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 engineeringgit 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/engineering)<a href="https://agentmods.dev/skills/tikazi/tikaz-ai-skills/engineering"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/engineering/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/engineering"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/engineering.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 | $0.00043 | $0.00447 |
| Opus 5 | $0.00022 | $0.00224 |
| Sonnet 5 | $0.00009 | $0.00089 |
| Haiku 4.5 | $0.00004 | $0.00045 |
Grade A, and why
engineering 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineering
Designed, integrated, refactored, and continuously maintained by TIKAZ.
Inputs and routing
Accept a repository, requested change, constraints, risk boundary, and expected evidence. Use the orchestrator for cross-file or release-bound work; use a child Skill directly when architecture mapping, delivery, security audit, Supabase operations, or media-pipeline engineering is the whole outcome.
TIKAZ method
- Freeze scope, non-goals, acceptance criteria, and evidence required for completion.
- Use
code-intelligenceto map architecture and impact before editing unfamiliar or cross-cutting code. - Use
engineering-deliveryas the lifecycle owner: plan small slices, implement, test, review, and report. - Route only domain-specific work to
supabase-operationsorvideo-workbench. - Run
skill-security-auditbefore importing unfamiliar executable skills or dependencies. - Keep an evidence ledger: commands, results, artifacts, regressions checked, and remaining risk.
Conflict rule
code-intelligence advises; engineering-delivery executes. Domain adapters cannot expand scope without explicit acceptance criteria.
Completion gate
Require repository-native validation, final diff review, no leaked secrets, an explicit release/rollback note when applicable, and objective evidence for every acceptance criterion.
Output, fallback, and limits
Return the agreed scope, impact map, implementation record, verification evidence, rollback note, and remaining risks. If repository-native commands or required credentials are unavailable, stop at the last verified artifact and state the missing capability. Do not deploy, migrate production data, or perform destructive actions without explicit authority.
Example
Use engineering to map this API change, implement it in small verified slices, review the final diff, and provide rollback evidence.
Read references/routing.md and references/output-contract.md.
What ships with it
16 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.
- agents/openai.yaml 259 B
- assets/workflow.svg 5.2 KB
- code-intelligence/agents/openai.yaml 312 B
- code-intelligence/SKILL.md 2.3 KB
- engineering-delivery/agents/openai.yaml 301 B
- engineering-delivery/SKILL.md 2.1 KB
- README.md 5.1 KB
- README.zh-CN.md 2.6 KB
- references/output-contract.md 269 B
- references/routing.md 634 B
- skill-security-audit/agents/openai.yaml 318 B
- skill-security-audit/SKILL.md 1.7 KB
- supabase-operations/agents/openai.yaml 310 B
- supabase-operations/SKILL.md 1.6 KB
- video-workbench/agents/openai.yaml 308 B
- video-workbench/SKILL.md 1.9 KB
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.
- 11d ago First seen · 42 lines · 43 tokens per session scan A 88e219f51442
engineering is a skill published in the GitHub repository TIKAZI/TIKAZ-AI-Skills (6 stars, last pushed 8d ago), licensed MIT. It adds 43 tokens to every session and 447 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 2026-08-31.
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