Borrowing it
Nothing to install: this file belongs to MercurieVV/ScalaSemantic. 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/MercurieVV/ScalaSemantic/master/.claude/skills/orchestrate/SKILL.mdgit clone --depth 1 https://github.com/MercurieVV/ScalaSemanticWrote 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/mercurievv/scalasemantic/orchestrate)<a href="https://agentmods.dev/skills/mercurievv/scalasemantic/orchestrate"><img src="https://agentmods.dev/badge/skills/mercurievv/scalasemantic/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/mercurievv/scalasemantic/orchestrate"><img src="https://agentmods.dev/badge/skills/mercurievv/scalasemantic/orchestrate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 350 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00101 | $0.04259 |
| Opus 5 | $0.00051 | $0.02129 |
| Sonnet 5 | $0.00020 | $0.00852 |
| Haiku 4.5 | $0.00010 | $0.00426 |
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 10d 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 — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate — tree-aware multi-agent execution
You are the conductor. You do NOT implement tasks. You manage the task tree from task-splitting-evaluation, schedule workers, track state, handle failures, and report.
Worker agents own their subtree lifecycle — one worker per tree root/orphan, each walks depth-first, fetching context from issue comments, executing sequentially respecting dependencies, and updating GitHub + .claude/task-state.json.
Routing knowledge: .claude/orchestrate-routing.md. Read it once at start.
Default to codex/agy. Use claude (scala-coder) ONLY for hard Scala tasks needing scala-semantic MCP.
Tree structure (from task-splitting-evaluation)
Each task is a GitHub issue with:
- task-tree-marker comment: Status (leaf-ready), Parent, Children, Preferred executor
- Body: Task description, Acceptance criteria, Dependencies (e.g., "depends on #129")
- Dependencies: explicitly listed in issue body (e.g., "Depends: #129 → read from comment")
Root issues (no parent): #111, #105, #112, #108, #106, #79, #73, #72, #80, #71
- Leaf issues (no children): all others (30+ children from expansion)
- Orphan issues (if any): leaves not linked to any parent via marker
Invocation modes
Normal
/orchestrate — build task tree, schedule workers, execute depth-first per branch with root/orphan parallelization.
Dry-run
/orchestrate --dry-run (or user says "preview"/"plan only") — build task tree, print execution plan but do NOT launch workers. Show:
| Root | Tree depth | Leaf count | First task | Executor | Status |
|---|---|---|---|---|---|
| #112 | 1 | 4 | #128 (research) | agy | pending |
| #111 | 0 | 1 | #111 (value_flow) | claude | pending |
Let user inspect and approve before executing. Only spend tree-building (Haiku) tokens.
Resume (partial failure)
/orchestrate --resume — read .claude/task-state.json, continue from last halted/incomplete task, skip done tasks.
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.
- 10d ago First seen · 364 lines · 101 tokens per session scan A f9c7def6a9e4
orchestrate is a skill published in the GitHub repository MercurieVV/ScalaSemantic (21 stars, last pushed 2d ago), licensed MIT. It adds 101 tokens to every session and 4,259 once invoked, about $0.0005 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 2026-08-30.
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