| name | agent-authoring |
| description | Guidance on writing high-quality skills and prompt templates. Use when creating, reviewing, or improving agent instructions. Triggers on "write a skill", "create a prompt template", "capture skill", "capture template", "review skills", "deprescribe", or any agent authoring task. |
Agent Authoring
Guidance for writing skills and prompt templates that are concise, intent-focused, and effective.
Where to Save Skills
Canonical path: ../../<category>/<skill-name>/SKILL.md
Categories:
seed/ — thinking, inquiry, concept work (e.g. untangle-concept, cognitive-motion)general/ — cross-domain utilities (e.g. agent-authoring, conversation-capture)engineering/ — code and repo workflows (e.g. plan, explore-design-space)
After creating a skill, register it in aspects/dotfiles/index.ts under the skills array so fig deploys it.
Prompt templates: ~/.dotfiles/aspects/dotfiles/files/.agents/prompts/<name>.md — thin wrappers that invoke a skill. Register in index.ts under prompts. Use $ARGUMENTS for user input passed after the slash command.
Do not save skills to ~/.claude/skills/ directly — that path is deployed from dotfiles.
Core Principle
State what to achieve and why, not how to execute. Trust the agent to figure out mechanics.
Too prescriptive:
Step 1: Run git log to find the commit.
Step 2: Run git cherry-pick <hash>.
Step 3: If there are conflicts, run git status to list them.
Better:
Cherry-pick the commit onto a clean branch. Resolve conflicts preserving intent. If it can't land cleanly, explain why.
Degrees of Freedom
Match specificity to the task's fragility. Not everything should be loose.
- High freedom: multiple valid approaches, context-dependent decisions. State intent: "Review the code for bugs, edge cases, and convention adherence."
- Low freedom: fragile operations where consistency is critical. Be exact: "Run
scripts/migrate.py --verify --backup. Do not modify the command."
Most skills should be high freedom. Use low freedom only for operations that break when done differently.
What to Include
- Intent and constraints: what the agent should achieve, what it must avoid
- Domain knowledge the agent lacks: CLI syntax for unfamiliar tools, API quirks, format requirements
- Safety rules and hard constraints: these are not prescription, they're boundaries
- Output expectations: what the result should look like
- Gotchas: list non-obvious traps instead of dictating workflows ("the
/health endpoint returns 200 even if the DB is down; use /ready")
What to Omit
- Step-by-step execution: "Run X, then run Y, then check Z"
- Tool instructions the agent already knows: how to use git, how to read files, how to check if something exists
- Parallelism hints: "run these in parallel" / "run multiple tool calls"
- Obvious behavior: "analyze the output" / "review the results"
Writing Well
- Lead with a paragraph stating what the skill does, then add structure only where needed
- Keep skills short. If it's over 50 lines, ask whether every line earns its place
- CLI reference material (commands, flags, examples) is fine at any length. That's knowledge, not prescription.
- Use the same judgment for prompt templates: describe the task and constraints, not the keystrokes
Trailing Steps Get Skipped
A step that sits late in the skill, delays the deliverable, and produces no visible output is the one the model silently drops (a late verification or monitoring step loses the attention competition against the immediate result). For such steps:
- Give a concrete entry action so the step has a trigger.
- Require a visible output artifact so a skip is detectable.
- State the stop condition as a hard constraint ("do not report done until X is shown"), not a suggestion.
