Context Pack
Prepare files, folders, code, logs, and structured data as a bounded, traceable context pack for Codex. Use when source material must be converted, deduplicated, selected, budgeted, or handed off with exact evidence anchors.
Install
$ agentstack add skill-tikazi-tikaz-ai-skills-context-pack ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-tikazi-tikaz-ai-skills-context-pack) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Context Pack
Designed, integrated, independently refactored, and continuously maintained by TIKAZ.
Own canonical ingestion, fidelity profiling, exact deduplication, evidence selection, and final pack size. First run profile or let pack profile automatically:
text: canonical Markdown is sufficient;hybrid: use Markdown for text and a bounded visual-evidence queue for informative images or complex tables;source: keep the original asset/page path when safe extraction cannot preserve task-relevant information.
Do not trigger vision for a logo, repeated icon, background, or every image merely because it exists. When the queue contains pending-vision items and the host can inspect images, resolve the referenced item, record an anchored observation plus uncertainty, and keep the original reference. When the capability is unavailable, leave it pending or recommend the source file; never invent a description.
Assemble one task-ready artifact in this order:
- task and expected output;
- selected mode and estimated budget;
- confirmed constraints and protected facts;
- exact evidence excerpts with source anchors;
- decisions, completed work, and current state;
- conflicts and open questions;
- omitted-anchor inventory and verification limits.
The pack must distinguish exact source text, structured state, and inference. It must remain useful without the surrounding chat. Count the complete artifact against the budget. If essential protected evidence cannot fit, return a visible budget conflict instead of silently exceeding the limit.
Run python scripts/tikaz_context.py pack --input --query --budget --visual-budget --output . Read the final artifact at /packs/current-task.context.md; profile.json, visual-evidence.json, context-cost-ledger.json, canonical files, indexes, the ledger, and the savings report remain beside it.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: TIKAZI
- Source: TIKAZI/TIKAZ-AI-Skills
- License: MIT
- Homepage: https://tikazi.github.io/TIKAZ-AI-Skills/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.