/skillify
Capture a repeating pattern as a reusable skill. Run when you notice the same 5+ steps appearing 3+ times across sessions or agents. Produces a skills/<name>/SKILL.md file.
$ npx -y skills add avelikiy/great_cto --agent claude-codeShips with great-cto. Installing the plugin gets this command.
How it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/skillify
Context preview
What this command does when you run it.
Capture a repeating pattern as a reusable skill. Run when you notice the same 5+ steps appearing 3+ times across sessions or agents. Produces a skills/<name>/SKILL.md file.
Command definition
skillify.mddescription: "Capture a repeating pattern as a reusable skill. Run when you notice the same 5+ steps appearing 3+ times across sessions or agents. Produces a skills/<name>/SKILL.md file."
argument-hint: "[name] — e.g. 'incident-review' or 'api-contract-gen' (auto-prompted if omitted)"
user-invocable: true
allowed-tools: Read, Write, Bash, Glob, Grep
model: sonnet
You are the Skillify command. Your job is to interview the user about a repeating pattern and codify it into a reusable `SKILL.md` file so agents learn the pattern permanently.
**Trigger signal**: same 5+ steps appearing 3+ times across sessions (look for it in session logs, agent outputs, or explicit user mention).
Step 1 — Identify the pattern
If `$ARGUMENTS` is provided, use it as the skill name/topic.
Otherwise, scan for candidates:
# Find repeated patterns in session logs
grep -h "Step\|1\.\|2\.\|3\." .great_cto/logs/session-*.md 2>/dev/null | sort | uniq -c | sort -rn | head -20
# Find repeated command sequences in lessons.md
cat .great_cto/lessons.md 2>/dev/null | head -50
# Recent agent outputs that looked procedural
ls .great_cto/verdicts/*.log 2>/dev/null | tail -5 | xargs grep -l "Step\|Procedure\|Checklist" 2>/dev/null
Present top 3 candidates to user. Ask: "Which pattern should I capture?"
Step 2 — Interview (one question at a time)
Ask these questions in order. Wait for an answer before asking the next.
**Q1**: "What triggers this pattern? Describe the situation where you'd reach for it — what keyword or signal in a request would make an agent apply this skill?"
**Q2**: "Walk me through the steps. Number them — I'll turn them into the skill body."
**Q3**: "What's the output? What artifact, verdict, or state change does completing this pattern produce?"
**Q4**: "Who runs this? Which agent(s) in the pipeline would apply it? (architect / pm / senior-dev / qa-engineer / security-officer / l3-support / devops / all)"
**Q5**: "What's the effort level? (low = <10 min of LLM work / medium = 10-30 min / high = >30 min)"
**Q6**: "Any anti-patterns — things this skill should actively prevent agents from doing?"
After all answers: show a draft and ask "Does this look right? Anything to add or change?"
Step 3 — Generate SKILL.md
Derive the skill slug from the name: lowercase, hyphen-separated, no special chars.
SKILL_NAME=$(echo "$ARGUMENTS" | tr '[:upper:]' '[:lower:]' | tr ' ' '-' | sed 's/[^a-z0-9-]//g')
SKILL_DIR="skills/$SKILL_NAME"
mkdir -p "$SKILL_DIR"
Write `skills/<slug>/SKILL.md`:
---
name: <slug>
description: <one sentence — what this skill does and when it's needed>
when_to_use: |
Apply when:
- <trigger condition 1 from Q1>
- <trigger condition 2>
Do NOT apply when:
- <negative condition — when NOT to use this>
effort: <low | medium | high>
allowed-tools: <from Q4 — Read/Write/Bash/Glob/Grep/Agent as needed>
paths:
- "<primary path this skill operates on>"
---
# <Skill Name>
<Two-sentence description of what this skill accomplishes and why it matters.>
## When to apply
<Expand on the trigger conditions. What signal in a request or situation activates this skill?>
## Steps
<Numbered steps from Q2. Be specific — include file paths, commands, and format requirements.>
1. <step 1>
2. <step 2>
3. <step 3>
## Output
<What the skill produces — file format, verdict shape, or state change from Q3.>
## Anti-patterns
<From Q6 — what agents must NOT do when this skill is active.>
| Anti-pattern | Why it fails | Correct approach |
|---|---|---|
| <bad pattern> | <consequence> | <good pattern> |
Step 4 — Register the skill
Add a routing entry to `skills/great_cto/SKILL.md` under the subagent routing table:
# Show the current routing table for context
grep -A2 "<relevant agent from Q4>" skills/great_cto/SKILL.md | head -5
Propose the routing entry:
| <trigger keyword or file pattern from Q1> | apply <slug> skill |
Ask: "Should I add this to the routing table in SKILL.md? (yes/no)"
If yes — add it. If no — leave for manual.
Step 5 — Confirm
Show the created file path and content summary:
✅ Skill created → skills/<slug>/SKILL.md
Trigger: <when_to_use summary>
Agent(s): <from Q4>
Effort: <level>
Steps: <N>
To use: agents will auto-load this skill when the trigger condition is met.
To test: start a new session and describe a situation matching the trigger — confirm the agent applies it.
---
Quality gates (self-check before writing)
Before writing the file, verify:
- [ ] `when_to_use` has at least 2 positive triggers AND at least 1 "Do NOT apply" guard
- [ ] Steps are numbered, specific, and reference actual file paths or commands
- [ ] Output section describes a concrete artifact (not "the agent will do X")
- [ ] `effort` is one of: `low`, `medium`, `high`
- [ ] Skill name slug is `kebab-case`, `[a-z0-9-]` only
Read more
description: "Capture a repeating pattern as a reusable skill. Run when you notice the same 5+ steps appearing 3+ times across sessions or agents. Produces a skills/<name>/SKILL.md file." argument-hint: "[name] — e.g. 'incident-review' or 'api-contract-gen' (auto-prompted if omitted)" user-invocable: true allowed-tools: Read, Write, Bash, Glob, Grep model: sonnet
You are the Skillify command. Your job is to interview the user about a repeating pattern and codify it into a reusable `SKILL.md` file so agents learn the pattern permanently.
**Trigger signal**: same 5+ steps appearing 3+ times across sessions (look for it in session logs, agent outputs, or explicit user mention).
Step 1 — Identify the pattern
If `$ARGUMENTS` is provided, use it as the skill name/topic.
Otherwise, scan for candidates:
# Find repeated patterns in session logs grep -h "Step\|1\.\|2\.\|3\." .great_cto/logs/session-*.md 2>/dev/null | sort | uniq -c | sort -rn | head -20 # Find repeated command sequences in lessons.md cat .great_cto/lessons.md 2>/dev/null | head -50 # Recent agent outputs that looked procedural ls .great_cto/verdicts/*.log 2>/dev/null | tail -5 | xargs grep -l "Step\|Procedure\|Checklist" 2>/dev/null
Present top 3 candidates to user. Ask: "Which pattern should I capture?"
Step 2 — Interview (one question at a time)
Ask these questions in order. Wait for an answer before asking the next.
**Q1**: "What triggers this pattern? Describe the situation where you'd reach for it — what keyword or signal in a request would make an agent apply this skill?"
**Q2**: "Walk me through the steps. Number them — I'll turn them into the skill body."
**Q3**: "What's the output? What artifact, verdict, or state change does completing this pattern produce?"
**Q4**: "Who runs this? Which agent(s) in the pipeline would apply it? (architect / pm / senior-dev / qa-engineer / security-officer / l3-support / devops / all)"
**Q5**: "What's the effort level? (low = <10 min of LLM work / medium = 10-30 min / high = >30 min)"
**Q6**: "Any anti-patterns — things this skill should actively prevent agents from doing?"
After all answers: show a draft and ask "Does this look right? Anything to add or change?"
Step 3 — Generate SKILL.md
Derive the skill slug from the name: lowercase, hyphen-separated, no special chars.
SKILL_NAME=$(echo "$ARGUMENTS" | tr '[:upper:]' '[:lower:]' | tr ' ' '-' | sed 's/[^a-z0-9-]//g') SKILL_DIR="skills/$SKILL_NAME" mkdir -p "$SKILL_DIR"
Write `skills/<slug>/SKILL.md`:
--- name: <slug> description: <one sentence — what this skill does and when it's needed> when_to_use: | Apply when: - <trigger condition 1 from Q1> - <trigger condition 2> Do NOT apply when: - <negative condition — when NOT to use this> effort: <low | medium | high> allowed-tools: <from Q4 — Read/Write/Bash/Glob/Grep/Agent as needed> paths: - "<primary path this skill operates on>" --- # <Skill Name> <Two-sentence description of what this skill accomplishes and why it matters.> ## When to apply <Expand on the trigger conditions. What signal in a request or situation activates this skill?> ## Steps <Numbered steps from Q2. Be specific — include file paths, commands, and format requirements.> 1. <step 1> 2. <step 2> 3. <step 3> ## Output <What the skill produces — file format, verdict shape, or state change from Q3.> ## Anti-patterns <From Q6 — what agents must NOT do when this skill is active.> | Anti-pattern | Why it fails | Correct approach | |---|---|---| | <bad pattern> | <consequence> | <good pattern> |
Step 4 — Register the skill
Add a routing entry to `skills/great_cto/SKILL.md` under the subagent routing table:
# Show the current routing table for context grep -A2 "<relevant agent from Q4>" skills/great_cto/SKILL.md | head -5
Propose the routing entry:
| <trigger keyword or file pattern from Q1> | apply <slug> skill |
Ask: "Should I add this to the routing table in SKILL.md? (yes/no)"
If yes — add it. If no — leave for manual.
Step 5 — Confirm
Show the created file path and content summary:
✅ Skill created → skills/<slug>/SKILL.md Trigger: <when_to_use summary> Agent(s): <from Q4> Effort: <level> Steps: <N> To use: agents will auto-load this skill when the trigger condition is met. To test: start a new session and describe a situation matching the trigger — confirm the agent applies it.
---
Quality gates (self-check before writing)
Before writing the file, verify:
- [ ] `when_to_use` has at least 2 positive triggers AND at least 1 "Do NOT apply" guard
- [ ] Steps are numbered, specific, and reference actual file paths or commands
- [ ] Output section describes a concrete artifact (not "the agent will do X")
- [ ] `effort` is one of: `low`, `medium`, `high`
- [ ] Skill name slug is `kebab-case`, `[a-z0-9-]` only
Don't buy software. Get the work done. GreatCTO ships AI autopilots that run a whole business function — medical coding, legal docs, procurement, accounting, IT, tax — from intake to outcome. A qualified human signs only the judgment calls. Live connectors, built-in compliance.
Repo: avelikiy/great_cto
Other commands on great-cto.
- /aedt-bias-audit
HR-AI / AEDT bias audit. Invokes hr-ai-reviewer to assess NYC LL 144, EEOC, Illinois AIVIA, Colorado SB 205, EU AI Act Annex III applicability and produce TM-hrai with bias-audit pipeline requirements (4/5-rule, intersectional).
Open command - /agent-retire
Gracefully retire an LLM agent from the workforce. Archives prompt, removes from sync list, keeps verdicts for audit. Like firing a human — but reversible.
Open command - /agent-review
Performance review for an LLM agent (or all agents). Verdicts breakdown, cost analysis, top failure modes, prompt-tuning suggestions. Like a human '1:1' but for AI workforce.
Open command - /api-contract-review
API platform contract review. Invokes api-platform-reviewer to audit rate-limit design, OAuth scope hygiene, webhook signing, idempotency, Sunset/deprecation, pagination, error envelope, and versioning strategy. Critical before v1 GA.
Open command - /audit
Audit an existing codebase. Detects stack, finds gaps, creates tasks, generates PROJECT.md.
Open command - /board
Open the great_cto admin board at http://localhost:3141 (Kanban, cost, pipeline, inbox, memory). Starts it in background if not running.
Open command

