plugins/utils/skills/add-command/SKILL.md
Scaffold a new command definition inside an existing addon or framework
npx skillsauth add jmagly/aiwg add-commandInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Scaffold a new command definition inside an existing addon or framework.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
| Pattern | Example | Action | |---------|---------|--------| | Named add | "add command lint-fix --to aiwg-utils" | Scaffold directly | | Template specified | "add command deploy-all --template orchestration" | Use named template | | Interactive | "add command --interactive --to sdlc-complete" | Guided mode | | Target omitted | "add command my-command" | Ask which addon or framework |
Extract from $ARGUMENTS:
<name> — kebab-case command name (required)--to <target> — addon or framework directory name (required)--template <type> — one of utility (default), transformation, orchestration--interactive — enable guided design questionsIf either <name> or --to is missing, ask before proceeding.
Commands in AIWG are generated from skills at deploy time. The primary source of truth is the skill definition; the command file is the deployable artifact. This skill scaffolds the command .md file directly inside the target's commands/ directory.
Commands differ from skills:
/command-name $ARGUMENTSUse a command when the user needs explicit control over invocation.
Confirm the target exists:
# Check addons
ls agentic/code/addons/<target>/
# Check frameworks
ls agentic/code/frameworks/<target>/
| Template | Use When | Structure |
|----------|----------|-----------|
| utility | Single action, quick operation | Arguments, Steps, Output |
| transformation | Input → processed output pipeline | Input, Pipeline stages, Output format |
| orchestration | Multi-agent workflow, phase transitions | Phases, Agent assignments, Gate criteria |
Ask before generating:
--flag options should it support?aiwg add-command <name> --to <target> --template <type>
---
name: <name>
description: <one-sentence purpose>
args: [<arg>] [--option value]
---
# Command Title
[Description]
## Usage
\`\`\`
/<name> <arg> [--option value]
\`\`\`
## Arguments
| Argument | Required | Description |
|----------|----------|-------------|
| <arg> | Yes | What it controls |
## Options
| Option | Default | Description |
|--------|---------|-------------|
| --option | value | What it controls |
## Execution
1. Validate inputs
2. [Step 2]
3. [Step 3]
## Output
[What success looks like]
The CLI tool updates <target>/manifest.json. Verify:
{
"commands": ["existing-command", "<name>"]
}
<target>/commands/<name>.md
Manifest updated: <target>/manifest.json
Command Created: <name>
───────────────────────
Location: <target>/commands/<name>.md
Template: <type>
Created:
✓ <target>/commands/<name>.md
✓ manifest.json updated
Next Steps:
1. Define arguments and options
2. Write execution steps
3. Specify output format
4. Deploy: aiwg use <target>
5. Test: /<name> --help
User: "add command validate-intake --to sdlc-complete"
Action:
aiwg add-command validate-intake --to sdlc-complete
Result: agentic/code/frameworks/sdlc-complete/commands/validate-intake.md scaffolded with utility template.
User: "create an orchestration command for running the security review cycle in aiwg-utils"
Extraction: name=security-review-cycle, target=aiwg-utils, template=orchestration
Action:
aiwg add-command security-review-cycle --to aiwg-utils --template orchestration
User: "scaffold a command called convert-voice --to voice-framework --template transformation --interactive"
Process: Guided questions clarify input format, transformation pipeline, and output shape before scaffolding.
data-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.