Borrowing it
Nothing to install: this file belongs to zhnnky329/MathModeling-skills. 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/zhnnky329/MathModeling-skills/main/.claude/skills/workflow-orchestrator/SKILL.mdgit clone --depth 1 https://github.com/zhnnky329/MathModeling-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/zhnnky329/mathmodeling-skills/workflow-orchestrator)<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/workflow-orchestrator"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/workflow-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/zhnnky329/mathmodeling-skills/workflow-orchestrator"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/workflow-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01525 |
| Opus 5 | $0.00020 | $0.00763 |
| Sonnet 5 | $0.00008 | $0.00305 |
| Haiku 4.5 | $0.00004 | $0.00153 |
Grade A, and why
workflow-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 12d 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 — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Act as the gate-driven scheduler and state reader. Do not solve models, write model code, or draft paper sections.
../../AGENTS.md is the packaged policy source. Prefer a project-root AGENTS.md when one exists; otherwise read the packaged copy relative to this SKILL.md. Apply that policy without reproducing large reports or dashboards.
Session Start
Before orchestration in a new workspace:
- show
git status --short; - check the chosen runtime and required core packages;
- verify the workspace skeleton needed for the current request;
- read
planning/session_config.json, accepting legacymode.
Report warnings concisely. Do not create the full project skeleton unless the user is initializing a project.
State Sources
Prefer, in order:
planning/manifests/Qx.json- canonical artifacts on disk
- legacy dashboard and legacy method/decision artifacts
Never trust a dashboard over newer canonical artifacts.
Manifest Contract
Maintain one compact JSON manifest per subquestion:
{
"schema_version": 1,
"question_id": "Q1",
"rigor_profile": "lean",
"current_gate": "G2",
"status": "method_screened_waiting_human",
"artifacts": {
"method_card": "methods/Q1/q1_method_card.md",
"decision_ledger": "methods/Q1/q1_decisions.jsonl",
"risk_probe": "methods/Q1/probes/risk_probe_summary.json",
"latest_run": null
},
"allowed": {
"code_generation": false,
"freeze": false,
"paper_writing": false,
"final_assembly": false
},
"blockers": [],
"next_action": {
"owner": "human",
"skill": "decision-prompt-builder",
"reason": "method choice not recorded"
},
"updated_at": "ISO-8601"
}
Update only fields affected by the current state change. Generate a human dashboard on request or at a milestone; otherwise derive status directly from manifests.
Gate Evaluation
Evaluate each Qx independently.
G1 — PROBLEM_FRAMED
Pass when parse, classification, data inventory, success criteria, and human framing exist. A placeholder in a human-owned field blocks the gate.
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.
- 12d ago First seen · 205 lines · 41 tokens per session scan A e21bd791faa4
workflow-orchestrator is a skill published in the GitHub repository zhnnky329/MathModeling-skills (882 stars, last pushed 18d ago), licensed MIT. It adds 41 tokens to every session and 1,525 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 2026-08-30.
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