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/josemerca/mercadona-user-story-toolkitWrote 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/josemerca/mercadona-user-story-toolkit/validate-stories)<a href="https://agentmods.dev/commands/josemerca/mercadona-user-story-toolkit/validate-stories"><img src="https://agentmods.dev/badge/commands/josemerca/mercadona-user-story-toolkit/validate-stories/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/josemerca/mercadona-user-story-toolkit/validate-stories"><img src="https://agentmods.dev/badge/commands/josemerca/mercadona-user-story-toolkit/validate-stories.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 | $0.00018 | $0.00511 |
| Opus 5 | $0.00009 | $0.00255 |
| Sonnet 5 | $0.00004 | $0.00102 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
validate-stories 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 12d 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.
What it actually says
Paso 0 (obligatorio): Cargar ground-rules. Antes de proceder, lee
shared-config.mdy aplica:
- §Filosofía del Plugin — modo copiloto, NO inventar, preguntar antes de generar
- §Estilo de Escritura — frases ≤30 palabras, sin adjetivos sin datos, NUNCA inventar métricas
- §Antipatrones Compartidos — los 7 antipatrones a detectar
Si no puedes leer el fichero, detén la ejecución y reporta el problema.
Ejecuta /user-story-quality-coach para validar stories generadas.
Input necesario: User stories a validar (de /stories o de tu issue tracker).
Regla feedback-flip (obligatoria)
Antes de empezar, decide el modo de ejecución según la procedencia de las stories:
| Procedencia | Modo |
|---|---|
Generadas en ESTA sesión vía /stories, /build-story, /from-gsd |
Sub-agente fresco obligatorio |
| Pegadas, fichero externo, issue tracker, sesión previa | Sesión actual válida |
Por qué: si el revisor ya vio cómo se generó la story, justifica las decisiones en lugar de cuestionarlas. Lada Kesseler — feedback-flip.
Si toca sub-agente fresco: dispatcha con Agent (subagent_type=general-purpose) pasando sólo:
- La ruta
skills/user-story-quality-coach/SKILL.md - Las stories serializadas en markdown
- Instrucción: "NO uses el contexto previo de generación. Trata estas stories como si vinieran de un repositorio externo."
Proceso (dentro del agente que ejecute la validación):
- Leer el SKILL.md de
skills/user-story-quality-coach/ - Para cada story:
- Evaluar scoring 6 dimensiones (usar
scripts/score_story.py) - Detectar antipatrones (7 tipos)
- Generar reporte individual
- Evaluar scoring 6 dimensiones (usar
- Si hay múltiples stories (sprint/backlog):
- Generar reporte de equipo
- Comparar con histórico
- Identificar patrones de mejora
Output: Reporte de calidad con scoring + antipatrones + recomendaciones.
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.
- 12d ago First seen · 45 lines · 18 tokens per session scan A 2557b9d3b639
validate-stories is a command published in the GitHub repository josemerca/mercadona-user-story-toolkit (25 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 511 once invoked, about $0.0001 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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