Documentation

Hydra has three surfaces, a CLI, an interactive TUI cockpit, and a desktop app: sitting in front of every AI model on your machine. This covers all three, the tools it plugs into, and every command: what it does, how it works, and how to use it. The deep math lives on First Principles.

Overview discover → route → check → observe

Hydra picks the model best suited to each task, and can check the answer before you rely on it. It discovers every model you can reach (hosted APIs, local servers, CLI agents), routes each request to a model measured capable at that task type (today the lowest-cost one that clears the bar, with stronger models as the fallback chain), checks the answer with verifiers when you ask it to, and logs every request. No single vendor is privileged.

the pipeline
   discover                 route                       execute + observe
┌───────────┐   ┌────────────────┐   ┌──────────────┐
│ PATH scan │─┐ │ policy gate    │   │ CLI agents   │  claude·codex·cursor
│ env keys  │─┼▶│ capability rank│─▶ │ API models   │  openai·gemini·groq
│ port scan │─┘ │ fallback chain │   │ local models │  ollama·lm studio
└───────────┘   └────────────────┘   └──────────────┘
                          │                        │
                    ~1.1µs/decision          cost.jsonl · calibration · verdicts

install one binary, no runtime

Pure Go, single static binary.

Usage
# Homebrew (recommended)
brew install ankit373/hydra/hyctl

# npm  ·  or run once, no install:  npx hyctl
npm install -g hyctl

# pip
pip install hyctl

# Standalone installer
curl -fsSL https://raw.githubusercontent.com/ankit373/hydra/main/install.sh | sh

# From source (Go 1.26+)
git clone https://github.com/ankit373/hydra.git && cd hydra
go build -o hyctl ./cmd/hydra

The CLI shipped the whole interface

Everything Hydra does runs through the single hyctl binary: requests, discovery, verification, graph and cost. Scriptable, CI-friendly, zero daemon.

hyctl dispatch --dry-run "add pagination"
  prompt → STANDARD → T5
  Primary:   gemini pro   score 82
  Fallback:  openrouter   score 76  ← if primary rate-limits
  Local:     ollama/qwen3 ← always available, $0
  ✔ chain resolved · nothing dispatched (dry-run)

hyctl tui shipped interactive cockpit

A terminal cockpit you operate: type a task, press enter, and it runs. Tab cycles six views: Chat, Agents, Models, Activity, Usage, Audit. Every frame below is a real hyctl tui --snapshot, rendered by the binary itself.

HYDRA ▸ chat
 HYDRA  chat  agents  models  activity  usage  audit          session $0.0000 · context ▱▱▱▱▱▱▱▱ 0%
────────────────────────────────────────────────────────────────────────────────────────────────────
CONTEXT BUDGET       │ 15 models found by the scan.          │ CODE · go
░░░░░░░░░░░░░░░      │                                       │   1 // paginated users endpoint
claude 0%            │ Type a task and press enter. shift+tab│   2 func (s *Server) ListUsers(w ht…
                     │ mode · ctrl+t thread · ? shortcuts ·  │   3     page := parsePage(r.URL.Que…
MODELS               │ :q quits.                             │   4     users, err := s.repo.Users(…
 ✓ Claude Code       │ ❯ add pagination to the users endpoint│   5     if err != nil {
 ✓ Claude Opus 4.…   │   auto-routed · standard work → T7    │   6         http.Error(w, err.Error…
 ✓ OpenAI Codex      │ qwen2.5-coder · single                │   7         return
 ✓ Claude Sonnet …   │   why code edit, standard scope, no   │   8     }
 ✓ Gemini 2.0 Fla…   │ PII                                   │   9     json.NewEncoder(w).Encode(u…
 ✓ Antigravity       │   plan ✓ 3 steps · edit ✓ users.go    │  10 }
 ✓ …1 Pro (High)     │ +24/−6 · tests ✓ go test ./...        │
 ✓ …1 Pro (Low)      │  /diff · /undo · /open                │
 ✓ …5 Flash (High)   │   ✓ done 3.2s · $0.0041 est · trace   │
 ✓ …5 Flash (Medi…   │ demo0000, enter opens the trace       │
 ✓ …5 Flash (Low)    │                                       │
 ✓ Qwen2.5-Coder:…   │                                       │
 ✓ qwen3:0.6b (Ol…   │                                       │
 ✗ Ollama            │                                       │
 ✗ nomic-embed-te…   │                                       │
                     │                                       │
MODE                 │                                       │
 auto                │                                       │
                     │ ╭────────────────────────────────────╮│
                     │ │  Auto ▾  what do you need done?,   ││
                     │ │ enter runs it                      ││
                     │ ╰────────────────────────────────────╯│
 ctrl+t thread  enter send  shift+tab mode  ctrl+o route  ? shortcuts        mode auto · route auto
HYDRA ▸ models
 HYDRA  chat  agents  models  activity  usage  audit          session $0.0000 · context ▱▱▱▱▱▱▱▱ 0%
────────────────────────────────────────────────────────────────────────────────────────────────────
╭─────────────────────────────────────────────────────────────────╮ ╭─────────────────────────────╮
│ MODELS · by provider/server                                     │ │ SERVER                      │
│                                                                 │ │                             │
│ ▸ ▾ ● anthropic                  1 model                        │ │  anthropic                  │
│      ● Claude Code             T1                               │ │                             │
│   ▾ ● antigravity                8 models                       │ │  models      1 (1 routable) │
│      ● Claude Opus 4.6 (Thin…  T2                               │ │  state       up             │
│      ● Claude Sonnet 4.6 (Th…  T3                               │ ╰─────────────────────────────╯
│      ● Antigravity             T4                               │
│      ● Gemini 3.1 Pro (High)   T5                               │
│      ● Gemini 3.1 Pro (Low)    T6                               │
│      ● …3.8 Flash (High)       T7                               │
│      ● …3.8 Flash (Medium)     T8                               │
│      ● …3.8 Flash (Low)        T9                               │
│   ▾ ● openai                     1 model                        │
│      ● OpenAI Codex            T3                               │
│   ▾ ● Ollama                     3 models                       │
│      ● Qwen2.5-Coder:7b       T10                               │
│      ● qwen3:0.6b             T10                               │
│      ◌ nomic-embed-text:late… T10 embeddings only, never routed │
│                                                                 │
│ ● up · ○ down (children unavailable) · ◌ not routable           │
╰─────────────────────────────────────────────────────────────────╯



 j/k move  enter detail  space collapse  p pin  ? shortcuts               scanned 0s ago · r rescan
HYDRA ▸ audit
 HYDRA  chat  agents  models  activity  usage  audit          session $0.0000 · context ▱▱▱▱▱▱▱▱ 0%
────────────────────────────────────────────────────────────────────────────────────────────────────
╭─────────────────────────────────────────────────────────────────╮
│ MODEL SCORECARD · calibration                                   │
│                                                                 │
│  source               domain      n  sens  spec  D nats         │
│  claude               trust-b…   10  0.83  0.50    0.24         │
│  qwen                 trust-b…    9  0.88  0.20    0.02         │
│  claude               trust-b…    5  0.86  0.50    0.28         │
│  ollama/Qwen2.5-Code… trust-b…    5  0.86  0.50    0.28         │
│  qwen                 trust-b…    5  0.86  0.50    0.28         │
│  test-src             test-do…    1  0.67  0.50    0.06         │
│  verifier:go          gotest      1  0.67  0.50    0.06         │
│                                                                 │
│  consensus checks       0.50 mean confidence over 16            │
│  cleared without review 0%                                      │
│  same-family agreement  acme ×0.14 (J=0.86), echo, not evidence │
╰─────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────╮
│ AUDIT LOG                                  │
│                                            │
│  chain    BROKEN · 635 events, 599 chained │
│  today    89 allowed · 0 denied            │
│  all-time ████████████████████ 635         │
╰────────────────────────────────────────────╯
╭─────────────────────────────────────────────────────────────╮
│ GUARDRAILS                                                  │
│                                                             │
↓ 9 more
 j/k move  enter resolve  v verify  i ignore  ? shortcuts           chain BROKEN · checked 14:20:08
How it works

Chat executes: the route line names the routing level, model and strategy the router picked and why, then the proof strip reports what the run planned, edited and verified. shift+tab cycles the modes, Auto (plan → edit → run your tests → fix → repeat), Plan, Edit, Ask, and ctrl+o overrides where the next task runs without changing what it does. Models is the discovered estate by provider, each model at its routing level, with a server's children greyed when the server itself is down. Audit carries the calibration scorecard, the hash-chained log's integrity, the guardrails actually in force, and anything waiting on a human. Agents, Activity and Usage cover work in flight, per-run traces, and where the money went. ? lists every key, rendered from the keymap itself so it cannot drift.

Streaming

An answer appears as it arrives rather than all at once when the task finishes, so a slow model and a stuck one no longer look the same. The frame repaints five times a second, which is also what coalesces the stream: deltas land every ~20ms and the render never runs per delta.

When a model gives up part-way through, its partial output collapses to one dim line naming the model and the reason, so it cannot be mistaken for the answer, and e expands it again. The text is kept, not re-fetched. Only plain routing streams: a swarm has several models answering at once and consensus picks by judge after N replies, so neither has a single stream to show.

Keys & usage
hyctl tui
# tab cycles views · shift+tab modes · ctrl+o routing · e expands a
# collapsed partial · ? all keys · :q quit
hyctl tui --snapshot --view 0..5   # render one static frame

The desktop app download point-and-click cockpit

A native window over the same engine, Wails v2 + React, in desktop/. It opens on the chat, with the other views behind an icon rail. Every release ships a build for macOS, Windows and Linux. Click the sidebar: the views swap live.

Hydra · Usage
runs · live first
● 20260802T190000Z-5e55… 4.7s · $0.0031 · 3 agents
   2 running · 1 ok
○ 20260802T182210Z-ab41…  1.3s · $0.0000 · 1 agent · ok
○ 20260802T175902Z-9d07…  8.1s · $0.0142 · 5 agents · ok
fleet · this session
saved vs frontier
$6.03
▁▃▄▆▅▇█▇
local share
85%
▂▄▃▅▆▆▇█
last confidence
0.98
▅▆▆▇▇█▇█
governor · claude_pct
███████████░░░░░░░ 58%
supervision tree
orchestrator main model · you · 0.71
├─ design T3 · agy · claude · returned · 0.93
├─ token-rotation T3 · agy · claude · running · 0.88
│  ├─ worker-1 T6 · gemini pro · 0.91
│  └─ worker-2 T8 · gemini flash · 0.62
└─ docs T10 · qwen · local · 0.87
   ┄▶ A2A token-rotation → tests
internal/auth/token.go  +2 −1
 41  41   func Rotate(k *Key) error {
 42     − return k.rotate()
     42 + if err := k.validate(); err != nil {
     43 +   return err
 43  44   }
Get it
# Download from the releases page:
hydra-desktop_<version>_darwin_universal.zip   # macOS, Intel + Apple Silicon
hydra-desktop_<version>_windows_amd64.zip      # Windows
hydra-desktop_<version>_linux_amd64.tar.gz     # Linux

# Every artifact ships a .sha256 beside it. Verify before you run:
shasum -a 256 -c hydra-desktop_<version>_darwin_universal.zip.sha256   # macOS
sha256sum   -c hydra-desktop_<version>_linux_amd64.tar.gz.sha256       # Linux

# Windows (PowerShell):
$f = "hydra-desktop_<version>_windows_amd64.zip"
(Get-FileHash $f -Algorithm SHA256).Hash -eq (Get-Content "$f.sha256").Split(' ')[0]

# Or build it yourself:
go install github.com/wailsapp/wails/v2/cmd/wails@latest
cd desktop && wails build                # → desktop/build/bin/Hydra.app
The builds are not code-signed yet, so the published .sha256 is the only integrity check available, worth the one command above. The first launch also takes one extra step. macOS: Gatekeeper reports an unidentified developer, right-click the app → Open → Open, once. If it still refuses after unzipping from a terminal, run xattr -dr com.apple.quarantine Hydra.app. Windows: SmartScreen may warn, More info → Run anyway. Linux: needs libgtk-3-0 and libwebkit2gtk-4.1-0, then chmod +x Hydra.
The app reads the same logs the CLI writes, so its numbers are the CLI's numbers, Usage totals match hyctl cost and hyctl stats for the same data. There is no separate daemon and no telemetry: it reads ~/.hydra/logs/ on your machine.

How discovery works no plugins, no config

Hydra finds every model on your machine across three channels in under two seconds, scores each with a CapScore, and routes across all of them. Provider-neutral: it routes away from expensive models, never toward a favored vendor.

13+

PATH scan

executables on $PATH

Finds installed coding agents & CLIs, Claude Code, Codex, Cursor, Gemini CLI, Copilot and more.

14

Env vars

provider API keys

Detects keys for the major API providers and registers each as a routable model.

2

Port scan

localhost servers

Queries Ollama (11434), LM Studio (1234), a LiteLLM proxy (4000) and a llama.cpp server (8080), and enumerates every model each one serves.

Coding agents & CLIs discovered on $PATH

Whatever agent you drive Hydra with becomes the orchestrator; the rest are interchangeable sources it can send work to. Hydra shells out to each through its native executor.

Claude Code
cli · expert
Anthropic's agent, top reasoning routing level.
Antigravity (agy)
cli · expert
Claude-family model registry; a first-class model.
OpenAI Codex
cli · complex
Strong code generation.
Cursor
cli · complex
IDE agent, routable from Hydra.
Windsurf
cli · complex
Agentic IDE.
Gemini CLI
cli · standard-complex
Google's coding CLI.
GitHub Copilot
cli · standard
Copilot in the terminal.
Sourcegraph Cody
cli · standard
Context-aware assistant.
Amp
cli · standard
Agentic coding tool.
Continue
cli · standard
Open-source assistant.
Amazon Kiro
cli · complex
AWS's agentic IDE.
Hydra sends each request to a model measured capable at that task type, and moves to another model when that model fails, or when the answer fails its check (with a --confidence target, or the validator hyctl edit runs).

API providers discovered from env keys

Set a provider's API key and it becomes a routable model automatically, through the OpenAI-compatible or provider-native HTTP executor. No config file to touch.

AnthropicOpenAIOpenRouterGoogle AI GroqTogetherFireworksMistral DeepSeekxAI · GrokAWS BedrockAzure OpenAI PerplexityCohereReplicate
Add one
export ANTHROPIC_API_KEY=sk-…      # then:
hyctl probe                        # it shows up as a scored model
Route within OpenRouter

A key alone gives one routing choice: a single model. Hydra already prices and scores OpenRouter's whole catalogue, so naming models turns each into its own routing choice the router chooses between. Admission is explicit: enumerating hundreds would bury this list. Naming nothing changes nothing.

# ~/.hydra/config.toml
[openrouter]
models = ["anthropic/claude-sonnet-4.5", "google/gemini-2.5-pro"]

hyctl probe then lists one entry per model and says how much of the catalogue is enabled ("2 of 423"). A name the catalogue does not hold is shown as not routable with the reason, never dropped.

Local runtimes the free floor

Local models are the terminal fallback: always available, always $0, and where PII-flagged prompts are pinned so sensitive data never leaves the machine.

Ollama
port 11434 · simple-local
Every installed model enumerated individually (Qwen, Llama, Phi…).
LM Studio
port 1234 · simple-local
Local server; models discovered and routed.
LiteLLM
port 4000 · per-model
One entry per model the proxy fronts. Local only where the upstream itself is local, so a proxy forwarding to OpenAI is never priced or governed as local.
llama.cpp
port 8080 · simple-local
One entry per loaded model, and the server is identified by its own build_info rather than assumed from the port, so an unrelated service on 8080 is never offered to the router.

hyctl init first-run wizard

Scans your machine, ranks every model, and walks you through picking your main model (the orchestrator), a local model calibrated to your real free RAM, and whether you handle sensitive data. Writes ~/.hydra/config.toml.

Usage
hyctl init

hyctl probe discover every model

Runs the three discovery channels concurrently and lists every model with its CapScore and status. For a local model it also shows the quantization actually loaded, because the same model id at Q4_K_M and at Q8_0 is not the same model: it differs in accuracy, VRAM and tokens/sec. --json also carries the model's architectural context ceiling, which is what caps the window the budget governor holds a local model to.

Usage
hyctl probe

hyctl status live state

The models that can actually run, budget bars, and the rate-aware governor.

How it works

Model list comes from live discovery, grouped by the routing level each model would route at, so it cannot drift from the router; anything discovery found but nothing can drive is counted, not listed. The governor models context usage as a drifting process and estimates the first-passage probability of crossing the ceiling before the task ends, escalating before a threshold is hit.

Usage
hyctl status
How the governor decides →

hyctl dispatch the router

Sends a request to a model measured capable at its task type, with automatic fallback. Today that is the lowest-cost model that clears the bar. The core command.

How it works

1 · classify → enum/routing level · 2 · policy gate (PII can block before any network call) · 3 · select highest-CapScore available model at/under routing level · 4 · execute · 5 · on failure fall down the chain to local Qwen · 6 · log tokens + cost. ~1.1µs of decision overhead.

Usage
hyctl dispatch "refactor auth to JWT refresh"
hyctl dispatch --enum SIMPLE "write a User DTO"
hyctl dispatch --dry-run "add pagination"
hyctl dispatch --local "write unit tests"
Streaming

On a terminal the answer is drawn as it arrives: a spinner covers the wait before the first token, then tokens append, then the token counts, elapsed time and measured TTFT print as a footer, since none of those numbers exist until the call returns. Measured on a local 7B: 435 deltas spread over 9.9s of a 10.0s call, where before there was nothing on screen for the whole ten seconds.

Piped output never streams and is byte-identical to before, so scripts are unaffected; --no-stream asks for the same buffered rendering on a terminal. When a model fails part-way through, its partial is collapsed off the screen and replaced by one line naming the model and the reason, because a partial left on screen reads as part of the answer. Nothing is erased once it has scrolled past the top of the window.

A fan-out has no single stream to show, so --swarm and --confidence draw a live panel instead: every model that was selected, with its state, elapsed time, tokens and the cost as it accrues. A confidence run adds the running log-odds against the threshold it has to cross, so an ensemble that stops after two models says why it stopped. The panel is erased when the run ends, and the result printed after it is unchanged.

Key flags
--enum / --tier--dry-run--local --file raise bar by blast radius--a2a handoff.json--system --no-stream

dispatch --swarm fan out, keep the best

race (first success), best (LLM judge), or all (ranked by CapScore), with a pre-flight cost guard.

Usage
hyctl dispatch --swarm --swarm-mode best "implement a rate limiter"
  --swarm-max-heads 5  --swarm-max-cost 0.05  --swarm-judge-tier 1

dispatch --confidence route to a P(correct)

Sample models adaptively until a target confidence is reached, then stop.

How it works

An SPRT accumulates the calibrated log-likelihood ratio across votes and stops at the boundary implied by your target. --file raises the bar by blast radius.

Usage
hyctl dispatch --confidence 0.95 "is this migration safe for prod?"
See the SPRT walk derived →

hyctl edit safe file edits

Scoped, validated, rollback-safe single-file edit through a model.

Usage
hyctl edit --file "$PWD/internal/foo.go" --enum MODERATE --prompt "add a nil check"

hyctl review code review

Review / approve / reject / QA a change.

Usage
hyctl review --file internal/foo.go

hyctl parallel fan independent tasks

Fan a set of independent tasks across models. Optimal count follows n*=√((1−s)/k).

Usage
hyctl parallel --tasks tasks.txt
graph parallel →

hyctl trust calibration and verification

Builds and inspects the calibration behind --confidence. Each source earns a measured reliability from real outcomes.

How it works

A Beta-Bernoulli posterior over sensitivity/specificity → a per-vote LLR and a diagnostic power D (KL divergence, nats). A coin-flip source has D≈0 and is ignored. The defect-cost model prices a wrong answer and sets the required confidence.

Subcommands
hyctl trust calibration      # per-source se / sp / D
hyctl trust record --source ollama/qwen3:4b --domain go --said-correct --outcome correct  # a model ID from `hyctl probe`
hyctl trust defect --pii --production
hyctl trust stats   # samples saved vs fixed-N
hyctl trust explain <hash>   # the LLR ledger for a run
hyctl trust benchmark        # measured SPRT numbers
See diagnostic power D derived →

hyctl graph blast how dangerous is this file?

Reports a file's blast radius and the confidence a change to it demands.

How it works

From graph.json it counts transitive dependents and computes κ = ⟨k²⟩/⟨k⟩ (Molloy-Reed). κ ≥ 2 ⟹ cascade-capable core ⟹ higher confidence bar.

Usage
hyctl graph blast internal/auth/token.go
Drag the percolation threshold →

hyctl graph parallel how many agents?

Returns the optimal number of parallel agents for a set of files.

How it works

Amdahl + coordination cost: minimizing T(n)=s+(1−s)/n+kn gives n*=√((1−s)/k). Independent files → ~6; coupled → ~2.

Usage
hyctl graph parallel internal/a.go internal/b.go
See the speedup curve →

hyctl context entropy signal, not length

Measures context density and tells you when to compact.

How it works

ρ = |gzip(C)|/|C| proxies the entropy rate; useful = L·ρ. Compact on falling ρ, not raw length.

Usage
hyctl context entropy internal/foo.go
cat notes.md | hyctl context entropy -
See useful-tokens fall →

hyctl mcp accountability ledger

A local, append-only ledger that records, and can gate: what every agent touches.

Subcommands
hyctl mcp check <tool> --agent A --resource R --action write
hyctl mcp log --denied     # what got blocked
hyctl mcp report          # allowed / denied by agent & tool

hyctl mcp registry safety score for the MCP servers on your machine

Every existing MCP directory answers "does this server exist", none answer "is it safe to run with my credentials right now," and star/download counts are actively misleading (the most-starred servers score worst on quality in independent research). This scores what's actually installed instead of indexing everything that exists.

Subcommands
hyctl mcp registry sync             # pull the official MCP registry into a local cache
hyctl mcp registry scan             # list servers installed across Claude Code/Desktop, Cursor, Windsurf, VS Code
hyctl mcp registry audit            # resolve + score installed servers, update lifecycle state
hyctl mcp registry export --out DIR  # static index.html/index.json of audited servers
hyctl mcp registry backtest         # validate scoring against known real incidents (postmark-mcp, CVE-2025-6514)
hyctl mcp registry list             # audited servers by safety score
hyctl mcp registry clear <server>   # recover a server quarantined in error

Scoring is shaped around the CSA MCP Selection Scorecard's four categories (Security Implementation, Repository Health, Operational Security, Community & Governance), automating a taxonomy the MCP Security Working Group already endorsed, not inventing a new one. Only a confirmed finding (a known advisory match) quarantines a server; a name-similarity heuristic lowers the score without condemning it, because quarantine has no automatic way out, clear is the manual recovery path. A category nothing could be checked in contributes a neutral baseline rather than being dropped from the average, so failing to reach GitHub can never raise a score, and a server nothing is known about reads "insufficient evidence" rather than a number. A server's status (new → provisional → trusted → flagged → quarantined) drops back to provisional on every version bump, detected via a content-hash diff of the manifest, the direct fix for the postmark-mcp rug-pull pattern (15 clean npm versions, then a malicious one). scan never reads env-var or secret values from client configs, only server identity.

Feeds back into the ledger: hyctl mcp check auto-classifies a tool call as mcp-unverified, mcp-flagged, or mcp-quarantined from a server's registry state, the same way PII is auto-detected from content, so a policy rule can gate on it automatically. Below that: mcp-behavior-change, a server whose ledger history has only ever shown one kind of access (read, say) suddenly performing another (network) is flagged from local history alone, no registry data or CVE required. A server's first-ever call is never flagged, there's nothing yet to compare it against.

The exported page (export) carries a disclaimer, this is a probabilistic signal from automated checks, not a guarantee of safety or a claim about a publisher's intent, and every row links a pre-filled dispute issue against this repo, since a public negative signal about a real project needs a correction path before it ships, not as an afterthought.

hyctl oracle verify tests as evidence

Turns a verifier (tests/compile/lint) into a high-D evidence source whose verdict can outweigh a model's opinion.

Usage
hyctl oracle verify go test ./... --source verifier:go-test

hyctl cost spend, honestly labeled

Reads cost.jsonl; tokens_source marks real-vs-estimated, cost_source is always estimated.

Usage
hyctl cost

hyctl stats rollup

Cost rollup by model, routing level, and day: your real spend.

Usage
hyctl stats

hyctl pricing live rates

Live OpenRouter rates, cached 24h, with a static YAML fallback offline.

Usage
hyctl pricing list [filter] [--json]
hyctl pricing refresh

hyctl models runtime registry

Add a model at runtime, no rebuild. Merges into ~/.hydra/models.json.

Usage
hyctl models list
hyctl models add kimi-k3 --provider moonshot --cap-score 85
hyctl models sync   # import the OpenRouter catalog

Routing levels & CapScore how routing decides

Every model gets a CapScore (0-100); tasks route through named routing levels by score. Lower routing level number = stronger.

Routing levelScoreExample models
expert90-100Claude Opus, Claude Code
complex80-89Codex, GPT-class, Gemini Pro
standard70-79Gemini Flash, Claude Haiku
simple60-69Qwen3 8B, Qwen2.5-Coder 7B
local50-59Llama 3.2 3B, Phi-4 Mini

Budget governor spend attention wisely

Static pressure bands downgrade routing levels as usage climbs; a rate-aware first-passage model escalates before a threshold is crossed. The terminal fallback is always the free local model.

claude_pctModeAction
0-49%normalfull orchestration
50-64%compactcompact recommended
65-69%cautioncompact urgently
70-74%warningdowngrade one routing level
75-79%criticalrouting only
80%+emergencyroute to local, warn

PII / local-only enforced, not conventional

With local-only policy on, any prompt containing sensitive data is blocked from leaving your machine at the dispatch layer, before any network call.

Detected

SSNs, credit cards, emails, API keys/tokens, IPs, private-key material → re-routed to a local model.

A2A handoffs causal, conflict-aware

Work passed between agents carries a vector clock for causal ordering; concurrent handoffs touching overlapping files are flagged as conflicts. Saved to logs/last_handoff.json, replayed with --a2a.

The math why the router isn't vibes

Six results run the router: Wald's SPRT, calibration diagnostic power (KL), the Bayes defect-cost bar, Molloy-Reed percolation-κ, Amdahl optimal parallelism, and context entropy, each stated, derived, and interactive.

Open First Principles, six interactive proofs →