Install
$ agentstack add skill-tikazi-tikaz-codex-context-economy-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.
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.
Inputs and routing
Accept one or more files, folders, code trees, logs, structured data, or converter-produced Markdown plus a concrete task. Use text for confident text-first material, hybrid for bounded task-relevant visuals or complex tables, and source when extraction cannot preserve important evidence.
Workflow
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.
Profile first, protect literal facts and anchors, deduplicate only exact or formatting-only repetition, select task-relevant evidence, and 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.
Output contract
Return /packs/current-task.context.md with profile.json, visual-evidence.json, context-cost-ledger.json, canonical files, indexes, and savings-report.md. Distinguish exact excerpts, structured state, inference, omissions, and pending visual evidence.
Validation and fallback
Count the complete artifact against the budget and verify protected facts plus selected anchors. If a converter or vision host is unavailable, leave evidence pending or preserve the source reference. Never invent a visual description. If essential evidence cannot fit, report a visible budget conflict.
Example
Use context-pack on these release notes and logs. Build an 800-token pack for regression review, keep commands and versions exact, and list omitted anchors.
Run python scripts/tikaz_context.py pack --input --query --budget --visual-budget --output .
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-Codex-Context-Economy
- License: MIT
- Homepage: https://tikazi.github.io/TIKAZ-AI-Skills/skills/context-economy/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.