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 nexus-substrate/nexus-agents --skill research-and-votegit clone --depth 1 https://github.com/nexus-substrate/nexus-agentsWrote 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/nexus-substrate/nexus-agents/research-and-vote)<a href="https://agentmods.dev/skills/nexus-substrate/nexus-agents/research-and-vote"><img src="https://agentmods.dev/badge/skills/nexus-substrate/nexus-agents/research-and-vote/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/nexus-substrate/nexus-agents/research-and-vote"><img src="https://agentmods.dev/badge/skills/nexus-substrate/nexus-agents/research-and-vote.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 74 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00050 | $0.00790 |
| Opus 5 | $0.00025 | $0.00395 |
| Sonnet 5 | $0.00010 | $0.00158 |
| Haiku 4.5 | $0.00005 | $0.00079 |
Grade A, and why
research-and-vote 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 11d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research and Vote Skill
Full documentation:
Process
Phase 1: Research
- Check research registry first:
grep -ri "keyword" docs/research/ - Gather primary sources (official docs, specs, RFCs)
- Document findings with source links
Phase 2: Proposal
Create proposal with:
- Problem statement
- Proposed solution
- Alternatives considered
- Trade-offs
Phase 3: Voting
Voting Agents: Architect, Security, DevEx, AI/ML, PM
Thresholds:
| Decision Type | Threshold |
|---|---|
| Reversible changes | Majority |
| Architecture | Supermajority |
| Security-critical | Unanimous |
See CONSENSUS_PROTOCOLS.md for protocol selection matrix.
Phase 4: Documentation
Record decision in GitHub issue with voting record.
Output Format
# Decision Record: [Topic]
## Status: [Approved/Rejected]
## Voting Record
| Agent | Vote | Reasoning |
| ----- | ---- | --------- |
Anti-rationalization — Research and vote
| Excuse | Counter |
|---|---|
| "I already know the answer" | Then write up the alternatives anyway. The vote isn't to discover the answer; it's to surface what you missed. |
| "Skip the research, just vote" | A vote without research surfaces opinion, not informed judgment. Cite primary sources. |
| "Simulated votes are fine for this" | Per CLAUDE.md and memory: simulated votes are random. Never use for real decisions. |
| "Unanimous would be too slow" | Unanimous applies to security-critical and breaking-API. Match the threshold to the reversibility. |
| "We can revisit if it's wrong" | Some decisions are expensive to reverse (data shape, public API, dep choice). Apply higher threshold accordingly. |
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.
- 11d ago First seen · 98 lines · 50 tokens per session scan A 9d8520b2687e
research-and-vote is a skill published in the GitHub repository nexus-substrate/nexus-agents (18 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 790 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 2026-08-30.
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