lulufoolulufoo/lulu-workflow/lulu-design/SKILL.md

lulu-design

Skill3 starsChanged 7 days agoMITView on GitHub

Produce and deliver a design-doc for a feature cycle.

In this repository11 other files it gives its agents.
- composeSkill
- decisionSkill
- eval-librarySkill
- lulu-approachSkill
- lulu-betSkill
- lulu-brainstormSkill
- lulu-execSkill
- lulu-planSkill
- lulu-specSkill
- lulu-tasksSkill
- lulu-workflowSkill

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.

≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Very specific:
Do NOT proceed until you have read ../_runtime.md and:
line 25
Very specific:
Run $DESIGN_PREFLIGHT. Bind stdout profile_path as $PROFILE_PATH and scope_package as $SCOPE_PACKAGE.
line 35
Very specific:
Do NOT proceed until you have read {SKILL_ROOT}/compose/SKILL.md in full.
line 38

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

SKILL.md

lulu-design

Own the stage-specific contract and inputs for composing the design doc. Completion is delivery through the shared compose engine.

Contract

Boundary	Contract
Scope	Feature cycle only
Prerequisite	Delivered `lulu-approach` as a `decision-package`. Product mode also requires Delivered `lulu-spec`.
Output	Delivered design doc
Ownership	`lulu-design` prepares stage inputs; `compose` owns orchestration

Runtime

<HARD-GATE>
Do NOT proceed until you have read `../_runtime.md` and:

loaded $SKILL_ROOT and $PLATFORM from ## Platform Context
established $CYCLE_ID and $CYCLE_TYPE via ## Session Foundation
set $SKILL_DIR = $SKILL_ROOT/lulu-design

</HARD-GATE>

Compose

Run $DESIGN_PREFLIGHT. Bind stdout profile_path as $PROFILE_PATH and scope_package as $SCOPE_PACKAGE.

<HARD-GATE>
Do NOT proceed until you have read `{SKILL_ROOT}/compose/SKILL.md` in full.
Continue from its `## Entry`.
</HARD-GATE>

Script Macros

Macro	Command
`$DESIGN_PREFLIGHT`	`python3 "$SKILL_DIR/scripts/start/tech_design_preflight.py" --cycle-id "$CYCLE_ID"`

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

It worked
Partly
It didn't

What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free