grp06/useful-codex-skills/execplan-create

ExecPlan Authoring

Write plans the way a strong software designer would: not as a task list for rearranging code, but as a path to a simpler system with clearer boundaries.

Preferred Inputs

Preferred source input is a decided work item with a completed decision.md.

Supported inputs, in priority order:

1. explicit work-item path
2. explicit decision.md path
3. .agent/active when it points at a work item with stage="decision" and state="completed"
4. the most recently updated work item under .agent/work/ with stage="decision" and state="completed"
5. a user-supplied PRD, RFC, voice note, or detailed problem statement

If using a decided work item, do not silently reopen candidate search unless the decision artifact is clearly incomplete.

Work Item Model

For the new workflow, plans live inside work-item directories:

.agent/work/<id-slug>/execplan.md

Each work item should have a small meta.json file with:

• stage
• state
• timestamps
• relative artifact paths

Update .agent/active as a convenience symlink when operating on a work item, but do not treat it as authoritative over meta.json.

Legacy compatibility:

• If no work-item directory is available and the user explicitly wants the older singleton flow, you may still write .agent/execplan-pending.md.
• Downstream skills will prefer the work-item format and only fall back to legacy singleton files when needed.

Source of Truth

• Read {baseDir}/.agent/PLANS.md in full before drafting.
• If {baseDir}/.agent/PLANS.md is missing, copy this skill's PLANS.md to {baseDir}/.agent/PLANS.md, then read that copy as the source of truth.
• Follow PLANS.md exactly. If any instruction conflicts with this skill, PLANS.md wins.

Ousterhout Lens

Use John Ousterhout's design philosophy as the default planning lens:

• prefer deep modules over shallow wrappers
• prefer interfaces that hide sequencing and policy
• prefer fewer concepts and fewer special cases
• prefer simpler mental models over elegant-looking decomposition
• prefer concentrating complexity behind a stable boundary over spreading it around

Treat these as the main forms of complexity:

• change amplification
• cognitive load
• unknown unknowns

When authoring a plan, answer these questions explicitly:

• what complexity exists today, and who pays for it
• what boundary or interface becomes simpler after this work
• what knowledge moves out of callers and into the implementation
• what special cases, duplicate concepts, or orchestration steps disappear
• what future change becomes easier after this work

Workflow

Step 1: Resolve the input source

If operating on a decided work item:

• read meta.json
• read decision.md

If operating from a raw user brief instead:

• create or reuse a work-item directory under .agent/work/
• initialize or update meta.json
• use the user brief as the planning source

Step 2: Inspect the repo and planning boundaries

Inspect the relevant files and flows. Ask:

• what callers currently need to know
• where sequencing leaks
• where concepts duplicate
• where special cases accumulate

Step 3: Draft execplan.md

Write the ExecPlan to:

• work-item format: .agent/work/<id-slug>/execplan.md
• legacy fallback only when necessary: .agent/execplan-pending.md

The plan should:

• preserve the hard constraints from decision.md
• name the exact files and boundaries involved
• explain the current pain
• describe the intended complexity dividend
• remain self-contained and novice-friendly

Step 4: Finalize metadata

If using a work item, update meta.json:

• stage="plan"
• state="completed"
• artifacts.execplan="execplan.md"
• updated_at=<now>

Anti-Patterns

• reopening candidate search during planning without strong evidence
• writing a mechanically correct plan that preserves the same complexity under new names
• proposing thin wrappers or pass-through modules unless they clearly hide detail
• leaving key design choices to the implementer when the repo evidence is already strong