Borrowing it
Nothing to install: this file belongs to VoTruongDanh/Skills-Agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/VoTruongDanh/Skills-Agent/main/.agents/skills/orchestrate/SKILL.mdgit clone --depth 1 https://github.com/VoTruongDanh/Skills-AgentWrote 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/votruongdanh/skills-agent/orchestrate)<a href="https://agentmods.dev/skills/votruongdanh/skills-agent/orchestrate"><img src="https://agentmods.dev/badge/skills/votruongdanh/skills-agent/orchestrate/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/votruongdanh/skills-agent/orchestrate"><img src="https://agentmods.dev/badge/skills/votruongdanh/skills-agent/orchestrate.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 | $0.00057 | $0.00909 |
| Opus 5 | $0.00028 | $0.00454 |
| Sonnet 5 | $0.00011 | $0.00182 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
orchestrate 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 4d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Protocol
START: Read .ai-memory.md from project root. Check project architecture, team structure, past orchestration plans, ongoing tasks, and blockers.
END: Update .ai-memory.md using Memory Compaction Rules with: workstreams, assignments, dependencies, execution order, and blockers/risks.
Goal
Break a complex request into a coordinated execution plan with clear agent assignments.
Agent Routing
- Primary coordinator → read
.kiro/skills/agents/agents/orchestrator.mdand apply its knowledge - For planning phases → read
.kiro/skills/agents/agents/project-planner.mdand apply its knowledge - For each workstream, read the most relevant agent file:
- Frontend tasks → read
.kiro/skills/agents/agents/frontend-specialist.md - Backend tasks → read
.kiro/skills/agents/agents/backend-specialist.md - Database tasks → read
.kiro/skills/agents/agents/database-architect.md - Testing → read
.kiro/skills/agents/agents/test-engineer.md - Security review → read
.kiro/skills/agents/agents/security-auditor.md - Deployment → read
.kiro/skills/agents/agents/devops-engineer.md
- Frontend tasks → read
Socratic Gate
Before orchestrating, verify:
- What is the full objective? (end-to-end scope)
- How many domains are involved? (frontend, backend, DB, infra?)
- Are there hard dependencies or deadlines? If any answer is unclear, ASK before proceeding.
Workflow
- Read Memory — Load
.ai-memory.mdfor project context and history. - Decompose the objective into workstreams.
- Assign each workstream to the appropriate agent/role.
- Identify dependencies, blockers, and the critical path.
- Define parallelizable tasks and merge points.
- Produce an execution order with clear handoffs.
- Quality Gate — Read
.kiro/skills/_scripts/checklist.mdand verify each workstream output before merge. - Update Memory — Save orchestration plan to
.ai-memory.md.
Output format
- Objective
- Workstreams (with assigned agents)
- Dependencies and critical path
- Execution order (sequential + parallel)
- Risks and mitigations
- Done criteria for each workstream
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.
- 4d ago Changed · +3 lines ee75a56f3d7f
- 9d ago First seen · 78 lines · 57 tokens per session scan A f0c77b619701
orchestrate is a skill published in the GitHub repository VoTruongDanh/Skills-Agent (2 stars, last pushed 5d ago), licensed MIT. It adds 57 tokens to every session and 909 once invoked, about $0.0003 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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