[OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries.

AGPL-3.0Auto-check passed

Install Analyze

skills CLI
$ npx skills add yangyuan-zhen/PolyWeather --skill analyze -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yangyuan-zhen/PolyWeather analyze --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/analyze .claude/skills/analyze && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
analyze
GitHub stars
316
Token cost
~1.6k tokens
SKILL.md length
853 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
AGPL-3.0

At a glance

[OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries.

  • Works in 3 steps: Evidence — directly supported by… → Inference — a reasoned conclusion drawn… → Unknown — a question the current…
  • A user says analyze
  • SKILL.md covers Use $analyze when, Do not use $analyze when, Non-negotiable contract and Question-aligned synthesis, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Analyze is an agent skill from yangyuan-zhen/PolyWeather. [OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries. Use when a user says 'analyze', 'investigate', 'why does', 'what's causing', or needs grounded cross-file explanation before any changes are proposed.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: polymarket Intelligent Weather Quant Analysis Bot. The licence is AGPL-3.0.

When your agent uses it

  • A user says analyze
  • Needs grounded cross-file explanation before any changes are proposed

Example prompts

  • “analyze”
  • “investigate”
  • “why does”
  • “/analyze”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Evidence — directly supported by concrete repository artifacts
  2. Inference — a reasoned conclusion drawn from evidence
  3. Unknown — a question the current repository evidence does not resolve

What it can do on your machine

Read from SKILL.md and the folder at commit 43e658b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Analyze loads about 1.6k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 853 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~82
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from yangyuan-zhen/PolyWeather at commit 43e658b, republished under its AGPL-3.0 licence (© yangyuan-zhen). 853 words, ~1,626 tokens.

Download SKILL.mdSave it as .claude/skills/analyze/SKILL.md (or your agent's skills folder).
name
analyze
description
[OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries. Use when a user says 'analyze', 'investigate', 'why does', 'what's causing', or needs grounded cross-file explanation before any changes are proposed.

Analyze — Read-Only Deep Analysis

Use this skill to answer the user’s question through read-only repository analysis. The goal is to explain what the codebase most likely says about the question, not to drift into implementation, debugging theater, or generic fix planning.

Use $analyze when

  • the user wants a grounded explanation, not code changes
  • the answer requires reading multiple files or tracing behavior across boundaries
  • there are several plausible explanations and they need to be ranked
  • confidence should reflect the strength of the available evidence
  • the user wants to understand architecture, behavior, causality, impact, or tradeoffs before changing anything

Examples:

  • why a workflow behaves a certain way
  • how a feature is wired across modules
  • what likely explains a failure, regression, or mismatch
  • what would be impacted by changing a dependency or contract
  • which interpretation of the current codebase is best supported

Do not use $analyze when

  • the user explicitly wants code edits, a fix, or execution — use the appropriate implementation lane instead
  • the user wants a new product plan or acceptance criteria — use $plan / $ralplan
  • the request is a simple one-file fact lookup — read the file and answer directly
  • the request is purely about running the OMX tmux team runtime — use $team only when OMX runtime is active

Non-negotiable contract

Analyze is read-only by contract.

  • Do not edit files.
  • Do not turn the answer into an implementation plan.
  • Do not recommend fixes as the primary output.
  • Do not silently switch into execution work.
  • Do not overclaim certainty.
  • Do not invent facts that are not supported by repository evidence.
  • Do not use judgmental, normative, or speculative language that outruns the evidence.

If a next step is helpful, keep it to a discriminating read-only probe that would reduce uncertainty.

Question-aligned synthesis

Answer the user’s actual question first.

  • Start from the asked question, not a generic debugger template.
  • Keep the synthesis scoped to what the user needs to know.
  • Scale the depth to the request: for simple or obvious questions, reduce swarm intensity and answer directly after enough reading.
  • For broader questions, expand the search surface but keep the final answer tightly synthesized.

Evidence rules

Maintain an explicit evidence-vs-inference distinction. Every material claim must be labeled as one of:

  1. Evidence — directly supported by concrete repository artifacts
  2. Inference — a reasoned conclusion drawn from evidence
  3. Unknown — a question the current repository evidence does not resolve

Never present an inference as if it were direct evidence. Never present a guess as if it were an inference. Call out uncertainty explicitly when the codebase does not settle the question.

Acceptable evidence

Prefer stronger evidence over weaker evidence:

  1. direct code paths, contracts, tests, generated artifacts, configs, or docs with concrete file references
  2. multiple independent files pointing to the same conclusion
  3. localized behavioral inference from well-supported code structure
  4. weaker contextual clues that remain explicitly marked as tentative

Unsupported speculation is not evidence.

Show full SKILL.md (374 more words)Show less

Parallel exploration policy

Parallel exploration is allowed when it improves quality, but it must stay runtime-safe.

  • Default to direct read-only analysis when the answer is simple.
  • When parallelism helps, prefer native subagents by default or equivalent in-session parallel exploration when available.
  • Keep parallel lanes bounded: each lane should answer a concrete sub-question or inspect a specific subsystem.
  • Use $team only when OMX runtime is active and durable tmux-based coordination is actually needed.
  • Do not imply that $team is available in plain Codex/App sessions.

A good default split for complex analysis is:

  • one lane for primary code path / contracts
  • one lane for config / orchestration / generated surfaces
  • one lane for tests / docs / secondary corroboration

Execution policy

  • Default to outcome-first progress and completion reporting: state the question, evidence, inference boundaries, and stop condition before adding process detail.
  • Treat newer user task updates as local overrides for the active workflow branch while preserving earlier non-conflicting constraints.
  • If the user says continue, keep working from the current analysis state instead of restarting discovery.

Working method

  1. Restate the question in one sentence.
  2. Identify the smallest set of files most likely to answer it.
  3. Read for direct evidence first.
  4. If needed, open bounded parallel exploration lanes.
  5. Compare competing explanations.
  6. Rank the explanations by support.
  7. Return a synthesis that clearly separates evidence from inference.

Output contract

Structure the answer so the user can see what is known, what is inferred, and how confident the synthesis is.

Question

[Restate the user’s question briefly]

Ranked synthesis
RankExplanationConfidenceBasis
1...High / Medium / Lowstrongest supporting evidence
2...High / Medium / Lowwhy it trails
3...High / Medium / Lowwhy it remains possible
Evidence
  • path/to/file:line-line — what this artifact directly shows
  • path/to/file:line-line — corroborating evidence
Inference
  • What the evidence most strongly implies
  • Why weaker alternatives were down-ranked
Unknowns / limits
  • What the repository evidence does not establish
  • What would need to be checked next to reduce uncertainty

Quality bar

A good analyze response is:

  • read-only and question-aligned
  • ranked rather than flat
  • explicit about confidence
  • concrete about file references
  • careful about evidence vs inference
  • free of unsupported speculation
  • free of normative drift or judgmental filler
  • explicit about the evidence-vs-inference distinction
  • concise for simple cases, broader only when the question truly needs it

© yangyuan-zhen, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .codex/skills/analyze of yangyuan-zhen/PolyWeather.

Open the folder on GitHubat commit 43e658b

Compare with similar skills

Analyze next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Analyze compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Analyze this skillyangyuan-zhen/PolyWeather316—~1.6kAutomated safety check: PassAGPL-3.0
Returns Reverse Logisticssickn33/agentic-awesome-skills47k8 repos~6.4kAutomated safety check: PassMIT
Returns Reverse Logisticsaffaan-m/ECC276k2 repos~2.3kAutomated safety check: PassApache-2.0
Returns Reverse Logisticsaffaan-m/ECC276k—~2.9kAutomated safety check: PassApache-2.0
Returner Cvmohitagw15856/pm-claude-skills1.4k—~890Automated safety check: PassMIT
Ecommerce Returns Managementnexscope-ai/eCommerce-Skills1.1k—~602Automated safety check: PassMIT

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Questions about Analyze

What does Analyze do?

[OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries. Analyze is an agent skill from yangyuan-zhen/PolyWeather. [OMX] Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries.

When should I use Analyze?

Analyze fits situations like: A user says analyze; needs grounded cross-file explanation before any changes are proposed.

How do I install Analyze in Claude Code?

Run `npx skills add yangyuan-zhen/PolyWeather --skill analyze -a claude-code`. Or copy the skill folder (.codex/skills/analyze in yangyuan-zhen/PolyWeather) into .claude/skills/analyze in your project. Claude Code loads it when a task matches its description.

How do I install Analyze in Codex?

Run `npx skills add yangyuan-zhen/PolyWeather --skill analyze -a codex`. Or copy the skill folder (.codex/skills/analyze in yangyuan-zhen/PolyWeather) into .agents/skills/analyze in your project. Codex loads it when a task matches its description.

Can I use Analyze in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yangyuan-zhen/PolyWeather --skill analyze -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze, .gemini/skills/analyze, .github/skills/analyze and .opencode/skills/analyze in your project.

What does Analyze need to run?

SKILL.md names no scripts, command-line tools or credentials: Analyze is instructions for the agent only.

Does Analyze access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Analyze safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Analyze use?

Analyze is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analyze use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Analyze?

Skills that share tags, products or a category with Analyze: Returns Reverse Logistics (sickn33/agentic-awesome-skills, 47k stars), Returns Reverse Logistics (affaan-m/ECC, 276k stars), Returns Reverse Logistics (affaan-m/ECC, 276k stars) and Returner Cv (mohitagw15856/pm-claude-skills, 1.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyze?

yangyuan-zhen (a GitHub user) maintains it in yangyuan-zhen/PolyWeather, which has 316 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on September 20, 2026.

Source: yangyuan-zhen/PolyWeather on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.