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zack-dev-cm

Open Feed Recsys Reviewer

by Zakhar Pashkin · GitHub ↗ · v1.0.4 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install open-feed-recsys-lab
Description
Review open feed recommendation repositories with source-backed evidence, artifact-readiness checks, and cautious architecture summaries. Use when a user ask...
README (SKILL.md)

Open Feed Recsys Lab

Use this skill to review public feed recommendation repositories and separate what the source supports from what remains unproven.

Default target: https://github.com/xai-org/x-algorithm.

Review Workflow

  1. Confirm the target repository, commit, public link, or user-provided file set.
  2. Build an evidence ledger with repository/ref, files inspected, supported claims, weak claims, and open questions.
  3. Separate source inspection from runnable-model proof. If Phoenix artifacts are missing, say execution is not verified.
  4. Map the visible architecture: Home Mixer, Phoenix retrieval/ranking, Thunder, Grox, ads blending, and candidate pipelines when present.
  5. Treat public algorithm claims as hypotheses. Mark each claim supported, partly_supported, unsupported, or not_public_repo.
  6. Frame shareable output around reproducibility and evidence. Do not present the public source as a reach predictor or full live-platform clone.

Phoenix Artifact Readiness

Only treat Phoenix execution as verified after the official artifacts are present and the user has supplied a local run result. The expected extracted directory is:

phoenix/artifacts/oss-phoenix-artifacts/

Expected files include:

  • retrieval/model_params.npz
  • retrieval/embedding_tables.npz
  • retrieval/config.json
  • ranker/model_params.npz
  • ranker/embedding_tables.npz
  • ranker/config.json
  • sports_corpus.npz
  • example_sequence.json

If the report says Phoenix is not run-ready, state that source inspection succeeded but execution is blocked by missing extracted LFS artifacts.

Boundaries

  • Use public source or user-provided local files only.
  • Do not request or inspect private user data, authenticated account pages, or non-public analytics.
  • Do not promise reach, ranking, virality, revenue, or live-platform equivalence.
  • Do not claim that public source contains every production weight, threshold, model version, or serving rule.
  • Do not execute repository code or delete local files as part of a review unless the user separately asks for that engineering work.

Output Shape

Return a concise review with:

  • Target: repo, ref, and source date when known.
  • Supported: claims backed by public source.
  • Blocked: missing artifacts, missing configs, or live-platform gaps.
  • Architecture: short component map.
  • Risks: overclaims, ambiguous evidence, or unsafe product positioning.
  • Next check: the smallest concrete verification step.

The preferred public-safe framing is:

I verified the open X For You algorithm locally at commit \x3Csha>; here is the report.

Companion Skills

Use x-algo-claim-auditor when the user asks whether a public claim, screenshot text, or viral thread is supported by the source.

Use tinytroupe-feed-research-lab when the user asks to compare draft posts, simulate audience reactions, or pretest a post before publishing. Keep that work labeled as synthetic audience research, not source verification or reach prediction.

Usage Guidance
This skill appears safe to install for source-backed reviews of public recommender-system repositories. As with any repo-review skill, only provide local files you intend the agent to inspect, and separately approve any engineering work if you later ask it to run code.
Capability Analysis
Type: OpenClaw Skill Name: open-feed-recsys-lab Version: 1.0.4 The skill bundle is designed to analyze open-source recommendation system repositories, specifically targeting the X (formerly Twitter) algorithm. The instructions in SKILL.md emphasize evidence-based reporting, artifact verification, and explicitly forbid accessing private user data or executing code without permission. No indicators of malicious intent, data exfiltration, or unauthorized execution were found.
Capability Assessment
Purpose & Capability
The stated purpose and instructions are coherent: review public feed recommendation repositories, distinguish supported from unsupported claims, and summarize architecture cautiously.
Instruction Scope
The skill explicitly limits review to public source or user-provided files and tells the agent not to inspect private data, authenticated pages, or non-public analytics.
Install Mechanism
There is no install spec, no required binaries, no code files, and no package installation behavior.
Credentials
No environment variables, credentials, network services, or elevated local permissions are requested.
Persistence & Privilege
The artifacts do not show persistence, background execution, credential use, or privilege escalation.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install open-feed-recsys-lab
  3. After installation, invoke the skill by name or use /open-feed-recsys-lab
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.4
Add companion routing for claim audits and TinyTroupe-inspired synthetic draft research.
v1.0.3
Republish public package as a source-backed review skill with narrowed ClawHub files.
v1.0.2
Add companion claim-auditor routing guidance while preserving the reproducibility report workflow.
v1.0.1
Align public license metadata with ClawHub MIT-0 registry display after the initial release.
v1.0.0
Initial public release for commit-pinned reports, Phoenix artifact checks, documentation mismatch detection, and architecture maps for open feed recommendation repos.
Metadata
Slug open-feed-recsys-lab
Version 1.0.4
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 5
Frequently Asked Questions

What is Open Feed Recsys Reviewer?

Review open feed recommendation repositories with source-backed evidence, artifact-readiness checks, and cautious architecture summaries. Use when a user ask... It is an AI Agent Skill for Claude Code / OpenClaw, with 123 downloads so far.

How do I install Open Feed Recsys Reviewer?

Run "/install open-feed-recsys-lab" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Open Feed Recsys Reviewer free?

Yes, Open Feed Recsys Reviewer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Open Feed Recsys Reviewer support?

Open Feed Recsys Reviewer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Open Feed Recsys Reviewer?

It is built and maintained by Zakhar Pashkin (@zack-dev-cm); the current version is v1.0.4.

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