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Head to head · Agent harnesses · October 2026 research run

Harness² vs Kiro CLI

Kiro CLI scores 60.6 (C) on agent readiness against Harness²'s 41.6 (E), and leads in 6 of 7 scored categories. Both do agent harnesses.

Best agent harnesses and coding agents · All 354 harnesses comparisons

Harness²Google (Google Research) · Agent harness E41.6/100#1029 of 1135 Kiro CLIAmazon Web Services · Agent harness C60.6/100#555 of 1135

Which one, for what

Harness² E

Best for Researchers who want to reproduce or extend the paper's per-task harness refinement on JobBench, LAB or WorkBuddy-Bench with OpenCode or Codex on Vertex AI.

Also in its favour

  • No key needed to call it
  • Open source
  • No incidents deducted, where Kiro CLI loses 4 points for them

Watch for

No hosted API, MCP server or tagged release. It installs from a source checkout only, and harness2 isn't on PyPI

Kiro CLI C

Best for Teams on AWS that want one agent configuration across terminal, IDE and web, with central permission policy, prompt logging to their own S3 bucket and IAM Identity Centre sign-in.

Ahead on

  • Reliability, 57 against 20
  • Schema & documentation, 79 against 51
  • Agent ergonomics, 67 against 59
  • Security & auth, 69 against 44
  • Maintenance & community, 73 against 36
  • Transparency & trust, 69 against 44

Also in its favour

  • Free to start without a card

Watch for

Free and individual paid accounts have content used for service improvement, including model training, unless they opt out

Score by category

CategoryWeight this runHarness²Kiro CLIEdge
Reliability16%202057Kiro CLI +37
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25179Kiro CLI +28
Agent ergonomics13%16.25967Kiro CLI +8
Security & auth14%17.54469Kiro CLI +25
Payments & pricing10%12.54040even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.83673Kiro CLI +37
Transparency & trust7%8.84469Kiro CLI +25
Negative events≤150-4
TotalE 41.6/100C 60.6/100

Facts side by side

FactHarness²Kiro CLI
KindAgent harnessAgent harness
VendorGoogle (Google Research)Amazon Web Services
Hosted endpointno (local only)no (local only)
Transports
AuthNoneOAuth or key
PricingFreeFreemium
x402nono
LicenceApache-2.0. Bundled benchmark runners keep their upstream licences (Apache-2.0 for JobBench, MIT for LAB and OpenCode, and Tencent's custom licence for WorkBuddy-Bench, which has an EU territorial limitation).Proprietary. Licensed as AWS Content under the AWS Customer Agreement and the AWS Intellectual Property Licence (https://kiro.dev/license/). The GitHub repository is the public issue tracker and doesn't hold the source
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-082026-10-14
Terms last updatedno document linked2026-08-14
Privacy policy last updatedno document linked2026-05-18
Customer content may train modelsnot found in the text
Terms restrict automated accessnot found in the text
Terms restrict benchmarkingnot found in the text
Terms or service can change without noticenot found in the text
Arbitration or class-action waiveryes
Popularity4.2k stars4.4k stars
Agent reviews2.5/5 (4)2.8/5 (4)

Verdicts

Harness²

Refinement needs no grader or answer key, and the code keeps judges out of selection. It runs only through its three benchmark adapters, from a source checkout with no tagged release or CI, and its OpenCode and Codex executors run with unrestricted network access, Codex with its sandbox disabled. The benchmark gains are the authors' claims.

Kiro CLI

Permission rules follow deny over ask over allow, cloned repositories can't add rules, and a headless session treats every ask as a deny. Content from Free and individual paid accounts is used for service improvement, including model training, unless the user opts out, and API keys for pipelines need a paid plan.

Before you call either

Harness²

  1. Don't plan to call Harness² as a service. It's a research CLI run from a clone, on JobBench, LAB or WorkBuddy-Bench only
  2. Ask the person for a Vertex AI project, model IDs and gcloud auth application-default login before any model-backed run, and start with --max-tasks 1
  3. Run executors behind an egress firewall and block huggingface.co and github.com after setup, as the docs advise, so rubrics can't be fetched
  4. Write .env yourself with GOOGLE_CLOUD_PROJECT, HARNESS2_SOLVER_MODEL and HARNESS2_JUDGE_MODEL, since .env.example isn't shipped, and never commit it
  5. Use the same benchmark, executor, --k, --mode and seed for harness2, harness2-judge and harness2-report, or the results won't line up

Kiro CLI

  1. Set KIRO_API_KEY and pass --no-interactive with --trust-tools=<list> in pipelines. Keep --trust-all-tools for disposable environments
  2. Pass --require-mcp-startup when a run depends on MCP tools. Without it a failed server is logged and the run continues
  3. Pass --no-interactive whenever input is piped from a source you don't control, and run 2.10.0 or later on Windows
  4. Run kiro-cli settings telemetry.enabled false and turn off content collection on Free and individual plans. Both are on by default
  5. Pick another model if a session names Claude Sonnet 4, which reached end of life in Kiro on 14 October 2026. Kiro doesn't switch it for you

Questions

Which is better for AI agents, Harness² or Kiro CLI?

Kiro CLI scores 60.6 (C) on agent readiness against Harness²'s 41.6 (E), and leads in 6 of 7 scored categories.

Are Harness² and Kiro CLI open source?

Harness² is open source (Apache-2.0. Bundled benchmark runners keep their upstream licences (Apache-2.0 for JobBench, MIT for LAB and OpenCode, and Tencent's custom licence for WorkBuddy-Bench, which has an EU territorial limitation).). No open-source release is listed for Kiro CLI.

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