agent-context-setuplisted
Install: claude install-skill Amey-Thakur/AI-SKILLS
# Agent context setup
An agent's output quality is bounded by what it knows about your
codebase. Most disappointing results come from an agent guessing at
conventions and interfaces it was never shown.
## Method
1. **Point at the relevant files explicitly.** Naming the modules
involved beats hoping the agent searches well, and it saves several
exploratory turns.
2. **Include one example of the pattern to follow.** An existing
similar implementation communicates conventions faster than any
description (see few-shot-examples).
3. **State the constraint that is not visible in code.** Performance
requirements, compatibility commitments, and decisions already made
and rejected.
4. **Give the failure, not the diagnosis, when debugging.** The actual
error, stack trace, and reproduction, rather than your theory, which
anchors the agent on your assumption (see debugging).
5. **Keep context focused.** Loading the whole repository degrades
attention on what matters (see context-compression).
6. **Let the agent explore for discovery tasks.** When the question is
how something works, searching is the task rather than overhead.
7. **Restate the goal when the session drifts long.** Long sessions lose
the original objective, and a mid-course restatement is cheap (see
staying-on-task).
## Boundaries
Context improves output and cannot supply capability the model lacks.
Very large contexts degrade rather than improve results.
Repository-wide instructions