prepare-acceptance

prepare-acceptance is a skill for Claude Code, Codex from Codagent-AI/agent-skills. It costs 58 tokens per session (3,820 once invoked), scanned A, original, MIT.

A testing and evidence workflow for preparing a completed change for human acceptance. It exercises the product through real user or client flows, reports defects without fixing them, checks current-head CI, and summarizes evidence.

In plain words
What is it for?
Use it before acceptance to test the agreed scenarios, document defects, wait for CI when appropriate, and prepare a concise handoff for a reviewer.
Why use it?
It separates realistic flow testing from implementation and automated fixes, making it clearer whether the delivered change is ready for human review. It also keeps the evidence tied to the code currently checked out.

Skill for Claude CodeCodex

Part of the codagent plugin — 27 skills shipped together

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.

agentmods
npx agentmods add skills/codagent-ai/agent-skills/prepare-acceptance
Any agent
npx skills add Codagent-AI/agent-skills --skill prepare-acceptance
Clone the repo
git clone --depth 1 https://github.com/Codagent-AI/agent-skills

Made for: Claude Code, Codex.

Or install codagent, the plugin that ships this one along with the rest of its 27 skills.

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 prepare-acceptance

README.md
[![agentmods](https://agentmods.dev/badge/skills/codagent-ai/agent-skills/prepare-acceptance.svg)](https://agentmods.dev/skills/codagent-ai/agent-skills/prepare-acceptance)
Your own site
<a href="https://agentmods.dev/skills/codagent-ai/agent-skills/prepare-acceptance"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/prepare-acceptance.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,820 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00058 $0.03820
Opus 5 $0.00029 $0.01910
Sonnet 5 $0.00012 $0.00764
Haiku 4.5 $0.00006 $0.00382

Measured 5d ago against content hash 79e4eeaee497, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

prepare-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 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.

skills/prepare-acceptance/SKILL.md · 281 lines

How it starts

The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prepare Acceptance

Prepare an implemented change for a separate human acceptance session. Exercise it as a human user or real client would, report clear defects, wait for CI once no defects remain, and produce concise evidence for the code currently checked out. Fixes and automated validation belong to separate caller-managed steps when used. PR and commit identity establish final CI and handoff alignment; they are not prerequisites for exercising the product.

Required inputs

Resolve these from the caller before acting:

  • approved requirements, scenarios, design, test plan when one exists, and task artifacts;
  • caller-supplied implementation summary or completion evidence identifying delivered behavior;
  • evidence output directory;
  • unresolved-assumptions ledger path, when one exists;
  • verification scope:
    • full;
    • targeted, naming the affected flows, directly dependent flows, a concise impact rationale, and prior full-pass evidence to retain, plus the caller's attestation that this scope covers the tracked changes since that baseline; or
    • evidence-only, identifying prior flow evidence whose coverage revision exactly matches the current tracked contents and supplying the caller's attestation of that content match.

If source-of-truth artifacts or the evidence directory are missing, report what is missing and stop before flow execution. Do not infer product behavior from implementation alone. When an approved test plan exists, treat its required and activated conditional AT-* flows, evidence requirements, authorized effects, and permitted substitutes as authoritative. Use full when the caller does not supply a scope or no trustworthy full-pass baseline exists. Targeted and evidence-only reuse depend on the caller's impact or content attestation: reconcile it with the approved flow inventory, but do not independently inspect a diff. Use evidence-only only when the caller attests that no tracked product contents changed after the recorded coverage revision; PR alignment, pushing the already-tested commit, waiting for CI, or a Validator run that made no tracked change do not invalidate flow evidence. When no assumptions-ledger path is supplied, use <evidence-directory>/acceptance-assumptions.md and create it if needed. Keep this preparation autonomous: preserve product, scope, or design ambiguity for the later human acceptance session instead of asking the user here.

Read the full file on GitHub · 281 lines

Files

What ships with it

1 file 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.

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. 5d ago First seen · 281 lines · 58 tokens per session scan A 79e4eeaee497

Subscribe to this mod's changes

prepare-acceptance is a skill published in the GitHub repository Codagent-AI/agent-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 3,820 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

use-agent-browser-for-airi

Test AIRI display-model imports with agent-browser across stage-tamagotchi Electron, stage-web, and stage-pocket mobile web layouts. Use when uploading and verifying contributor-supplied Live2D ZIP, VRM, or MMD ZIP/PMX/PMD files through AIRI's model selector, including onboarding bypass, format-specific import…

moeru-ai/airi · 87 tokens

run-integration-tests

Build, pack, and run .NET MAUI integration tests locally. Validates templates, samples, and end-to-end scenarios using the local workload.

dotnet/maui · 35 tokens

cli-e2e-testcase-writer

Use when adding or updating Go CLI E2E coverage for one tests/clie2e/{domain} domain of the compiled lark-cli, especially when the work requires live --help or schema exploration, scenario-based clie2e.RunCmd workflows, and per-domain coverage.md maintenance.

larksuite/cli · 78 tokens

webapp-testing

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

every-app/open-seo · 35 tokens

harness-test-writer

Add regression test cases to the Bifrost provider harness (the Postman collection run via make run-provider-harness-test) based on a merged PR or a GitHub issue. Fetches the PR/issue, traces the affected wire path in the codebase, checks existing harness coverage, designs cases following harness conventions, inserts…

maximhq/bifrost · 133 tokens

agent-device-evidence

Records iOS/Android native MP4 evidence for test/repro flows extracted from an Expensify GitHub PR or issue. Use when the user asks to "record the flow for PR.

Expensify/App · 43 tokens