best use case
context-engine is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls.
Teams using context-engine should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/context-engine/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How context-engine Compares
| Feature / Agent | context-engine | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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
| Condition | Confidence | Action |
|-----------|-----------|--------|
| < 30 days, full interview | High | Use directly |
| 30–90 days, update done | Medium | Use, flag what may have changed |
| > 90 days | Low | Flag stale, prompt refresh |
| Key fields missing | Low | Ask in-session |
| No file | None | Prompt /cs:setup |
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:**
1. Note internally: `[CONTEXT UPDATE: {what was learned}]`
2. At session end: *"I picked up a few things to add to your context. Want me to update the file?"*
3. 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 callsRelated Skills
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