sonder-external-positioning

Validates public claims about Sonder Runtime against repository evidence and release gates.

6|3|Updated Jul 3, 2026
One-click install
npx skills add https://github.com/Krilliac/Sonder-runtime --skill sonder-external-positioning-krilliac
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sonder-external-positioning
Source: https://github.com/Krilliac/Sonder-runtime/tree/main/.claude/skills/sonder-external-positioning
Command: npx skills add https://github.com/Krilliac/Sonder-runtime --skill sonder-external-positioning-krilliac

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Teams writing release notes, READMEs, blog posts, or competitor comparisons risk publishing unverified or overstated claims. This Skill decides what Sonder Runtime may publicly claim by tying every statement to grounded code evidence, a proven benchmark run at the current revision, or an explicit open/candidate status. ## Core Features & Use Cases - Claim ledger with proof obligations: Six candidate differentiators (execution-grounded learning, rollback-proven self-modification, privacy-first local learning, bounded fleets, signed TUF releases, measured moat) each mapped to grounding files and required proof runs. - Evidence standards for quoted numbers: Enforces the identity rule (suite, suite version, model digest) and documents exactly what scripts/benchmark_moat.py does and does not prove. - Release-gate workflow: Sequences version identity checks, history privacy scans, artifact integrity, and the TUF signing ceremony before any versioned claim ships. - Use Case: Before publishing release notes claiming a retrieval-quality improvement, run the moat benchmark at the current revision, cite the suite and model digest, and label ecosystem comparisons as unverified background knowledge. ## Quick Start Ask the assistant to review this draft announcement and tell me which claims are grounded, which need a benchmark run, and which must be removed.

Frequently Asked Questions about sonder-external-positioning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I verify a claim before publishing release notes?

Check the claim ledger to see if the claim is grounded in repository code, then run any required proof command at the current revision. Every quoted number must name its suite, suite version, and model digest, and unproven claims must be labeled open or candidate.

How do I benchmark the moat claim for a local model runtime?

Run scripts/benchmark_moat.py with Ollama serving the selected model, optionally with --json and --markdown outputs. It compares bare, cold, and warm retrieval runs on a fixed six-task suite; a personal-moat claim requires injecting a retrieve_fn pointed at your live memory.db.

What is the difference between grounded and proven claims?

Grounded means the claim points at specific code or docs in the repository at the current commit. Proven means a command was actually run at this revision and its output supports the number; mechanism claims need grounding, performance numbers need proof.

Can I compare Sonder against LangSmith or DeepEval in public docs?

Yes, but only as labeled background knowledge dated 2026-08 and unverified against those projects' current state. State architectural differences you can show in your own code, and never present ecosystem comparisons as measured head-to-head results.

Why must release claims avoid the app-latest prerelease channel?

The app-latest tag is a mutable prerelease snapshot that may lag main and is not a versioned, release-ready build. Versioned claims must attach only to app-vX.Y.Z releases that passed the version, artifact-integrity, SBOM, and provenance gates.

What are the limitations of the moat benchmark harness?

It measures retrieval-augmentation lift on one fixed model over a bounded six-task suite, not general capability. Default warm lessons are authored rather than distilled, one stochastic run is only a point estimate, and its prompt shape is pinned and diverges from the current runtime prompt.