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Plan lite

Skill Aquish-Lee/agent-handrails/skills/plan-lite

Explicit, claim-scaled engineering handrails for AI coding agents.

Install
npx -y skills add Aquish-Lee/agent-handrails --skill plan-lite

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 25 days oldThe repository was created 25 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Create a compact implementation strategy when a user explicitly requests a plan or a non-trivial task needs ordered, verifiable work slices, risk controls, and a review-boundary seed. Skip obvious single-step edits.

SKILL.md

2.6 KB, 483 tokens by cl100k_base, as published. Nobody here has run it

Plan Lite

Turn a sufficiently clear outcome into the smallest plan that makes execution, verification, review, and rollback legible.

<!-- handrails-contract contract: usable-loop/v2 role: execution-planner reference: references/usable-loop-v2.md runtime: none -->

Read the local v2 contract for complete record fields and authority/invalidation rules.

Preconditions

Use the current request, Alignment Snapshot, or Outcome Contract as the outcome source. An unconflicted current user request is authoritative when the user owns the task. Agent-derived interpretation is provisional. If a missing decision would materially change the plan, expose it instead of burying it as a task.

Do not require a spec. Do not plan a clear one-step edit. Do not execute the plan or silently invoke another handrail.

Build the implementation map

State:

  1. goal, acceptance criteria, and non-goals;
  2. chosen implementation strategy and major tradeoffs;
  3. ordered vertical slices with observable completion;
  4. verification at the narrow, integration, and risk-specific levels;
  5. isolation/rollback needs and explicit authorization gates;
  6. known dependencies, unknowns, and stopping conditions.

Prefer independently verifiable slices over file-by-file activity lists. Name likely files only when they clarify navigation; planned paths are hypotheses.

Review Boundary Seed

Produce a compact seed containing:

  • exact Outcome Reference binding;
  • expected logical changes;
  • dependent/generated changes;
  • authorization guardrails;
  • known pre-existing changes;
  • participating workspaces;
  • base/recovery hints;
  • open boundary questions;
  • Path semantics: hypotheses-not-allowlist.

The seed does not approve omitted paths and does not classify future changes. Branch Sandbox may record actual task-start delta from it. Two-Axis Review or Verify Before Claim must inventory and classify current candidates mechanically.

Direct result

Return the strategy, ordered slices, verification matrix, main risk/rollback, and Review Boundary Seed. Keep it conversational unless the user asks for a durable artifact. Bind Task ID, Outcome Revision, and Authority in one line by default; do not expand the full Outcome Reference or record schema unless the user explicitly asks for it or continuity requires it. Use a Checkpoint only on a continuity trigger.

What ships with it: 2 files

3.6 KB alongside SKILL.md

agents/

references/

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.