Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add TIKAZI/TIKAZ-AI-Skills --skill context-orchestratorgit clone --depth 1 https://github.com/TIKAZI/TIKAZ-AI-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tikazi/tikaz-ai-skills/context-orchestrator)<a href="https://agentmods.dev/skills/tikazi/tikaz-ai-skills/context-orchestrator"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/context-orchestrator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tikazi/tikaz-ai-skills/context-orchestrator"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/context-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00501 |
| Opus 5 | $0.00024 | $0.00251 |
| Sonnet 5 | $0.00010 | $0.00100 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
context-orchestrator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- context-orchestrator — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TIKAZ Context Orchestrator
Designed, integrated, independently refactored, and continuously maintained by TIKAZ.
What it owns
This Skill is a controller, not a third compressor. It fixes the task, evidence slots, risk, and budget, chooses exactly one primary route, and requires both routes to return traceable evidence, omissions, Pending items, fallbacks, and separate quality/cost metrics.
Routing
- Default to
context-economy: dependency-free, portable, conservative, and source-preserving. - Use
context-onpremiseonly when the first non-empty control word is uppercaseONfollowed by end-of-input, whitespace,:, or:, or when the user explicitly invokes it. - Strip the valid
ONcontrol prefix before passing the remaining task downstream. - Lowercase
on,ONLY,ON-board,请 ON 分析, andONappearing later in a sentence do not trigger the local route.
Use python scripts/route_context.py --text <request> when deterministic trigger verification is useful. The script parses only the control prefix; it does not open files, install dependencies, start models, or access the network.
Output contract
Return route, task, budget, evidence slots, context pack, protected facts, anchors, retrieval ledger, cost ledger, omissions, visual Pending items, and fallback reason. Report Recall/Precision, protected-fact recall, estimated tokens, file bytes, image counts, latency, and downstream answer quality separately. If labels or provider telemetry do not exist, mark the metric Pending.
Validation and fallback
A smaller context with lower evidence coverage is a failure. Expand retrieval or preserve the source when required slots are missing, facts conflict, visual evidence is unchecked, or protected literals are lost.
Example
ON:把这个扫描 PDF 和视频整理成可追溯的 Context Pack,并分别报告命中、保真和估算 Token。
Limits
The controller does not install local runtimes, download models, enable network access, or broaden authorization. Route availability depends on the installed child Skill and current environment.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 40 lines · 48 tokens per session scan A de89324c9965
context-orchestrator is a skill published in the GitHub repository TIKAZI/TIKAZ-AI-Skills (6 stars, last pushed 9d ago), licensed MIT. It adds 48 tokens to every session and 501 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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