context-shredding
Runtime context compression for agents approaching model context limits. Defines 3 compression tiers (full/summarized/minimal) with per-artifact templates. USE FOR: reducing artifact loading size at runtime, context budget management. DO NOT USE FOR: diagnostic context auditing (use context-optimizer), Azure infrastructure.
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npx tessl skill review --optimize ./.github/skills/context-shredding/SKILL.mdContext Shredding Skill
Runtime compression system that actively reduces context when agents approach model limits. Agents check approximate context usage before loading artifact files and select the appropriate compression tier.
When to Use
- Before loading a predecessor artifact file (01 through 07)
- When conversation length suggests >60% of model context is used
- When an agent needs to load multiple large artifacts
Compression Tiers
| Tier | Context Usage | Strategy |
|---|---|---|
full | < 60% | Load entire artifact — no compression |
summarized | 60-80% | Load key H2 sections only |
minimal | > 80% | Load decision summaries only (< 500 chars) |
Action Rules
Before loading any artifact file:
- Estimate context usage — count approximate conversation tokens
- Select tier based on the thresholds above
- Apply compression template from the reference doc below
- If loading multiple artifacts, compress the older/less-critical ones first
Tier Selection Protocol
1. Estimate current context usage (rough: 1 token ≈ 4 chars)
2. Check model limit (Opus: 200K, GPT-5.3-Codex: 128K)
3. Calculate usage percentage
4. Select tier:
< 60% → full (no compression needed)
60-80% → summarized (key sections only)
> 80% → minimal (decision summaries only)
5. Load artifact/skill using the appropriate variantSkill Loading Tiers
Skills also have compression tiers (digest and minimal variants):
| Context Usage | Skill Variant | Path Pattern | Approx Tokens |
|---|---|---|---|
| < 60% | Full | SKILL.md | 400-800 |
| 60-80% | Digest | SKILL.digest.md | 150-320 |
| > 80% | Minimal | SKILL.minimal.md | 40-100 |
Available for: azure-defaults, azure-artifacts,
golden-principles, context-shredding.
Reference Index
| Reference | File | Content |
|---|---|---|
| Compression Templates | references/compression-templates.md | Per-artifact H2 sections per tier |
- Repository
- jonathan-vella/azure-agentic-infraops
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