Flux skill builder

Flux Skill Builder

Autonomously create production-grade agent skills from a short description. No interview loops — the agent researches, infers, drafts, validates, and installs in one pass.

Why this exists: The default LLM behavior when asked to "make a skill" produces vague descriptions that never trigger, monolithic SKILL.md files with no progressive disclosure, empty gotchas sections, and instructions that state the obvious. This skill encodes the hard-won patterns that make skills actually work.

Session Phase Tracking

On entry, save the current phase and set the new one:

PLUGIN_ROOT="${DROID_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)}}"
[ ! -d "$PLUGIN_ROOT/scripts" ] && PLUGIN_ROOT=$(ls -td ~/.claude/plugins/cache/nairon-flux/flux/*/ 2>/dev/null | head -1)
FLUXCTL="${PLUGIN_ROOT}/scripts/fluxctl"
PREV_PHASE=$($FLUXCTL session-phase get 2>/dev/null || echo "idle")
$FLUXCTL session-phase set skill_build

On completion, restore the previous phase (not blindly reset to idle — this skill may be invoked from reflect or improve):

$FLUXCTL session-phase set "$PREV_PHASE"

Input

Full request: $ARGUMENTS

Accepts:

• Natural language description: "build a skill for database migrations"
• Path to existing workflow: "turn scripts/deploy.sh into a skill"
• Reference to repeated behavior: "I keep doing X manually, make it a skill"

If empty, ask: "What repeated workflow or capability should this skill encode? Describe it in 1-3 sentences."

Workflow

Execute these 4 phases sequentially. No human gates between phases — run to completion, present the finished skill.

Read pipeline.md for the detailed autonomous execution pipeline.

Phase overview:

Phase	What happens	Output
1. Research	Analyze intent, scan codebase, study existing skills	Inferred spec (category, triggers, capabilities, failure modes)
2. Draft	Write SKILL.md + supporting files using progressive disclosure	Complete skill folder
3. Validate	Run validate_skills.py, self-review against checklists	Pass/fail with auto-fixes
4. Deliver	Install to project-local .secureskills/ through PlaTo when available, with loose skill mirrors only as fallback, then generate trigger test report	Installed and ready

Key Principles

1. Infer, don't interview — Research the codebase, existing skills, and brain vault to answer the questions the interactive version would ask. Only ask the user if genuinely ambiguous (2+ equally valid interpretations).
2. Description is king — The frontmatter description determines whether the skill ever fires. Spend disproportionate effort here. It must include WHAT, WHEN (with specific trigger phrases), and negative triggers.
3. Gotchas are the highest-signal section — Analyze how Claude fails at this task today. Every known failure mode becomes a gotcha. An empty gotchas section means you didn't research hard enough.
4. Progressive disclosure — SKILL.md stays under 350 lines. Heavy content goes to workflow.md, references/, examples.md, or steps.md.
5. Scripts for deterministic work — If the skill involves a checkable operation, write a script. Code is deterministic. Prose instructions are not.
6. One job per skill — If the skill straddles two categories, split it or narrow the scope.

Gotchas

• Undertriggering is the #1 failure mode. Skills that never fire are worthless. The description must be "slightly pushy" — include adjacent phrases the user might say, not just the exact command name.
• Do not state the obvious. Claude already knows how to code. The skill should contain information Claude does NOT have — repo-specific constraints, non-obvious failure modes, decision rules that override defaults.
• Do not over-railroad. Only use rigid step sequences when deviating genuinely breaks things. For judgment-heavy tasks, give principles and examples, not exact scripts.
• Validate before delivering. Always run python3 scripts/validate_skills.py skills/<name>/ before presenting the skill. Fix errors automatically. Present warnings to the user.
• Check for existing skills first. Before creating a new skill, scan .secureskills/store/, ~/.codex/skills/, ~/.claude/skills/, .codex/skills/, and .claude/skills/ for overlap. Extend rather than duplicate.
• Validate the install path, not the repo path. Run validate_skills.py against the installed skill directory. Prefer PlaTo's materialized project path when available; otherwise validate the loose fallback install path, not skills/<name>/ inside the Flux repo.
• Restore session phase on completion. This skill may be invoked from reflect or improve. Save the previous phase on entry and restore it on exit — do not blindly reset to idle.

---

Update Check (End of Command)

ALWAYS run at the very end of execution:

PLUGIN_ROOT="${DROID_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)}}"
[ ! -d "$PLUGIN_ROOT/scripts" ] && PLUGIN_ROOT=$(ls -td ~/.claude/plugins/cache/nairon-flux/flux/*/ 2>/dev/null | head -1)
UPDATE_JSON=$("$PLUGIN_ROOT/scripts/version-check.sh" 2>/dev/null || echo '{"update_available":false}')
UPDATE_AVAILABLE=$(echo "$UPDATE_JSON" | jq -r '.update_available')
LOCAL_VER=$(echo "$UPDATE_JSON" | jq -r '.local_version')
REMOTE_VER=$(echo "$UPDATE_JSON" | jq -r '.remote_version')

If update available, append to output:

---
Flux update available: v${LOCAL_VER} → v${REMOTE_VER}
Update Flux from the same source you installed it from, then restart your agent session.
---