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 datit309/supergraph --skill executegit clone --depth 1 https://github.com/datit309/supergraphWrote 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/datit309/supergraph/execute)<a href="https://agentmods.dev/skills/datit309/supergraph/execute"><img src="https://agentmods.dev/badge/skills/datit309/supergraph/execute/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/datit309/supergraph/execute"><img src="https://agentmods.dev/badge/skills/datit309/supergraph/execute.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 | $0.00026 | $0.01953 |
| Opus 5.5 | $0.00010 | $0.00781 |
| Sonnet 5.5 | $0.00005 | $0.00391 |
| Haiku 4.5 | $0.00003 | $0.00195 |
Grade A, and why
execute 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/supergraph:execute
Dispatch plan tasks with TDD. Parallel by default when tasks are independent.
Usage: /supergraph:execute | task N | tasks N,M | from task N | plan auth-login task 2 | plan auth-login sequential
Steps
0. Announce
"I'm using /supergraph:execute to implement this plan."
1. Load Context
/supergraph:scanshould already be done. If.supergraph-envmissing → STOP: "Run/supergraph:scanfirst."- Commands from
.supergraph-env(if present) or plan## Environment Context
2. Select Plan
Count plan files in docs/supergraph/plans/*.md:
| Count | Action |
|---|---|
| 0 | STOP: "Run /supergraph:plan first" |
| 1 | Auto-select |
>1, no plan <slug> arg |
STOP: list plans, ask user |
plan <slug> provided |
Match filename. If >1 match ask. |
Parse task scope: task N, tasks N,M,K, from task N, or all incomplete.
Parse sequential flag → force sequential mode.
3. Critical Review
Read plan before dispatch:
- Has
## Environment Context? - Selected tasks have all required fields (Status, Risk, Dependencies, Files, Acceptance, TDD, Steps, Checkpoint)?
- Commands real, not placeholders? File paths exact?
- Plan-reviewer returned
Approved(or user explicitly approved)?
If missing or not Approved → STOP, dispatch supergraph:plan-reviewer, wait for Approval.
Also check: plan has user approval step (step 11)? If not → ask user: "Plan was not reviewed by you. Proceed anyway? [yes / no]"
Check dependencies: Task X depends on Task Y → is Y Status: completed? If not → STOP.
If any concern: STOP, ask. Never guess.
4. Branch Protection
If main/master → STOP, suggest new branch or worktree. User approves → continue.
5. Determine Execution Mode & Group by Waves
Parse tasks from plan:
- Wave-based DAG: Group incomplete tasks by
Wave: N(e.g. Wave 1, Wave 2, Wave 3). - Auto-Wave fallback: If plan lacks
Wave:fields, group tasks dynamically by dependencies:- Wave 1: Tasks with
Dependencies: none. - Wave N: Tasks whose dependencies are all satisfied by Wave < N.
- Wave 1: Tasks with
- Wave Strategy:
- Wave with 1 task → Sequential dispatch.
- Wave with >1 tasks → Parallel dispatch of concurrent subagents.
What ships with it
3 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.
- 4d ago Changed 6d2dd620f8d0
- 6d ago Changed · +17 lines 95c0192ba5d8
- 1mo ago Changed · +10 lines 49c4616aa04b
- 1mo ago Changed · +23 lines 6d5229b09d1a
- 1mo ago First seen · 97 lines · 26 tokens per session scan A bcdf3f43ec8d
execute is a skill published in the GitHub repository datit309/supergraph (22 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 1,953 once invoked, about $0.0001 per session on Opus 5.5. 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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