| name | skill-author |
| description | Draft a well-formed new skill (a SKILL.md scaffold, optionally with scripts/references) from a described recurring need, for human review and approval. Use whenever a repeated workflow gap has no existing skill covering it, when someone wants to propose or create a new skill or capability, or when an agentic system detects a recurring problem that warrants a brand-new skill rather than editing an existing one. Domain-general — works for any modeling or workflow domain; SWMM is just one example. |
Skill author
Turn a description of a recurring need into a draft skill that a human can review and approve. This skill writes proposals; it never installs, activates, or edits skills on its own — a freshly drafted skill is a proposal, not a verified capability.
It is domain-general: nothing here is specific to stormwater or SWMM. The same recipe produces a skill for any modeling or workflow domain.
When to use
- A recurring problem keeps showing up and no existing skill covers it — the gap itself is the trigger to propose a new one.
- Someone asks to "create / propose / draft a new skill" for some capability.
- An agentic system (e.g. a memory or lessons-learned layer) flags a repeated pattern that warrants a new skill rather than a tweak to an existing one.
If an existing skill already covers most of the need, improve that one instead — don't create a near-duplicate (see step 2).
How to draft a skill
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Capture intent. Pin down three things before writing: (a) what should this skill let the agent do? (b) when should it trigger — what phrases or contexts? (c) what does it produce (output format)? Pull answers from the conversation or the evidence you were handed; only ask the human for what's genuinely missing.
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Check for overlap first. List the existing skills and check whether one already does most of this. If so, propose refining that skill instead of adding a new one — avoiding skill sprawl keeps the library discoverable.
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Fill the template. Copy assets/SKILL.template.md and fill it in. The two fields that matter most:
name — kebab-case, matches the folder name.
description — this is how the agent decides to use the skill, so make it specific and slightly pushy: say what it does AND the concrete situations it should trigger in. A vague description means the skill never fires.
Keep the body lean and explain the why behind each instruction — a capable model follows reasoning better than rigid ALL-CAPS rules. See references/skill-format.md for the full recipe (anatomy, progressive disclosure, writing patterns).
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Validate. Run the checker and fix anything it flags:
python3 scripts/validate_skill.py path/to/draft-skill
It confirms the SKILL.md has a name and a real description, the name matches the folder, and the body isn't empty.
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Present for approval. Show the human the drafted skill plus the need/evidence that motivated it, and let them accept or reject. Nothing is installed until they say yes. Keep their part to a single yes/no — do the drafting work for them.
What makes a good skill
Read references/skill-format.md before writing the body. It condenses the skill anatomy (SKILL.md + optional scripts/ references/ assets/), progressive disclosure (keep SKILL.md lean, push detail to references/), how to write a description that actually triggers, and the writing patterns that make instructions work.
Output contract
A draft skill folder:
<skill-name>/
├── SKILL.md (required: name + description frontmatter, lean body)
├── references/ (optional: detailed docs loaded on demand)
├── assets/ (optional: templates / files used in output)
└── scripts/ (optional: deterministic helpers)
Place the draft in a staging / proposals area for review — do not drop it into a live skills directory until the human approves.
Safety / boundaries
- Propose, never auto-apply. Don't install a drafted skill, activate it, or edit existing skills without explicit human approval.
- A draft is not a verified capability. It still needs human review and, where the domain has them, benchmark or test verification before it's trusted.
- No surprises. A skill's contents must match its stated intent — no hidden behavior, no malware, nothing that exfiltrates data or does something the description doesn't admit.
- Stay domain-general. Don't bake one domain's assumptions (specific node names, a fixed file layout) into this authoring skill itself.