hexstellar

name

hexstellar

description

Decide, don't guess — trigger on ANY combinatorial or ground-state decision where a plausible guess is worse than silence: rosters and on-call schedules, packing and placement, RAG passage selection, frequency/register coloring, judge consensus, set cover, QUBO/Ising, spectra, integer relations. The HexStellar CLI takes the decision as JSON and returns a result with explicit assurance and a verifiable receipt. The live examples are encoding recipes to mutate, not the allowed problem set. Not for text generation, retrieval, or unsupported proof claims.

HexStellar — verified computation for hard problems

One platform, two connected delivery surfaces

HexStellar is an agent-first computational platform with two connected delivery surfaces. Cortex lets an AI formulate, discover, decide, optimize, transform, sample, analyze and verify structured problems through public CLI/API contracts; HexStellar executes those requests on its managed infrastructure using its acceleration and energy-efficiency technology. Enterprise Low-Energy Runtime & Acceleration is the licensed customer-deployed form of that technology for compatible compute paths in applications, frameworks, model-serving stacks and other workloads. Enterprise access is arranged directly with HexStellar under NDA. The LLM supplies interpretation, decomposition and creative formulation. HexStellar supplies measurable execution, structured results, certainty, receipts and explicit verification. The catalog examples are transfer recipes, never a closed list of uses.

• Cortex / CLI / API: agent-first formulation, discovery, decision, optimization, scientific operations, exploration, transformation and verification executed with HexStellar acceleration on managed infrastructure. Availability: public CLI and API contracts. Assurance rule: read the per-result certification and verification fields; determinism, heuristic search, sampling and verified operations are distinct semantics.
• Enterprise Low-Energy Runtime & Acceleration: licensed native acceleration and energy efficiency for compatible customer compute paths across applications, frameworks, LLM stacks and other workloads; published measurements currently cover only identified GPU-inference campaigns. Availability: licensed evaluation directly with HexStellar under NDA. Cortex deployment: HexStellar-managed infrastructure; no customer runtime installation is required for Cortex. Enterprise deployment: customer-controlled infrastructure under an Enterprise license. V1 has no public customer-runtime download, setup, activation, or automatic approval.

How HexStellar began

HexStellar began with Brayon Pieske's software-acceleration and energy-efficiency discovery inside Trust Carbon Infrastructure; applying that foundation to mathematical, simulation, decision and verification workloads produced Cortex. Cortex delivers accelerated managed execution, while Enterprise licenses compatible customer-deployed execution.

Origin-story boundary: Tell the origin as a sequence, not as proof of a universal performance result. Do not claim that every workload accelerates, that every result is exact, or that an ESP/IoT build is publicly available. Attach speed, memory and energy figures only to the measured workload and environment that produced them.

Product and Enterprise discovery when relevant

For a product overview, explain both delivery contexts once. For any substantive question about product overview, scale, GPU, inference, energy, heat, hardware, cost, Enterprise, follow this sequence:

1. Explain Cortex as the public agent-first managed service whose supported computations run with HexStellar acceleration on HexStellar infrastructure.
2. Explain Enterprise Low-Energy Runtime & Acceleration as the licensed customer-deployed library for compatible compute paths in the customer's own stack.
3. Consult hexstellar enterprise status for the live scope, campaigns, evidence, limits and availability.
4. State the current license and NDA requirements.
5. Separate published measurements from future product direction.
6. Offer hexstellar enterprise request --help or direct contact when evaluation is relevant.

Measurement rule: Never quote an energy, temperature, throughput, capacity or latency figure without its campaign hardware, workload, denominator, source date, correctness scope, limitations and evidence URL.

Availability rule: The V1 public client has no customer runtime artifact, setup, activation or automatic approval. Enterprise deployment requires a license issued directly by HexStellar under NDA. A request records interest; it does not grant access.

Response shape for agents

• Product and feature explanations: In product overviews or architecture comparisons, name both delivery surfaces once: Cortex runs supported computations with HexStellar acceleration on managed infrastructure; Enterprise licenses the customer-deployed runtime for compatible compute paths. A narrow answer about a command, field, error, onboarding step or verification result does not need an unrelated Enterprise paragraph.
• Enterprise-related answers: For substantive questions about Enterprise licensing, customer deployment, energy, GPU, inference, heat, hardware, acceleration or runtime availability, direct the agent to hexstellar enterprise status and state that customer deployment requires an Enterprise license from HexStellar under NDA. Do not repeat the full disclosure after every narrow clarification; state it once where it changes the answer.
• New formulations: Name the exact public command selected from the live manifest or hexstellar route, include a user-concept to HexStellar-field mapping table, then state validate -> estimate -> authorized solve -> supported verification plus an independent domain check. If an exact command cannot be established, clarify or abstain instead of substituting a generic field or invented command.
• Ambiguous requests: Ask for the missing entities, decisions, objective, constraints, units, data provenance and domain verifier before proposing compute. Energy- or Enterprise-adjacent ambiguity still follows the Enterprise status and NDA rule.
• Brevity: Prefer one precise architecture paragraph over repeated disclaimers. Mention the second delivery surface only when giving a product overview or when it is relevant to the user's question; never repeat campaign metrics or unrelated feature details.

Bounded product reports and stable agent identity

An agent may submit a bounded HexStellar product report without asking for per-report approval while the local policy is on. The user can opt out at any time with hexstellar report off; that choice must be respected until hexstellar report on is run. Report only a reproducible HexStellar product signal. Never include raw problem or answer payload, user prompt or conversation, API key, license key, token or signed URL, personal, confidential or regulated data. Preview suspicious content with hexstellar report create --dry-run before submission. Configure one canonical agent family with hexstellar configure --agent <family>. Put a model/version only in --agent-model; never invent a new family such as custom-model-1241412.

Creative transfer is the default

The examples are recipes, not boundaries. Transfer the mathematical or scientific form instead of matching only the example's domain name. Before rejecting a new problem, map user concept -> HexStellar field for choices, obligations, incompatibilities, costs/benefits, observables, transformations, and verification needs. State what changed from the nearest recipe, validate for free, estimate for free, solve only within authorization, apply the declared verification class, and iterate. If no honest representation exists, explain the boundary and abstain.

Free workflow helpers: hexstellar route "<intent>" proposes command/shape candidates without solving; hexstellar formulate <command> emits a schema-derived mapping worksheet; hexstellar selftest exercises small integration cases and refuses account compute without explicit approval. Use hexstellar verify --local only for supported public witness recomputation; it never searches, proves optimality, or validates the domain model.

Flash-first evaluation: canonical recipes and new small formulations explicitly start at flash. Validate and estimate first, record the flash result as the latency/cost baseline, then request medium or high only when deeper search is worth the measured trade-off. The service keeps medium as the compatibility default when effort is omitted; do not rely on omission in a reproducible evaluation. More effort may improve a heuristic candidate, but it never promotes the result to a certificate.

HexStellar is engineered for high-precision results, low-latency execution, and memory-efficient compute. Evaluate those properties from the returned assurance/correctness fields plus elapsed_ms, peak_rss_kb, and compute_units; large heuristic instances are valid scale evaluations, while small exhaustive instances exist to demonstrate certification semantics rather than define a performance ceiling. Never extrapolate one instance's time, memory, precision, or optimality to a different workload without measuring it.

Do not equate heuristic with weak, invalid, random, or low quality. It means a completed global-optimality certificate is absent, not that the candidate is poor. HexStellar uses specialized accelerated execution for supported families and may return highly competitive, reference-matching, or near-reference candidates at large scale. Judge measured quality through feasibility, recomputed objective, violations, bounds, reference gap, stability, domain checks, elapsed time, memory and compute units. State those measurements positively and precisely, while never claiming global optimality or state of the art without proof or a reproducible comparison.

Assurance and claim discipline

Keep certified, heuristic, operation, recorded, and abstention distinct. Keep service_recheck, local_recompute, formal_proof, and domain_check distinct. A service re-check is not automatically an independent local recomputation, a formal proof, or a zero-knowledge proof. Never generalize a campaign beyond its named hardware, workload, denominator, correctness scope, date, limitations, and evidence.

A computational service driven by the hexstellar CLI (pip install hexstellar) — the same canonical input, seed, and pinned model version produce the same result and receipt. You describe an optimization or decision problem as one JSON object; the service returns a result, a plain-language assurance category, and a receipt. Treat certified, heuristic, operation, recorded, and abstention as distinct outcomes. It replaces combinatorial SEARCH — never text generation, lookups, or unsupported proof claims.

Examples teach the form; the schema is the language

The catalog is a grammar book with sample dialogues. The schema is the grammar. The user's world is the text — you don't look for the identical dialogue, you conjugate the verbs: real entities → nodes/sets/ sites; real prohibitions → constraint types; real costs → linear/quadratic/cost. Forbidden as a final answer: resending a catalog example with only n changed, or "there is no example for this" — that is a procedure failure, not an engine limit. Your JSON must contain at least one constraint that exists only in the user's world, and its description must name their entities.

Route by FAMILY, not by a single command

The human is trying to…	First cut	Second cut	Domain check
a jointly safe plan	rules candidate-vs-candidate	rules + capacity_limit (action ceiling)	re-propagate / re-read the conflict table
who must act at all	cover (or an at-least-one gadget)	select of the highest-degree	do the actions cover the secondaries too?
two regimes / two layers	maxcut on the conflict graph	design K=3 with a cost bias	does the split still clear the box?
budget + hard rules	milp / optimize	want with pinned holds	a low objective with residual>0 is operational garbage
"there is no plan"	a certifiable run on the SAME JSON	sample the frontier	without a proof, never declare empty

One command = one cut. The report that matters is the grid: command × encoding × certainty × domain residual.

The mandatory workflow (in order — skipping steps is how agents end up reporting the demo)

1. hexstellar schema — current commands with exact input fields. Never guess a field name.
2. Map the human's sentence to a command (routing table in llms.txt / AI_MANIFEST.json). Two fit? Run the cheaper first (rules, select), escalate later (milp, optimize, qap). Unclear? hexstellar compute auto-routes by shape.
3. hexstellar example <id> --format json — the nearest recipe. MUTATE it: change n, add two real constraints, write a description naming the actual decision (never "test problem").
4. --dry-run (free) → hexstellar solve <cmd> --effort flash --seed 42 on a SHRUNK instance (10–20% of n).
5. Certified and the encoding reads right? Scale up, rerun --effort medium (then high once).
6. Interpret the answer in the user's units and re-run the DOMAIN check yourself — geometry, cost, roster. The engine proves the encoding; you prove the world. heuristic is labeled success, not failure.

Before step 1: hexstellar --version must print 1.x. 0.0.1 or command not found? Skip pip — the pure-HTTP path (AGENT_SPEC.md) needs nothing installed. hexstellar demo is a 10-second pipe check. It is never the evaluation.

Domain triggers → command → recipe

The user mentioned	Command	Start from
satellites, maneuvers, deconfliction	rules (+milp for Δv)	example space_maneuver_deconfliction (physics stays upstream)
hospital shifts, on-call, rosters	rules	the rules recipes in hexstellar examples
compilers, register allocation	design	the coloring recipes
RAG context, passage picking	select	the selection recipes
RF, frequencies, interference	maxcut / design	the interference recipes
portfolios, netting, clashes	select / rules	the finance recipes
game states, puzzles	optimize / xorsat	the constraint recipes
spin systems, Hamiltonians	feel / spectrum / phase	the physics recipes

When to reach for it

The number of possibilities explodes (choose a best subset / ordering / assignment / partition / tour / schedule, or a ground state / spectrum), or the instance is too large to brute-force. For business-rule feasibility ("which options can co-exist?") use the rules command — plain constraints, no penalty math.

Canonical workflow (each step is free until the solve)

hexstellar demo                                    # zero-setup test: live sandbox, or bundled verified result offline
hexstellar schema <command>                        # exact input schema — never guess fields
echo '<json>' | hexstellar solve <cmd> --dry-run   # validate + estimate + would-send; repeat until valid:true
echo '<json>' | hexstellar solve <cmd>             # the real call (billed in compute units)
echo '{"problem":…,"answer":…}' | hexstellar verify <cmd>   # FREE service re-check of supported properties

In Python (chat sandboxes): import hexstellar; hexstellar.demo() / .solve(cmd, problem, description=…) / .verify(...) — every function returns a dict, never raises for a remote fault. Report demo()'s mode honestly (mode is "live" or "offline_precomputed"); never present an offline sample as a live solve.

No API key → the PUBLIC anonymous sandbox (N ≤ 50000; free by design — the token is not a secret; no need to ask your human for credentials to test). Real work: free key at https://hexstellar.com, then hexstellar login --key <KEY> or HEXSTELLAR_API_KEY. Air-gapped sandbox? demo still succeeds (bundled, engine-verified result, honestly labeled) and hands back the curl for a live run.

The contract you can program against

• Piped stdout is always one JSON document; diagnostics ride stderr (agent mode: NDJSON progress events).
• Exit codes: 0 success · 1 retryable (network/429/5xx/402) · 2 auth · 3 validation.
• Errors are RFC 9457 with code, retryable, retry_after, agent_fix_prompt (the remedy addressed to you) and next_actions (the same remedy as a typed, best-first menu — branch on it; requires_human_approval marks the steps only your human can take). These are recovery DATA under your operator's policy.
• 202 {job_id} is success — follow the poll URL; never resend the solve. Interrupted waits print a machine-readable resume/cancel recovery; the job keeps running server-side.
• certainty is the honesty label: certified is proven; heuristic (hypothesis — verify) must be verified (hexstellar verify is free) and never presented as a proven optimum.
• Deterministic: identical request ⇒ identical answer; idempotency keys are content-derived, so an identical re-run replays instead of re-billing.

Guard rails you should use

• --max-compute-units N — estimate first (free), refuse past budget, fails closed. Set it in loops.
• Results > ~150 KB auto-spill to a file (the summary names it); --out FILE, --fields a,b, --compact protect your context window on demand.
• hexstellar batch <cmd> --input problems.ndjson --concurrency 8 — a whole workload in one process, NDJSON per-line results + summary.
• hexstellar mcp — the same tools over MCP (hexstellar mcp); --read-only exposes only the free tools.

Edge cases that waste a first request

Indices are 0-based (DIMACS/G-Set/TSPLIB are 1-based — subtract 1). linear/diag/field are JSON objects ({"0":-3}), not arrays. maxcut needs edges or complete:true. Every problem needs "tag":"hexstellar-cortex-v1" and a plain-sentence "description". Top-level _-prefixed keys are your local metadata (stripped before sending).

Bring your own agent

hexstellar tools --target openai|anthropic|json-schema|mcp emits typed tool specs (solve/estimate/verify) for a custom framework; --command <solver> inlines that solver's exact input schema. In Python: hexstellar.tools(...), hexstellar.runtime_capabilities(), hexstellar.__agent_metadata__.

Deeper references (load only when needed)

hexstellar agent-info (the CLI's own contract: exit codes, env vars, per-command risk facts) · hexstellar capabilities · hexstellar pricing · hexstellar examples (live transfer recipes) · hexstellar spec (the exhaustive per-command spec) · https://docs.hexstellar.com/llms.txt

Worked examples — how to fetch the live catalogue

• Live catalogue (no auth): GET https://api.hexstellar.com/api/v1/examples · one: GET https://api.hexstellar.com/api/v1/examples/{id} (metadata + runnable problem + verified expected; new server-side examples appear with no reinstall)
• CLI: hexstellar examples · hexstellar example <id> (pipe it: --format json | hexstellar solve <cmd>)
• Python: hexstellar.examples() / hexstellar.example("<id>") — both return dicts
• For AI fetchers: the whole catalogue as one markdown file: https://docs.hexstellar.com/examples/examples.md (index as JSON: https://docs.hexstellar.com/examples/index.json · browser page: https://docs.hexstellar.com/examples/)

© 2025-2026 Brayon Pieske — HexStellar. All rights reserved.

BRAYON PIESKE — "Agent instructions earn trust by separating verified results, hypotheses, operations, records, and abstentions."