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jbaruch/coding-policy

tessl

Coding policy tile for Baruch's AI agents. Language-agnostic code quality rules plus Tessl-specific plugin authoring standards — covering commits, testing, error handling, skill structure, script delegation, and eval quality.

What's New

  • 16 always-on steering rules: 8 covering code quality, 5 covering plugin authoring, 1 covering author-model declaration, 1 covering concurrency, 1 covering review discipline
  • release skill — structured PR + merge workflow with Copilot review and paired-reviewer cross-family enforcement
  • eval-authoring skill — generate, review, and curate eval scenarios with score-driven iteration
  • install-reviewer skill — scaffold the paired gh-aw PR review workflows (OpenAI + Anthropic) into a consumer repo
  • 0.3.0 added install-reviewer upgrade mode (--override) — refreshes scaffolded reviewer files in place instead of requiring a manual git rm-and-rerun
  • 0.2.0 lifted with-context attainment from 93 to 98 (3× avg, lift +17 → +22) by tuning skill prose against eval log analysis
  • Language-agnostic: works with any stack, no Python/JS assumptions

See CHANGELOG.md for full version history.

Installation

tessl install jbaruch/coding-policy

What's Included

Category Rule Summary
Git commit-conventions Imperative mood, one change per commit, PR hygiene
Testing testing-standards Outcome-based, deterministic, no binary fixtures
Errors error-handling Specific exceptions (with outer-boundary process-contract carve-out), actionable messages, structured logging
Deps dependency-management Stdlib-first, pinned versions, lock files
Files file-hygiene Proper .gitignore, no generated files committed
CI ci-safety Never skip tests, never modify CI without asking
Secrets no-secrets No credentials in code, env vars or secrets manager
Style code-formatting Use project's formatter, don't mix style with logic
Authoring context-artifacts Plugin structure, rule format, review iteration, surface sync, consistency checks
Authoring skill-authoring SKILL.md structure, step numbering, typed calls, tile.json reference
Authoring script-delegation Deterministic → script, reasoning → LLM, the regex trap
Authoring plugin-evals No bleeding, no leaking, persistent eval coverage
Authoring stateful-artifacts Cross-invocation state: schema, owner skill, schema_version, hints-not-authority, migration
Review author-model-declaration PRs declare author model; paired reviewers pick the cross-family one
Concurrency agent-worktree-isolation Mandatory git worktrees for concurrent agent work; cleanup; read-only exception
Discipline boy-scout Leave it better than you found it; "pre-existing" is not a valid concept; in-scope cleanups bundle, out-of-scope ones get filed

Skills

Skill Description
release PR creation, Copilot review, merge + cleanup workflow
eval-authoring Generate, review, iterate on eval scenarios with score-driven feedback
install-reviewer Scaffold the paired gh-aw PR review workflows (OpenAI + Anthropic) into a consumer repo — reviews every PR against the latest published jbaruch/coding-policy with cross-family enforcement. Supports --override for in-place upgrades.

Philosophy

  • Language-agnostic code rules. The code quality rules (commits through formatting) apply to Python, TypeScript, Go, Rust, Java — any language. No framework-specific assumptions.
  • Tessl-specific authoring rules. The authoring rules (context-artifacts through plugin-evals) are specific to the Tessl plugin workflow. They codify how to build, test, and ship tiles.
  • One concern per rule. Each file covers one topic. Easy to read, easy to reference, easy to override if a project needs an exception.
  • Opinionated but practical. These rules reflect real patterns found across 17+ repositories and the Tessl plugin authoring workflow. They solve problems that actually come up when agents write and ship code.
  • Always on. Every rule is alwaysApply: true. Agents follow these conventions without being reminded.

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General-purpose coding policy tile for AI agents

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