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 granoflow/granoflow-mcp-server --skill granoflow-skill-orchestratorgit clone --depth 1 https://github.com/granoflow/granoflow-mcp-serverWrote 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/granoflow/granoflow-mcp-server/granoflow-skill-orchestrator)<a href="https://agentmods.dev/skills/granoflow/granoflow-mcp-server/granoflow-skill-orchestrator"><img src="https://agentmods.dev/badge/skills/granoflow/granoflow-mcp-server/granoflow-skill-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/granoflow/granoflow-mcp-server/granoflow-skill-orchestrator"><img src="https://agentmods.dev/badge/skills/granoflow/granoflow-mcp-server/granoflow-skill-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 | $0.00082 | $0.01003 |
| Opus 5 | $0.00041 | $0.00502 |
| Sonnet 5 | $0.00016 | $0.00201 |
| Haiku 4.5 | $0.00008 | $0.00100 |
Grade A, and why
granoflow-skill-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 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Granoflow Skill Orchestrator
Coordinates read-only quality inventory of skills/* in this MCP server,
then proposes a recommendation plan. Uses skill-polish / skill-validate /
skill-steward / skill-authoring only when appropriate and after human
confirmation. Default: report only — no skill rewrites.
Keyword
#mcp-skill-orchestrate#skill-audit#polish-plan
When to use
- User wants to optimize / audit all or selected bundled MCP skills.
- User asks to apply
skill-polishseries to this repo without breaking contracts. - Need a recommendation bucket (
keep/steward_audit/polish_candidate/ …) before any write.
Not this Skill
| Concern | Owner |
|---|---|
| Product task Analysis/Plan/run | granoflow-task-orchestrator |
| New skill from interview | external skill-authoring full pipeline |
| Project definition / Baseline | granoflow-project-definition |
Hard Gates
- Report first. Run the audit script; show Markdown report; wait for human accept / revise of recommendation buckets.
- No silent polish. Mature skills default to
keep.polish_candidaterequires draft smells and a design lock (or explicit user-supplied design). Never polish by guessing. - Preserve effect. Hard Gates, fail-closed codes, and App admission rules must survive any later apply step.
- Apply is gated.
--apply-planrefuses unlessstatus: confirmed; this release still does not auto-mutate — confirmed apply is agent-executed skill-by-skill after human approval.
Workflow
1. Inventory + audit (read-only)
python3 skills/granoflow-skill-orchestrator/scripts/mcp_skill_orchestrate.py
Optional: --skill <id> (repeatable), --json-out, --md-out.
Success criteria:
temp/mcp-skill-orchestrate-report.jsonand.mdwritten.- stdout JSON has
awaiting_human_confirmation: true.
What ships with it
4 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.
- 10d ago First seen · 125 lines · 82 tokens per session scan A b792a8e1996c
granoflow-skill-orchestrator is a skill published in the GitHub repository granoflow/granoflow-mcp-server (0 stars, last pushed 1mo ago), licensed MIT. It adds 82 tokens to every session and 1,003 once invoked, about $0.0004 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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