Skills

Verification Before Completion

Use when about to claim work is complete, fixed, passing, verified, release-ready, or...

Install

npx skills add GanyuanRan/Aegis --skill verification-before-completion -g -a claude-code -y
Repository
GanyuanRan/Aegis1.4k
Category
Git and review
Updated
10d ago
License
MIT
Context cost
Mediumabout 2,194 tokens
Runs scripts
No, instructions only

What it does

Use when about to claim work is complete, fixed, passing, verified, release-ready, or ready to commit, merge, publish, or hand off.

<EXPLICIT-MODE-GATE> If `activation_mode = "explicit"` or `AEGIS_ACTIVATION_MODE=explicit` is visible and the request names neither Aegis nor this skill, return to the fast path without checklist/ceremony; otherwise continue. </EXPLICIT-MODE-GATE>

Execute

Before success claim: classify destructive permission; read sufficient current evidence and run a fresh falsifying check when it is missing or invalidated; read the complete result/scope; select L0/L1/L2. Downgrade for partial, stale, failing, or narrower evidence; never claim complete then verify later.

This pack grants no GateDecision, PolicySnapshot, evidence sufficiency, requirement acceptance, or completion authority.

Stop Signals

  • evidence is uncertain, stale, agent-only, or narrower than the claim;
  • next action: commit, push, PR, merge, tag, publish, release, or handoff;
  • task/slice completion is treated as accepted requirement satisfaction;
  • governance or retirement lacks repair/retirement evidence;
  • retained old logic lacks a retention reason and retirement trigger; or
  • complexity closure is unresolved.

Destructive/irreversible work needs scoped permission; broad assent is not scoped permission.

Required Evidence Slots

For changed interface/interaction claims, compose ui-ux-governance verification; carry results and uncovered user criteria here, keeping one closeout owner.

- Evidence action / check performed:
- Result / exit status:
- Covered scope:
- Uncovered scope:
- Residual risk:
- Confidence grade: A | B | C
  • A: target + regression; no meaningful unknown.
  • B: target evidence; bounded residual risk.
  • C: partial only; no full-completion claim.

For repairs/optimization, distinguish cause, closure and verified outcome. Check interactions and preserved behavior; investigate consequential unknowns.

Read the whole SKILL.md on GitHub

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