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 beel-collab/presets.dev --skill acceptance-orchestratorgit clone --depth 1 https://github.com/beel-collab/presets.devWrote 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/beel-collab/presets.dev/acceptance-orchestrator)<a href="https://agentmods.dev/skills/beel-collab/presets.dev/acceptance-orchestrator"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/acceptance-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/beel-collab/presets.dev/acceptance-orchestrator"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/acceptance-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 | $0.00031 | $0.00831 |
| Opus 5 | $0.00015 | $0.00415 |
| Sonnet 5 | $0.00006 | $0.00166 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
acceptance-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 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.
This is a copy
91% identical to acceptance-orchestrator — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Acceptance Orchestrator
Overview
Orchestrate coding work as a state machine that ends only when acceptance criteria are verified with evidence or the task is explicitly escalated.
Core rule: do not optimize for "code changed"; optimize for "DoD proven".
When to Use
- The task already has an issue or clear acceptance criteria and should run end-to-end with minimal human re-intervention.
- You need structured handoff across implementation, review, deployment, and final verification.
- You want explicit stop conditions and escalation instead of silent partial completion.
Required Sub-Skills
create-issue-gateclosed-loop-deliveryverification-before-completion
Optional supporting skills:
deploy-devpr-watchpr-review-autopilotgit-ship
Inputs
Require these inputs:
- issue id or issue body
- issue status
- acceptance criteria (DoD)
- target environment (
devdefault)
Fixed defaults:
- max iteration rounds =
2 - PR review polling =
3m -> 6m -> 10m
State Machine
intakeissue-gatedexecutingreview-loopdeploy-verifyacceptedescalated
Workflow
-
Intake
- Read issue and extract task goal + DoD.
-
Issue gate
- Use
create-issue-gatelogic. - If issue is not
readyor execution gate is notallowed, stop immediately. - Do not implement anything while issue remains
draft.
- Use
-
Execute
- Hand off to
closed-loop-deliveryfor implementation and local verification.
- Hand off to
-
Review loop
- If PR feedback is relevant, batch polling windows as:
- wait
3m - then
6m - then
10m
- wait
- After the
10mround, stop waiting and process all visible comments together.
- If PR feedback is relevant, batch polling windows as:
-
Deploy and runtime verification
- If DoD depends on runtime behavior, deploy only to
devby default. - Verify with real logs/API/Lambda behavior, not assumptions.
- If DoD depends on runtime behavior, deploy only to
-
Completion gate
- Before any claim of completion, require
verification-before-completion. - No success claim without fresh evidence.
- Before any claim of completion, require
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 · 118 lines · 31 tokens per session scan A 6eb38a23c639
acceptance-orchestrator is a skill published in the GitHub repository beel-collab/presets.dev (3 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 831 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to acceptance-orchestrator, differing in 19 lines, and is treated as a copy.
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to-spec
Turn the current conversation context into a spec and submit it as a GitHub issue. Use when user wants to create a spec or PRD from the current context.
qa-to-issues
Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Use when user wants to report bugs in their own codebase and create Github issues conversationally.