Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brunob54/superpowers-orchestrator --skill self-consistency-reasonergit clone --depth 1 https://github.com/brunob54/superpowers-orchestratorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/brunob54/superpowers-orchestrator/self-consistency-reasoner)<a href="https://agentmods.dev/skills/brunob54/superpowers-orchestrator/self-consistency-reasoner"><img src="https://agentmods.dev/badge/skills/brunob54/superpowers-orchestrator/self-consistency-reasoner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brunob54/superpowers-orchestrator/self-consistency-reasoner"><img src="https://agentmods.dev/badge/skills/brunob54/superpowers-orchestrator/self-consistency-reasoner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.00897 |
| Opus 5 | $0.00032 | $0.00449 |
| Sonnet 5 | $0.00013 | $0.00179 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
self-consistency-reasoner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Consistency Reasoner
A structured reasoning technique based on the Self-Consistency method (Wang et al., ICLR 2023).
Core idea: Complex problems often have multiple valid paths to the correct answer. Incorrect reasoning, even when confident-sounding, tends to scatter across different wrong answers. By generating N independent reasoning paths and taking majority vote, we reliably surface the correct answer and get a built-in confidence signal for free.
When This Fires
This skill is invoked internally by:
- systematic-debugging — during root cause hypothesis generation (Phase 3)
- verification-before-completion — during evidence evaluation
It fires when:
- The reasoning requires 3+ non-trivial steps
- A single reasoning chain could make a wrong assumption or logical error
- The answer has a fixed answer set (a root cause, yes/no, a specific conclusion)
- Being wrong has real cost (wrong diagnosis wastes edits; false "done" wastes review cycles)
How Many Paths to Generate
Scale paths to difficulty:
| Problem Type | Paths |
|---|---|
| Binary verification (does this evidence prove the claim?) | 3 paths |
| Root cause diagnosis with 2-3 candidates | 5 paths |
| Complex multi-factor diagnosis or high-stakes verification | 7 paths |
Default: 5 paths. Research shows gains plateau quickly — 5 captures most of the benefit of 40.
The Process
Step 1: Generate N Independent Reasoning Paths
Produce each path independently — don't let earlier paths contaminate later ones. Vary your approach deliberately:
- Use a different starting point or framing
- Work forward from given info in one path, backward from the goal in another
- Decompose the problem differently across paths
- For debugging: start from different points in the call stack, assume different failure modes
- For verification: evaluate the evidence from different angles (what would prove it true? what would prove it false?)
Each path must end with a clearly parsed final answer.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 104 lines · 63 tokens per session scan A a3e692de44fa
self-consistency-reasoner is a skill published in the GitHub repository brunob54/superpowers-orchestrator (3 stars, last pushed 2d ago), licensed MIT. It adds 63 tokens to every session and 897 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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