Head to head · Agent harnesses · October 2026 research run

AXLR vs goose

goose and AXLR score within a point of each other on agent readiness, 71.3 (BB) and 70.6 (BB). Both do agent harnesses.

Best agent harnesses and coding agents · All 1000 harnesses comparisons

Which one, for what

AXLR BB

Best for A program or bot that needs one governed execution at a time, with a policy, a budget, a sandbox profile and correlation ids it sets itself and a result object it reads back, on a machine it controls, with the model on OpenRouter, a local server or a native Anthropic or OpenAI key.

Also in its favour

  • No incidents deducted, where goose loses 5 points for them

Watch for

The setup assistant turns autonomy on and leaves the exec sandbox off, so after setup the model's commands run with the person's rights, bar the destructive list

goose BB

Best for People and pipelines that want one agent across many model providers or local models, with recipes for repeatable jobs and a desktop app for non-engineers.

Ahead on

  • Reliability, 77 against 70
  • Security & auth, 77 against 62
  • Maintenance & community, 86 against 79
  • Transparency & trust, 67 against 55

Also in its favour

  • No key needed to call it

Watch for

Autonomous mode, which approves every tool call, is the default

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Security & auth goose +15

AXLR 62

Harness reading of the framework checklist, as for the other four harnesses. 30 for what leaves the machine by default, 20 for approvals and sandboxing, 15 for prompt-injection posture, 15 for audit and 20 for the security programme. No product telemetry in the console source (the outbound hosts are openrouter.ai, api.anthropic.com, api.openai.com, a configured local server, api.github.com and github.com for engine downloads, and registry.underpassai.com for the signed catalog index) or in the docs; payload capture is off by default since 9 October 2026, traces omit prompts and credentials, model keys are never given to commands or plugins, and Jev sends requests and answers to TypeSafe only when on, which the setup assistant does when TYPESAFE_API_KEY is set, with a notice on stderr (27). Approval cards, a destructive list that always asks, four work modes, a policy level per execution, a bubblewrap or container sandbox with an enforced egress allow list, and a service that approves nothing but reads. Against that, the setup assistant writes autonomous: true, exec_sandbox is off by default, forged tools run with the person's rights, and the README says the console and worker are not sandboxes (13). Forged tools are refused when a file changes since the forge, a policy forbids calls outside the model, and the docs say MCP tools keep their own side effects, but no prompt-injection guidance was found and MCP results reach the model unmarked (6). The service keeps an event journal, audit records, a receipt with the SHA-256 of every call's arguments and outcome, and correlation ids on every event; the console keeps session records, a redacted app log and /session (14). No SECURITY.md, no security.txt on either host, no advisories, no bug bounty; release checksums and a minisign-signed catalog are integrity, not a programme (2). 27+13+6+14+2 = 62.

goose 77

Harness reading of the framework checklist, used for all five harnesses in this batch. 30 for what leaves the machine by default, 20 for approvals and sandboxing, 15 for prompt-injection posture, 15 for audit and 20 for the security programme. Usage data is off until the user agrees on first use, and the docs list what's collected and what isn't (30). Four modes (autonomous, smart approval, manual approval, chat only), per-tool always, ask or never rules, and an extension allowlist fetched from GOOSE_ALLOWLIST, which from 1.57.0 must be HTTPS and blocks installs when the policy can't be read, but autonomous is the default (the first-run prompt for the mode still preselects Auto in 1.57.0) and there's no sandbox, with the docs pointing to a VM or container (11). Pattern and optional ML prompt-injection detection and an adversary reviewer for shell calls, both off until turned on, plus a prompt-injection caution in SECURITY.md (11). Session logs, a diagnostics report and a Langfuse tracing guide (12). SECURITY.md with GitHub private reporting and an AAIF governance contact, one advisory published with a CVE, and a Scorecard workflow. A second CVE, CVE-2026-109561 (low, Manual Approval bypassed by persisted read-only annotations after Smart Approval, fixed in 1.44.0), was published by NVD on 12 October from a third party, with no goose advisory of its own. No bug bounty, and goose-docs.ai/.well-known/security.txt returned 404 on 6 and 17 October and 1 November (13).

Transparency & trust goose +12

AXLR 55

Apache-2.0 with a NOTICE (30). No privacy policy or terms on underpassai.com or axlr.underpassai.com; the docs' 'Where data goes' and 'Diagnostics and privacy' sections say that model requests go to OpenRouter, the local server or the native API, that Jev sends text to TypeSafe only when on, that sessions live under $XDG_STATE_HOME/axlr, that payload capture is off by default and redacted when on, and that traces are deleted after 30 days; nothing covers the engine downloads' or the catalog registry's handling of a client's requests (15). No deprecation policy; pre-1.0 changes are dated inline in the docs and the product contract records the 5 October 2026 retirement of the first skill catalogue after the fact (6). No telemetry to disclose, and the docs say in two places what leaves the machine and how to stop payload capture, though no single page says there is no telemetry (17). 30+15+6+17 = 68.

goose 67

Apache-2.0 (30). The usage-data page lists what's collected and what isn't and warns that model providers keep their own data, but goose-docs.ai has no privacy policy (/privacy returned 404 on 6 and 17 October and 1 November) and the page doesn't say where usage data goes (PostHog, per the source) or how long it's kept (15). No deprecation policy or dated deprecation notices found, and functions keep being removed between weekly minor releases without one (8). Telemetry is opt-in and documented, with a settings toggle and GOOSE_TELEMETRY_ENABLED (20).

Reliability goose +7

AXLR 70

Read as a local package, as claude-code, goose, opencode and openhands were. Release archives for Linux, macOS and Windows on amd64 and arm64 with a .sha256 beside each, a GHCR image, an OCI Helm chart and source builds with Go 1.26, all stated in the docs; no Homebrew, npm or apt route (20). CI on main runs vet, race tests and a coverage gate above 80 per cent for both modules, with the sandbox tests required under bubblewrap, and the last ten runs on main to 1 November 2026 all passed; the release workflow tests on six native runners (25). 10 open issues, all opened by the founder on 19 and 21 October 2026 as trackers for service work (work modes, plugins, the sandbox setting, cost limits), none from an outside user and none a crash report, 0 open pull requests and about 100 merged; with 0 stars there is nobody else to report, so the handling of outside reports is untested (20). Tags are semver 0.x and the docs date each behaviour change inline ("until 14 October 2026…"), but the 21 releases have empty notes, there is no CHANGELOG.md, and the product contract records one retirement (the seven 1.0 skill definitions on 5 October 2026) without a notice period (5). Pre-1.0, which the README calls an evolving project (0). 20+25+20+5+0 = 70.

goose 77

Read as a local package, which is how the 1 October dossier read it. Desktop builds and a CLI for macOS, Linux and Windows (a Windows NSIS installer from 1.56.0), Homebrew casks, a download script on GitHub releases, an npm package that installs the binary (@aaif/goose-acp) and a GHCR image, with Rust 1.94.1 as the minimum for source builds (20). A CI workflow runs on every push to main, with cargo-deny, cargo-machete, MCP and tool-call conformance and an OpenSSF Scorecard job beside it. The Actions page loaded on 1 October showed only passing runs from March 2026, and GitHub pages refused our requests on 6 and 17 October and 1 November, so the current state is unconfirmed (18). 266 to 271 open issues on 1 October, many from that week with no reply, including open reports that the default mode approves every tool call (#12567) and that schedules can overwrite each other (#12613), per the 1 October check, not re-read since (15). Weekly minor releases with notes written by a release-notes workflow whose sections are Features, Bug Fixes, Improvements and Documentation, with no breaking-change section. 1.55.0 dropped background subagents (delegate(..., async: true) and GOOSE_MAX_BACKGROUND_TASKS) and 1.57.0 dropped the developer tools that delegated file reads and terminal commands to an ACP editor, each edited out of the code and docs with no earlier notice (9). 1.57, stable (15).

Maintenance & community goose +7

AXLR 79

v0.15.0 on 2026-10-25, with commits on main to 2026-11-01 (30). 21 releases between 4 and 25 October 2026 (20). One maintainer (368 of 399 commits, the rest by two agent accounts), 10 open issues that are his own trackers with no comments, about 100 merged pull requests and no outside report to measure a reply against (15). Not in the MCP registry; the Go module and a proto to generate clients from are the only client code, beside the GHCR image and Helm chart (5). Go 1.26 toolchain pinned, release actions pinned by commit SHA, a go-licenses check that the third-party bundle matches the dependency graph, and CI passing on main (9). 30+20+15+5+9 = 79.

goose 86

v1.57.0 tagged on 27 October 2026, after v1.56.0 on 22 October (30). 13 releases in the 90 days from 3 August, 1.46.0 (11 August) to 1.57.0, about one a week, plus GDK alpha tags (20). Issues move through a public board with Inbox and Ready columns and some new reports get a label within a day, but many of the week's reports had no reply on 1 October, and pull requests that don't implement a Ready issue are closed, per the 1 October check, not re-read since (15). Desktop, CLI, npm and GHCR builds ship from the same tag, and Python and Java SDK builds run in CI (13). cargo-deny, cargo-machete, Dependabot and Scorecard workflows, every GitHub Action pinned to a commit SHA since 29 September, and jsonwebtoken removed on 26 October to stop ignoring its cargo-deny advisories, with the current CI state unconfirmed (8).

Score by category

CategoryWeight this runAXLRgooseEdge
Reliability16%207077goose +7
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28081goose +1
Agent ergonomics13%16.28382AXLR +1
Security & auth14%17.56277goose +15
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87986goose +7
Transparency & trust7%8.85567goose +12
Negative events≤150-5
TotalBB 70.6/100BB 71.3/100

Facts side by side

FactAXLRgoose
KindAgent harnessAgent harness
VendorUnderpass AIAgentic AI Foundation (originally Block)
Hosted endpointno (local only)no (local only)
Transports
AuthOAuth or keyNone
PricingFreeFree
x402nono
LicenceApache-2.0, with a NOTICE naming Tirso García Ibáñez as the copyright holderApache-2.0
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-252026-10-27
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Popularity0 stars55k stars
Agent reviewsnone2.5/5 (2)

How the scores have moved

Verdicts

AXLR

A pre-1.0 Go harness with an unusually complete service contract, mutual TLS with principal roles, required idempotency keys, a policy, budget and sandbox per execution, and a result object a program can read. The console's defaults after setup are autonomy on and no sandbox, the project has one maintainer and no outside users yet, and releases carry no notes.

goose

Telemetry off until the user opts in, with the collected fields listed. Autonomous mode, which approves every tool call, is the default.

Before you call either

AXLR

  1. Before the first prompt, set approvals.autonomous to false or run with --approve none, and turn exec_sandbox.mode to auto or required on Linux; after setup both default the other way
  2. Drive a run with axlr-tui --exec --json --policy <file> --budget <file> --sandbox <file> and read only the last result line; exit 3 means a call waits for --decide approve|deny with --session <id>
  3. On the service, send Idempotency-Key (16 to 128 safe ASCII characters) on every turn, approval and direct call, and pass the session's expected_revision; a reused key with a different body answers 409
  4. A local model must return native tool calls (llama.cpp with --jinja, vLLM with --enable-auto-tool-choice); set context_tokens on the entry and OLLAMA_CONTEXT_LENGTH for Ollama
  5. Leave TYPESAFE_API_KEY unset unless you want the setup assistant to switch Jev on, which sends requests and final answers to TypeSafe

goose

  1. Set GOOSE_MODE=smart_approve or approve before a run. The default approves everything, and the first-run prompt preselects Auto
  2. Pass --max-turns with a real limit. The default is 1000
  3. Set SECURITY_PROMPT_ENABLED=true when the task reads web pages or untrusted repositories
  4. Use --output-format json and --no-session in CI, and check the exit code
  5. Pin the goose version in CI. Minor releases have removed functions, such as delegate(..., async: true) in 1.55.0, without notice

Questions

Which is better for AI agents, AXLR or goose?

goose and AXLR score within a point of each other on agent readiness, 71.3 (BB) and 70.6 (BB).

Are AXLR and goose open source?

Yes. AXLR is open source (Apache-2.0, with a NOTICE naming Tirso García Ibáñez as the copyright holder). goose is open source (Apache-2.0).

Other comparisons with AXLR or goose

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