Context Check Command

Quick validation of context quality before shipping or during review.

5 checks. 5 minutes. Use before launch or during code review.

Usage

/context-check                    # Check a prompt/feature
/context-check --prompt           # Paste a prompt/payload to analyze
/context-check LIN-123            # Check context for Linear issue

The 5 Checks

1. RELEVANCE

Is everything here necessary?

More context ≠ better. Irrelevant context confuses the model, increases cost, and slows responses.

• Does every piece of context directly contribute to the task?
• Is there anything "kind of related" that could be cut?
• Is there decorative metadata that doesn't help reasoning?

2. FRESHNESS

Is the data current enough?

Stale context = stale outputs. A model reasoning about yesterday's data will give yesterday's answers.

• Are timestamps recent enough for this task?
• Are metrics, dashboards, logs up to date?
• Could cached data be invalid for this request?

3. SUFFICIENCY

Does the model have enough to reason?

Missing context forces the model to guess. Guessing = hallucinating.

• Are all required entities present?
• Are dependencies, relationships, history included?
• Could the model answer correctly without guessing?

4. STRUCTURE

Is context organized clearly?

Dumping raw text forces the model to parse meaning. Structured, labeled sections reduce ambiguity.

• Is context broken into labeled sections?
• Are relationships explicitly described (not implied)?
• Is domain knowledge structured (not prose blobs)?

5. CONSTRAINTS

Are the rules explicit?

Prompts are suggestions. The model will eventually ignore them. Hard rules must be enforced outside the prompt or stated as non-negotiable.

• Are business rules explicitly stated?
• Are tone, formatting, domain rules included?
• Is permission logic represented accurately?
• Are prohibited actions clearly listed?

Output

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 CONTEXT QUALITY CHECK
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

  ┌─────────────┬────────────┐
  │ Check       │ Result     │
  ├─────────────┼────────────┤
  │ Relevance   │ ✓ PASS     │
  │ Freshness   │ ✓ PASS     │
  │ Sufficiency │ ⚠ NEEDS WORK │
  │ Structure   │ ✓ PASS     │
  │ Constraints │ ⚠ NEEDS WORK │
  └─────────────┴────────────┘

  Overall: 3/5 PASSING

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

ISSUES TO FIX:

• Sufficiency: Missing user's role/permissions - model may suggest
  actions user can't take
• Constraints: No explicit list of prohibited topics - model may
  drift into off-topic responses

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

When to Use

Before shipping:

• Final check before launching AI feature
• Part of your pre-launch checklist

During review:

• Code review for prompt changes
• Reviewing teammate's context design

When debugging:

• Quick check to rule out context issues
• Before diving into full /ai-debug audit

Instructions

Workflow:

1. Ask what they're checking (prompt, feature spec, Linear issue)
2. If prompt pasted, analyze directly
3. Walk through each of the 5 checks
4. Score each: PASS / NEEDS WORK / FAIL
5. List specific issues to fix
6. Offer to export or add to Linear

For each check, ask:

• "Looking at [check name]... [specific question]"
• Give concrete feedback, not just pass/fail

Key insight: All hallucinations are context failures before they're model failures. This checklist catches problems before users do.

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Framework: Context Quality Checklist (4D Context Canvas) Best for: Pre-ship validation, code review, quick context audits