| name | evaluar-contexto-necesario |
| description | Use when preparing a complex task for an AI agent. Evaluates what files, examples, or templates should be attached as context to get the best result. Invoke with: /evaluar-contexto-necesario, what context do I need, prepare context, context for agent, attach files. |
| argument-hint | Describe the task you are about to run (e.g. 'train a classifier on the Iris dataset') |
| user-invocable | true |
Skill: evaluar-contexto-necesario
Evaluate and recommend the context that should be attached to a complex AI agent task.
Steps
1. Parse the Task
- Restate the task in one sentence.
- Identify: what code will be created or modified, what data will be used, what output is expected.
2. Apply the Context Checklist
Work through references/context-checklist.md for the task.
3. Recommend Files to Attach
- List specific files from the project that the agent will need.
- Prioritise: spec > existing implementation > tests > examples.
- Explain why each file is needed (not just list them).
4. Warn About Context Size
- If the total estimated tokens of recommended files exceeds ~8 000, flag it.
- Suggest pruning: "You need only the
train() function from train_model.py, not the whole file."
5. Flag Missing Context
- If the task requires information that does not exist yet (a spec, a schema, an example), say so explicitly: "You should first create
doc/spec.md using the spec-a-tareas skill."
Output
A prioritised list of files to attach with justifications, plus a warning if context would be too large.
