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 agentmods add skills/levi-qiao/longgraph-skill/loop-delivernpx skills add levi-qiao/longgraph-skill --skill loop-delivergit clone --depth 1 https://github.com/levi-qiao/longgraph-skillWrote 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/levi-qiao/longgraph-skill/loop-deliver)<a href="https://agentmods.dev/skills/levi-qiao/longgraph-skill/loop-deliver"><img src="https://agentmods.dev/badge/skills/levi-qiao/longgraph-skill/loop-deliver.svg" alt="Measured on agentmods" 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 | $0.00084 | $0.00493 |
| Opus 5 | $0.00042 | $0.00246 |
| Sonnet 5 | $0.00017 | $0.00099 |
| Haiku 4.5 | $0.00008 | $0.00049 |
Grade A, and why
loop-deliver 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 5d 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.
What it actually says
loop-deliver — a loop-graph preset for requirements
A thin authoring entry. It binds a requirement-delivery pack, starts the owner
interview, then follows loop-graph to compile the normal
executor, ledger, directives, ops, and supervisor artifacts. It is not a second runtime
and it does not ship a second template set.
Fit check
- Use this when a feature, integration, migration, or behavior change needs several verified slices and an independent acceptance audit.
- Use
../loop-converge/SKILL.mdwhen the goal is code cleanup or consolidation. Use../loop-research/SKILL.mdwhen the decision between approaches is still open. - If the requirement fits one normal host task, say so and send it directly. Do not wrap it in a graph.
On invoke
- Inspect the workspace and current host the same way loop-graph does. Never ask which client this is when context already identifies it.
- Read and bind
preset.md. That pack is the North Star, supervisor requirement, interview, shape, method guards, knob overrides, and artifact emphasis. Do not redesign them. - Start the owner interview immediately. Ask only the pack's unresolved choices — outcome/acceptance, authority, and launch — as recommended A/B (or A/B/C) choices. Do not ask the owner to invent a plan.
- Read and follow
../loop-graph/SKILL.mdfrom When called from a preset skill through generate and deliver. Compile only from loop-graph'stemplates/. This skill never executes the generated nodes.
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.
- 5d ago First seen · 37 lines · 84 tokens per session scan A c91a78078e2d
loop-deliver is a skill published in the GitHub repository levi-qiao/longgraph-skill (71 stars, last pushed 3d ago), licensed MIT. It adds 84 tokens to every session and 493 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 2026-08-30.
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