acceptance-pipeline-feature-design

acceptance-pipeline-feature-design is a skill for Claude Code, Codex from pproenca/dot-skills. It costs 111 tokens per session (1,230 once invoked), scanned A, original, MIT.

A design guide for extending Uncle Bob's Acceptance Pipeline Specification, a specification for running acceptance tests through defined processing stages. It describes new mutation methods, Gherkin syntax, report formats, pipeline stages, and internal data fields without choosing an implementation.

In plain words
What is it for?
Use it when designing new acceptance-pipeline features such as data tables, tags, mutation strategies, JSON fields, HTML or JUnit reports, parallel runs, or coverage filtering.
Why use it?
It helps keep changes precise and compatible across the parser, internal data model, processing stages, handlers, and reports.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when designing new acceptance-pipeline features such as data tables, tags, mutation strategies, JSON fields, HTML or JUnit reports, parallel runs, or coverage filtering.

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Install with agentmods
npx agentmods add skills/pproenca/dot-skills/acceptance-pipeline-feature-design
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 pproenca/dot-skills --skill acceptance-pipeline-feature-design
Clone the repo
git clone --depth 1 https://github.com/pproenca/dot-skills

Made for: Claude Code, Codex.

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-pipeline-feature-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/pproenca/dot-skills/acceptance-pipeline-feature-design/github.svg)](https://agentmods.dev/skills/pproenca/dot-skills/acceptance-pipeline-feature-design)
Your own site
<a href="https://agentmods.dev/skills/pproenca/dot-skills/acceptance-pipeline-feature-design"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/acceptance-pipeline-feature-design/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-pipeline-feature-design

Your own site · 80×15
<a href="https://agentmods.dev/skills/pproenca/dot-skills/acceptance-pipeline-feature-design"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/acceptance-pipeline-feature-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 111 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,230 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 $0.00111 $0.01230
Opus 5 $0.00056 $0.00615
Sonnet 5 $0.00022 $0.00246
Haiku 4.5 $0.00011 $0.00123

Measured 11d ago against content hash b7b7931c5d74, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

acceptance-pipeline-feature-design 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.

skills/.experimental/acceptance-pipeline-feature-design/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Acceptance Pipeline Feature Design

Guides agents through designing new features that extend Uncle Bob's Acceptance Pipeline Specification. Produces spec-quality output — language-neutral, implementation-agnostic, with precise behavioral requirements — that matches the style and rigor of the original spec.

This is a composition skill. It does not catalog what exists (that is acceptance-pipeline-catalog's job). Instead, it provides a structured workflow for designing what comes next.

When to Apply

  • Designing a new mutation strategy, value type, or filter mechanism for the mutator
  • Adding new Gherkin syntax support (data tables, tags, Rules keyword) to the parser
  • Extending the JSON IR with new fields or objects
  • Creating new report formats (HTML, JUnit XML) or output channels
  • Adding new pipeline stages or operating modes (parallel runs, coverage filtering)
  • Any spec-level change that affects multiple pipeline components (cross-cutting)

Prerequisite

Before using this skill, ensure acceptance-pipeline-catalog is available. That skill provides the baseline reference for the 9 required components, JSON IR schema, conformance checklist (21 items), and agent setup checklist (15 steps). This skill builds on top of that foundation.

Workflow Overview

The workflow has five phases, executed in order. Each phase builds on the output of the previous one — skipping phases produces incomplete or inconsistent designs.

Phase 1: Survey Existing Spec     → Know what exists before proposing changes
Phase 2: Identify Extension Point → Classify where the feature attaches
Phase 3: Draft Feature Spec       → Write the spec section in Uncle Bob's style
Phase 4: Conformance Design       → Add testable conformance items
Phase 5: Impact Analysis          → Assess backward compatibility and migration

Why this order matters:

  • Phase 1 prevents reinventing existing capabilities and ensures the design uses established patterns.
  • Phase 2 forces classification before writing — a parser extension has different constraints than a reporter extension.
  • Phase 3 produces the actual spec text, informed by the classification from Phase 2.
  • Phase 4 ensures the feature is testable from outside the implementation — if you cannot write conformance items, the spec is too vague.
  • Phase 5 comes last because you need the complete spec and conformance items to assess impact accurately.

Read the full file on GitHub · 95 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 · 95 lines · 111 tokens per session scan A b7b7931c5d74

Subscribe to this mod's changes

acceptance-pipeline-feature-design is a skill published in the GitHub repository pproenca/dot-skills (206 stars, last pushed 26d ago), licensed MIT. It adds 111 tokens to every session and 1,230 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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