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.
git clone --depth 1 https://github.com/ricneves-ai/flowgrammers-skillsWrote 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/commands/ricneves-ai/flowgrammers-skills/acceptance-criteria)<a href="https://agentmods.dev/commands/ricneves-ai/flowgrammers-skills/acceptance-criteria"><img src="https://agentmods.dev/badge/commands/ricneves-ai/flowgrammers-skills/acceptance-criteria/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/commands/ricneves-ai/flowgrammers-skills/acceptance-criteria"><img src="https://agentmods.dev/badge/commands/ricneves-ai/flowgrammers-skills/acceptance-criteria.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 | $0.00000 | $0.02404 |
| Opus 5 | $0.00000 | $0.01202 |
| Sonnet 5 | $0.00000 | $0.00481 |
| Haiku 4.5 | $0.00000 | $0.00240 |
Grade A, and why
acceptance-criteria 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- acceptance-criteria — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/acceptance-criteria
O que essa skill faz
Gera critérios de aceite estruturados em formato Given/When/Then (Gherkin) cobrindo happy path, edge cases, e casos de erro.
Saída: 5-10 cenários prontos para QA e eng usarem como test cases.
Quando usar
- User story aprovada, precisa detalhar validações
- Vai passar para QA — precisa ter explícito o que testar
- Feature tem regras de negócio complexas
Input esperado
Mínimo:
- Feature ou user story: O que está sendo testado
- Regras de negócio: Constraints, validações, edge cases
- Contexto: Que dados já existem
Opcional:
- Design mockup (para validações visuais)
- Casos de erro conhecidos
- Performance requirements
Processo
- Happy path — Fluxo ideal, tudo certo
- Edge cases — Variações que são válidas mas diferentes
- Error cases — Entradas inválidas, o que fazer?
- Performance/Scale — Se relevante, como se comporta em volume?
- Accessibility — Pode ser usado por screenreader?
Output
# Acceptance Criteria: [Feature Name]
## Cenário 1: Happy Path — [Descrição]
```gherkin
Given que [pré-condição/contexto inicial]
When [ação do usuário]
Then [resultado esperado]
And [validação adicional]
And [outra validação]
Notas para QA
- [Se há screenshot esperada, descreva]
- [Se há performance expectativa, mencione]
- [Qualquer detalhe visual importante]
Cenário 2: Happy Path Alternativo — [Variação]
Given que [contexto diferente do cenário 1]
When [ação similar]
Then [resultado diferente]
Notas para QA
[...]
Cenário 3: Edge Case — [Situação limite]
Given que [contexto especial]
When [ação que toca limite]
Then [comportamento esperado para limite]
Cenário 4: Error — [Erro esperado]
Given que [contexto que leva a erro]
When [ação que causa erro]
Then [mensagem de erro clara é mostrada]
And [campo fica highlighted]
And [user pode corrigir facilmente]
Cenário 5...N
[Mesmo formato]
Casos de teste por categoria
Validação de entrada
- Campo vazio
- String muito longa
- Caracteres especiais
- Números onde esperado texto
Fluxo de negócio
- Happy path completo
- Cancelamento/Back
- Reentrar dados
- Dados pré-populados
Estado do sistema
- Primeira vez usando feature
- Segunda vez (dados existem)
- Com dados muito antigos
- Em volume alto (performance)
Integração
- Com outros módulos
- Com dados de terceiros (API)
- Efeitos colaterais (emails, webhooks)
Acessibilidade
- Navegável via tab/keyboard
- Legível com screenreader
- Contraste adequate
- Mobile responsivo
Definição de Pronto
Feature está aceita quando:
- ✅ Todos os cenários passaram (manual ou automatizado)
- ✅ Sem erros em console/logs
- ✅ Performance dentro da spec
- ✅ Mobile funcionando
- ✅ PM fez sign-off em staging
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.
- 9d ago First seen · 370 lines · 0 tokens per session scan A 03f582cf8776
acceptance-criteria is a command published in the GitHub repository ricneves-ai/flowgrammers-skills (112 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,404 tokens. 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 2026-09-03.
Other commands, from other repositories
prototype
You are building a proof-of-concept for the current Grainulator sprint. Read CLAUDE.md for sprint context and claims.json for existing research claims.
qa-changes
This skill should be used when the user asks to "QA a pull request", "test PR changes", "verify a PR works", "functionally test changes", or when an automated workflow triggers QA validation of code changes. Provides a structured methodology for setting up the environment, exercising changed behavior, and reporting…
verify
Run repository verification using the verification-loop skill.
test-coverage
Analyze test coverage and identify the highest-value gaps to fill.
tdd
A command that follows test-driven development (TDD), a method where you write tests before the code they check. It moves through writing a failing test, adding the smallest implementation, and then improving the code.
check-dev
Type-check a Z specification with fuzz.