agent-superpowers_skill

This skill enforces engineering discipline for OpenClaw agents by verifying work, debugging systematically, and guiding design before code.
  • Python

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GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill agent-superpowers

  • _meta.json290 B
  • SKILL.md13.0 KB

Overview

This skill transforms a general-purpose OpenClaw agent into a disciplined engineering assistant. It enforces verification before claims, a three-agent review pipeline, systematic debugging, brainstorming gates, and anti-over-engineering constraints to keep work focused and reversible. Use it to raise reliability, reduce wasted effort, and make agent-driven development auditable.

How this skill works

The skill injects behavioral rules that require evidence for any completion claim and a stepwise pipeline: brainstorming → plan → implement → spec-review → quality-review → verify → complete. For implementation tasks it spawns three sub-agents (implementer, spec reviewer, quality reviewer) and enforces a four-phase debugging flow with a three-strike stop rule. Verification gates require running explicit commands and including command output before declaring success.

When to use it

  • Implementing coding tasks of any complexity where verification and reviews matter.
  • Debugging failures, test regressions, or hard-to-reproduce bugs under pressure.
  • Before claiming work is complete, to produce independent evidence of success.
  • When spawning sub-agents to execute plan steps and maintain auditability.
  • Planning features or components to force a short, approved design before coding.
  • Performing code reviews or enforcing codebase patterns and quality gates.

Best practices

  • Always present a short design and get approval before implementing any creative work.
  • Write minute-granular plans (2–5 minute steps) with exact file paths and commands.
  • Dispatch three reviewers in sequence: implementer → spec reviewer → quality reviewer.
  • Reproduce errors, investigate root cause, test one hypothesis at a time, and stop after three failed fixes.
  • Run the proving command and paste full output before stating tests/builds/bugs are fixed.
  • Prefer local, reversible changes; confirm before hard-to-reverse or external-facing actions.

Example use cases

  • Add a new feature: propose 2–3 approaches, get design approval, then follow the plan and review pipeline.
  • Fix a failing test: reproduce, instrument boundaries, hypothesize, change one variable, and verify with test output.
  • Spawn implementer/spec/quality sub-agents to complete and independently verify a complex refactor or feature.
  • Claim completion of a ticket only after running the defined verification command and including its output.
  • Avoid scope creep by following anti-over-engineering rules when asked for small, targeted fixes.

FAQ

The exact command that proves the claim, its full output, and a passing exit code or zero-failure count; prior runs or agent reports alone are not sufficient.

When should I stop attempting fixes and reassess architecture?

After three consecutive fixes that fail to resolve the original symptom, stop and discuss architecture instead of attempting a fourth blind fix.

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