Borrowing it
Nothing to install: this file belongs to NeuroverseOS/Neuroverseos-governance. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/NeuroverseOS/Neuroverseos-governance/main/AGENTS.mdgit clone --depth 1 https://github.com/NeuroverseOS/Neuroverseos-governanceWrote 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/instructions/neuroverseos/neuroverseos-governance/agents-md)<a href="https://agentmods.dev/instructions/neuroverseos/neuroverseos-governance/agents-md"><img src="https://agentmods.dev/badge/instructions/neuroverseos/neuroverseos-governance/agents-md/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/instructions/neuroverseos/neuroverseos-governance/agents-md"><img src="https://agentmods.dev/badge/instructions/neuroverseos/neuroverseos-governance/agents-md.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 | $0.05898 | $0.05898 |
| Opus 5.5 | $0.02359 | $0.02359 |
| Sonnet 5.5 | $0.01180 | $0.01180 |
| Haiku 4.5 | $0.00590 | $0.00590 |
Grade A, and why
Neuroverseos-governance AGENTS.md 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 19d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — for people and coding agents working in this repo
Two formats, one engine. neuroverse-governance/1 is the general contract (AI agents calling tools in scopes under a principal's authority, SPEC.md § 16); robot-domain-rules/3 is the robotics dialect (actions in areas, SPEC.md § 1–15). Both are decided by one evaluate, one evaluatePlan, one conflict check and one backtest, through the dialect table in src/model.ts. The robotics dialect is robot-domain-rules 0.5.3 unchanged: its 261 conformance cases are byte for byte the published ones, and a change that alters any of them is a regression unless SPEC.md § 11 gets an erratum line and the change is additive.
The invariants you must keep
PRINCIPLES.md is the contract. Each principle is enforced by conformance cases in both formats, and any change that breaks one is a bug, not a redesign. In one line each:
- Every rule carries a declared authority.
sourceandsetByon every rule; the engine invents nothing; a rule from an agent or a system is weighed bysetBy, never by who wrote it; a mission's rules carry the authorityplan, below every declared one. - Authority is declared, layered, and only tightens.
authoritieshighest first; a lower level can only tighten;authority-overrideis named and has no effect; approvals must hold whatwait.bynames; a mission has noallow; a delegate's authority never grows. - AI writes and proposes; the rulebook decides. No model and no clock in
evaluate.ts,plan.ts,check.ts,compile.ts,governance.ts,backtest.ts; the structuredthendecides, never prose; a draft'ssetBycomes from the caller, never from the model. A plan is checked step by step on projected facts and byplanRules; it is never written here. The model's text about its intent is not an input anywhere. - Unknown means no; a missing fact is never a yes.
/3:required_facts,area_declared,role_declared,role_permits_action,unknown_action./1:required_facts,args_wellformed,scope_declared,role_declared,scope_permits_tool,role_permits_tool,unknown_tool,delegation_exceeds_authority. Only declared defaults are filled in; history is the caller's and a rule that needs it and does not get it refuses; a projected fact out of range refuses, never clamps; an undeclared, missing, mistyped or doubly-supplied argument isargs_wellformedbefore any rule is weighed. - Every decision explains itself.
reasons,trace,setBy,limits,then,fingerprint; RFC 8785 canonical JSON and the SHA-256 fingerprint (over UTF-8, findings excluded) are reproduced byte for byte; a/1PAUSE that rejected approvals carriesapprovalsRejected: [{ id, nonce?, code, reason }]— those four members and nothing else, never the approval, its signature or key material. - Waiting has two meanings, and approval is not a fact. Approval waits return
approvalRequestsand are cleared by a sufficient approval; condition waits are cleared only by facts. WithtrustedKeysdeclared, only the verified handleverifyApprovalreturned (src/verified.ts; averifiedmember in request data is ignored) counts, bound to the rule, the rulebook fingerprint and —/3— the participant, action and area, or —/1— the principal, participant, tool, scope andfingerprint(args), valid atrequest.now, with a nonce not inconsumedApprovals; it clears that wait only, each approval clears at most one wait, a plan consumes nonces step by step. A rejected approval is a PAUSE with a code, never a BLOCK. Facts,now,history, the scope, the delegation chain and the approvals come from the harness, never from the requester. - Conflicts are surfaced, never quietly resolved. Eight finding kinds (
unmatched_selectoris on one rule, no witness); exact for the rule language on reachable requests, with awitnesson every certain finding between two rules, in the rulebook's own words (tools and scopes for/1); "possible" only for history conditions; compile never hides findings andvalidateRulebookre-derives them. The Z3 cross-check (test/z3-crosscheck.test.ts) must keep agreeing on every pair. - One law for everyone. Robots, people and agents, both formats, through one
evaluate; selectors by ID, kind, tag and exclusion; area and scope role limits as re-derived never rules; a subagent may use a tool only if its own role and every role in the chain list it, and a mission binds delegates (who: "*"). - Rules say what may happen; evidence says what is true. Facts are trusted; this is not a safety system and not a judge of text (BOUNDARY.md). The adapter runs the executor only on ALLOW or LIMIT, with the limits; anything that fails before it is a BLOCK with nothing run and the reservation and nonce claims given back; every nonce the decision used is claimed atomically (
consumed.claim) before the executor, so two concurrent calls with one approval cannot both run; once the executor has been invoked a throw is an uncertain outcome (outcome: "uncertain"): spend committed, nonces consumed, history appended,harness.reconciletold — never a release, never an un-consume; the arithmetic behind a cumulative limit (reserve, commit, release) is the harness's, and the engine only compares.
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.
- 19d ago Changed · -169 lines · +3,232 tokens per session e2baec3273b1
- 26d ago Changed · +13 lines · +282 tokens per session 4a8bc443be8a
- 2mo ago First seen · 276 lines · 2,384 tokens per session scan A c8472b9f64e1
Neuroverseos-governance AGENTS.md is an instructions file published in the GitHub repository NeuroverseOS/Neuroverseos-governance (2 stars, last pushed 19d ago), licensed MIT. It adds 5,898 tokens to every session, about $0.0236 per session on Opus 5.5. 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.
Neuroverseos-governance AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Neuroverseos-governance AGENTS.mdNeuroverseOS/Neuroverseos-governance | Instructions file | 2 | 19d ago | MIT | A | 5,898 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode model-prompts.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 2,022 | GitHub Copilot |