acceptance

acceptance is a skill for Claude Code from juicesharp/rpiv-mono. It costs 122 tokens per session (1,937 once invoked), scanned A, original, MIT.

A tool that turns a written project goal into a checklist of observable acceptance conditions, each with a short ID and, when possible, a command that can verify it. The checklist is saved under .rpiv/artifacts/acceptance/.

In plain words
What is it for?
Use it to extract testable outcomes from a brief, record evidence commands, and create an acceptance inventory in one non-interactive pass.
Why use it?
It makes the definition of finished work explicit before planning begins, so later implementation and testing can be checked against the original goal.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions subagents.

Good fit Use it to extract testable outcomes from a brief, record evidence commands, and create an acceptance inventory in one non-interactive pass.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/juicesharp/rpiv-mono/acceptance
Install

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.

Any agent
npx skills add juicesharp/rpiv-mono --skill acceptance
Clone the repo
git clone --depth 1 https://github.com/juicesharp/rpiv-mono

Made for: Claude Code.

Wrote 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.

agentmods badge for acceptance

README.md
[![agentmods](https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/acceptance/github.svg)](https://agentmods.dev/skills/juicesharp/rpiv-mono/acceptance)
Your own site
<a href="https://agentmods.dev/skills/juicesharp/rpiv-mono/acceptance"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/acceptance/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.

agentmods 80×15 button for acceptance

Your own site · 80×15
<a href="https://agentmods.dev/skills/juicesharp/rpiv-mono/acceptance"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/acceptance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,937 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00122 $0.01937
Opus 5 $0.00061 $0.00968
Sonnet 5 $0.00024 $0.00387
Haiku 4.5 $0.00012 $0.00194

Measured 11d ago against content hash 33c354b6ea60, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

acceptance 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 11d 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.

packages/rpiv-pi/skills/acceptance/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Acceptance

You derive an acceptance inventory from the verbatim goal: the distinct observable outcomes the finished work must exhibit, each with a short stable id (a1, a2, …) and — wherever one can be derived — a runnable evidence command that will exit 0 once the outcome holds. One non-interactive pass, one Write. You do not plan, design, or judge feasibility — the inventory is the measure the later stages answer to, not a plan of how to get there.

The inventory exists to keep the standard of completion independent of the work: it is authored before any plan, from the goal alone, so a plan that silently narrows the brief is caught against enumerated items instead of prose re-reading. Downstream: the planner addresses or explicitly defers each item, the grade panel's completeness dimension receives the inventory as --acceptance, and validate runs the evidence commands against the finished tree — a failed item with a runnable command becomes a structured, remediable blocker.

Input

$ARGUMENTS — flags (order-independent):

  • --goal <path> (required) — the verbatim brief. Read it FULLY (no limit/offset). Missing/empty ⇒ print an error and stop — a dispatch error (the workflow runs goal before acceptance).
  • --research <path> (optional) — the grounding doc. Read it FULLY. Research grounds only the evidence procedures (which command, which test path, which grep target); it NEVER adds, drops, or narrows items — the item set derives from the goal alone.

Metadata

node "${SKILL_DIR}/../_shared/now.mjs"
echo
node "${SKILL_DIR}/../_shared/git-context.mjs"

Copy values verbatim. <iso> is the first tab-separated field (use as date:); <slug> is the second.

What an item is

An acceptance item is one observable outcome the goal asks for — behavior a reader could check on the finished tree, not an implementation step. Good items are:

  • Goal-traceable — the statement restates one explicit ask (or explicit constraint) from the goal in one line; quote or closely paraphrase the goal's own words. Never invent scope the goal doesn't name (the graders' anti-scope-inflation rule applies here first).
  • Observable — phrased as a checkable end state ("/wf ship halts at the grade gate with a route note"), never as activity ("implement the gate").
  • Singular — one outcome per item; a goal sentence naming two outcomes yields two items.
  • Right-sized set — typically 3–12 items; every explicit ask is covered, and nothing is padded. A one-line goal may legitimately yield a single item. The schema's hard ceiling is 24 — deliberately tighter than the plan/slice family's 32, because an inventory that large is re-litigating scope, not enumerating a brief; a goal genuinely that broad belongs in build's slice decomposition, with each slice's asks staying items here only at the observable-outcome grain.

Read the full file on GitHub · 124 lines

Changes

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.

  1. 11d ago First seen · 124 lines · 122 tokens per session scan A 33c354b6ea60

Subscribe to this mod's changes

acceptance is a skill published in the GitHub repository juicesharp/rpiv-mono (773 stars, last pushed 2d ago), licensed MIT. It adds 122 tokens to every session and 1,937 once invoked, about $0.0006 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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