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Agent context setup

Skill Amey-Thakur/AI-SKILLS/skills/ai-coding-tools/agent-context-setup

Give a coding agent the right files and background at the start of a task, so it works from the real system rather than from assumption. Use when starting a non-trivial task with an agent.From its SKILL.md

Install
npx -y skills add Amey-Thakur/AI-SKILLS --skill agent-context-setup

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

1.8 KB, as published. Nobody here has run it

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 belong in an instruction file rather than being repeated per task (see agent-instruction-files).

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.