productionos-agentic-eval
Niche-agnostic agentic evaluator using CLEAR v2.0 framework — 6-domain assessment, 8 analysis dimensions, 6-tier source prioritization, evidence strength…
Skill by ShaheerKhawaja
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/shaheerkhawaja-productionos-agentic-eval
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: research, agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/productionos-agentic-eval
What's inside
- Skill name
productionos-agentic-eval- Description
- Niche-agnostic agentic evaluator using CLEAR v2.0 framework — 6-domain assessment, 8 analysis dimensions, 6-tier source prioritization, evidence strength ratings, and decision trees. Evaluates any plan, codebase, or research output.
- License
- MIT
- Instructions
- 53 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# productionos-agentic-eval Use this alias when you want the same workflow through a top-level Codex-safe name without the `productionos:` namespace. ## Overview This is the Codex-native workflow wrapper for [.claude/commands/agentic-eval.md](../../.claude/commands/agentic-eval.md). Use it when the user wants this exact ProductionOS workflow, not just the umbrella `productionos` router. ## Source of Truth 1. Read the source command spec at [.claude/commands/agentic-eval.md](../../.claude/commands/agentic-eval.md). 2. Use [CODEX-PARITY-HANDOFF.md](../../docs/CODEX-PARITY-HANDOFF.md) to confirm runtime support and parity expectations. 3. Preserve the source workflow's guardrails, scope, artifacts, and verification intent. 4. Translate Claude-only slash-command and hook semantics into Codex-native execution instead of copying them literally. ## Codex Behavior - Summary: Niche-agnostic agentic evaluator using CLEAR v2.0 framework — 6-domain assessment, 8 analysis dimensions, 6-tier source prioritization, evidence strength ratings, and decision trees. Evaluates any plan, codebase, or research output. - Use the source command as the behavioral spec, then execute the same intent with Codex-native tools and constraints. ## Inputs - `target` — What to evaluate: a file path, directory, or 'latest' for most recent pipeline output Default: `latest` Optional. - `domain` — Evaluation domain or 'auto-detect' Default: `auto-detect` Optional. ## Execution Outline 1. Follow the source command sections in order and preserve its exit criteria. ## Agents And Assets - Agents: no explicit agent references in the source command. - Templates: no explicit shared templates beyond general repo conventions. - Artifacts: `.productionos/EVAL-CLEAR.md` ## Workflow 1. Load only the agents, templates, prompts, and docs referenced by the source command. 2. Execute the workflow intent with Codex-native tools. 3. If the source command implies parallel agent work, only delegate when the user explicitly wants that overhead. 4. Verify with the smallest relevant checks before concluding. 5. Summarize what changed, what was verified, and what still needs human approval. ## Guardrails - Do not claim that Claude-only marketplace, hook, or slash-command behavior runs directly in Codex. - Keep the scope faithful to the source command rather than broadening into a generic repo audit. - Prefer concrete outputs and validation over describing the workflow abstractly. - Preserve the scope and stop conditions from the source command rather than broadening into a generic repo audit.
From ShaheerKhawaja/ProductionOS, MIT.
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Signals
- Stars
- 8
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Apr 3, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/ShaheerKhawaja/ProductionOS
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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- 0.469score
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ProductionOS — dual-target AI engineering operating system for repo-wide audits, upgrade plans, code reviews, strategic product reviews, security sweeps, UX…
SkillDFreshness: D★ 8Claude Code +9 - 0.469score
continuous-learning
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ProductionOS instinct-based learning system.
SkillDFreshness: D★ 8Claude Code +9 - 0.469score
frontend-audit
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ProductionOS frontend quality scanner.
SkillDFreshness: D★ 8Claude Code +9 - 0.469score
security-scan
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ProductionOS security scanner.
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productionos-auto-mode
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productionos-auto-optimize
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Self-improving agent optimization — generates challenger variants of any agent/command, benchmarks against baseline, promotes winners, logs learnings to…
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Cite this page
productionos-agentic-eval skill. Agent Mart. https://agentmart.dev/skills/shaheerkhawaja-productionos-agentic-eval (last updated 2026-10-24)