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Context Shredding

ASecurity

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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  • Added May 27, 2026
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Scanned May 27, 2026

npx -y skills add jonathan-vella/bmit-2026 --skill context-shredding --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: context-shredding
description: "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."
---

# Context 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:

1. **Estimate context usage** — count approximate conversation tokens
2. **Select tier** based on the thresholds above
3. **Apply compression template** from the reference doc below
4. If loading multiple artifacts, compress the older/less-critical ones first

## Tier Selection Protocol

```text
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 variant
```

## Skill 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`, `session-resume`,
`golden-principles`, `context-shredding`.

## Reference Index

| Reference             | File                                  | Content                           |
| --------------------- | ------------------------------------- | --------------------------------- |
| Compression Templates | `references/compression-templates.md` | Per-artifact H2 sections per tier |

Files in this skill

  • SKILL.digest.md1.3 KB
  • SKILL.md2.8 KB
  • SKILL.minimal.md296 B
  • references/compression-templates.md4.2 KB

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