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[aw] Matt Pocock Skills Reviewer: has an unavailable configured model

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  • ¿Algo no está bien?
#697 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Nadie ha tomado este issue todavía.

Evaluación

Dificultad
2/5
Tiempo estimado
1-3 horas
Aptitud para principiantes
57/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
github, github-actions, typescript
Área
ai-infra-agents, ci-cd

Línea de trabajo

Start with .github/workflows/mattpocock-skills-reviewer.md on branch pelikhan-agentic-engine-upgrades and inspect the failed run’s model configuration and logs. Check which models are available to the agentic-workflows integration for that run context. Done means the workflow selects a supported model and a rerun completes; the issue does not identify the model currently configured or name a test.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

agentic-workflows
What happened

Matt Pocock Skills Reviewer has an unavailable configured model.

View run #39691205577 · Workflow source · Previous failures

Branch: pelikhan-agentic-engine-upgrades

Next step

Review the failure details below for a targeted fix, or assign this issue to a coding agent to investigate.

Failure details

[!WARNING]
Model Not Supported: The requested model was rejected by the provider for this request.

This may be an invalid model name, a policy or access restriction for this token/repository, or a change in provider availability. Retrying the same session will not resolve a model that remains unavailable.

Copilot also filters models by integration. A model enabled by organization policy and available in the standalone CLI can still be unavailable to the agentic-workflows integration. In particular, Gemini models have been absent from that integration's catalog. The bundled gh-aw model catalog is not proof of live access. Select a model offered to this workflow; enabling a missing model for agentic-workflows requires Copilot API support. Do not change the integration ID to bypass access policy.

How to fix this

Specify a valid model for the selected engine in the workflow frontmatter:

---
engine: copilot
model: gpt-5-mini
---

To find valid models, check your engine/provider documentation (for Copilot see supported models) and the model catalog returned for the failing token/context.

If the model previously worked with the same workflow and token type, compare the successful and failing runs' model catalogs and request context. If the catalog changed, share sanitized timestamps, repository/organization context, and Copilot service request IDs with the Copilot model-access support team. Do not share tokens.

If the error text is No model available. Check policy enablement under GitHub Settings > Copilot, the model is not disabled in the workflow but by Copilot policy. Enable the model under GitHub Settings > Copilot > Policies for the org/repo, or pick a model that is already enabled. This can also be triggered by a subagent (task tool) dispatch requesting a model that the policy does not allow, even when the main agent's model is enabled.

[!WARNING]
Engine Failure: The copilot engine terminated unexpectedly.

Error details: 
Driver exit code: 1

Review the workflow run logs for diagnostics. Raw agent output is omitted because it may contain secrets.

Copy a debugging prompt

Paste this into your coding agent:

Debug the agentic workflow "mattpocock-skills-reviewer" failure.
Follow https://raw.githubusercontent.com/github/gh-aw/main/debug.md
Failed run: https://github.com/githubnext/rig/actions/runs/39691205577

If the repository includes the agentic-workflows skill, load it before investigating.

Manage failure notifications

To stop creating failure issues for this workflow, set this in its frontmatter and recompile:

safe-outputs:
  report-failure-as-issue: false

This only disables issue reporting; it does not fix the failure.

Generated from Matt Pocock Skills Reviewer · ◷

  • expires on Oct 28, 2026, 11:10 PM UTC
Lenguaje dominante
TypeScript
Estrellas
14
Forks
0
Merge medio
9 h 27 min
PR fusionados (30 d)
34

Preparar el entorno

Este proyecto no incluye contenedor de desarrollo, Dockerfile ni guía de contribución, así que la configuración corre por tu cuenta: empieza por su README y consulta nuestra guía para la primera contribución para los pasos generales.

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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