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Agent skill

Omh Data Analysis

by rlaope in rlaope/oh-my-hermes

[omh] Dataset or table to analyze: scope supplied data with provenance, causal-claim, and hallucination guards.

MITAuto-check passedData & Analytics

Install Omh Data Analysis

skills CLI
$ npx skills add rlaope/oh-my-hermes --skill omh-data-analysis -a claude-code

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

GitHub CLI
$ gh skill install rlaope/oh-my-hermes omh-data-analysis --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/rlaope/oh-my-hermes.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/omh-data-analysis .claude/skills/omh-data-analysis && 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
omh-data-analysis
GitHub stars
3.2k
Token cost
~1.8k tokens
SKILL.md length
830 words
Files
1
Skills in repo
143
Repo updated
First seen
Licence
MIT

At a glance

[omh] Dataset or table to analyze: scope supplied data with provenance, causal-claim, and hallucination guards.

  • The user says: data-analysis
  • SKILL.md covers Why This Exists, Do Not Use When, Examples and Completion Checklist, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Dataset analysis

What it does

Omh Data Analysis is an agent skill from rlaope/oh-my-hermes. [omh] Dataset or table to analyze: scope supplied data with provenance, causal-claim, and hallucination guards. Use when the user says: data-analysis, data analysis, dataset analysis, csv analysis, json analysis, log analysis, table analysis, analyze csv.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Data analysis and CSV and tabular files. The repository describes itself as: All in one plugin for Hermes Agent ⚚ the coding intelligence, a long-term memory system and model optimized workflow packages. The licence is MIT.

When your agent uses it

  • The user says: data-analysis
  • Dataset analysis

Example prompts

  • “/omh-data-analysis”

What it can do on your machine

Read from SKILL.md and the folder at commit f772a94. 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 (its code samples are bash).

    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

Omh Data Analysis loads about 1.8k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 830 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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 rlaope/oh-my-hermes at commit f772a94, republished under its MIT licence (© rlaope). 830 words, ~1,794 tokens.

Download SKILL.mdSave it as .claude/skills/omh-data-analysis/SKILL.md (or your agent's skills folder).
name
omh-data-analysis
description
[omh] Dataset or table to analyze: scope supplied data with provenance, causal-claim, and hallucination guards. Use when the user says: data-analysis, data analysis, dataset analysis, csv analysis, json analysis, log analysis, table analysis, analyze csv.

Data Analysis

This is a Hermes-native data-analysis workflow skill.

Why This Exists

data-analysis exists so Hermes users can ask for this workflow in chat and get a structured, checkable answer instead of an improvised one.

Do Not Use When

  • The request is already handled by a narrower explicit skill with stronger evidence.
  • The user asks OMH to secretly run external platforms, connectors, schedulers, file exports, or runtime agents.
  • The only safe answer is to ask for missing authority, credentials, target, or observed evidence first.

Examples

Good example:

  • Prompt: data-analysis analyze this CSV and summarize anomalies by segment.
  • Expected behavior: Produce prepare_data_analysis_card with required context, wrapper actions, and not-evidence boundaries.
  • Why: The prompt names a real workflow surface that Hermes can orchestrate without hiding execution.

Bad example:

  • Prompt: data-analysis invent trends from an unavailable spreadsheet.
  • Expected behavior: Report the missing observed evidence or authority instead of claiming the external step happened.
  • Why: Prepared OMH guidance is not platform, runtime, connector, file, memory, or delivery evidence.

Completion Checklist

  • Dataset or corpus source, record scope, schema or extraction method, join assumptions, analysis question, method, and stop condition are explicit.
  • Numeric claims, anomalies, trends, segments, and log patterns are reported only from observed data or supplied evidence.
  • Causal claims require observed identification evidence.
  • Source acquisition, file conversion, report generation, and code fixes are routed to the narrower workflow when stronger.

Recovery Notes

  • If the data itself is missing, ask for the smallest dataset sample, schema, or query output needed.
  • If the user wants datasets found online, route to source-finder before analysis.
  • If the user wants a PPT/PDF/XLSX report generated from data, route to materials-package or deliverable-package after analysis scope is clear.

Workflow Lane

  • Current lane: Research and company ops (product-docs, source-finder, web-research, research, model-optimization, inference-serving, model-finetuning, research-brief, +20 more) - research, signals, ops, and briefings.
  • If intent belongs to another lane, hand back to oh-my-hermes or name the adjacent workflow.
  • Shared product, routing, compatibility, and evidence rules: omh-routing/references/skill-common-rail.md.

Use When

Use when Hermes should prepare supplied structured, unstructured, or mixed data analysis without unsupported numeric or causal claims.

Strong routing signals: `data-analysis`, `data analysis`, `dataset analysis`, `csv analysis`, `json analysis`, `log analysis`, `table analysis`, `analyze csv`, `analyze this csv`, `analyze json`, `analyze logs`, `summarize anomalies`, `anomaly analysis`, `trend analysis`, `segment analysis`, `column analysis`, `schema check`, `table to chart`, `chart with an executive summary`, `spreadsheet delta analysis`, `cohort analysis`, `retention analysis`, `correlation analysis`, `causal analysis`, `causality check`, `데이터 분석`, `csv 분석`, `json 분석`, `로그 분석`, `이상치 분석`, `추세 분석`, `오류 패턴`, `컬럼 분석`, `전환율 델타`, `차트 요약`, `상관관계 분석`, `인과 분석`, `인과관계`
Show full SKILL.md (404 more words)Show less

Catalog Metadata

Category: analysis Phase: data-task Hermes role: guide Quality tier: workflow-surface-gated Reasoning demand: standard

Quality bar:

  • Name the user-facing workflow objective, required context, next action, and stop condition.
  • Separate prepared guidance from observed platform, runtime, connector, file, memory, or delivery evidence.
  • Expose missing tools, credentials, targets, or observations as user-visible gaps.

Handoff policy:

Keep this as Hermes-facing orchestration guidance first. Prepare executor, connector, gateway, or host-runtime handoff only when the user accepts that next step and observed evidence can be recorded.

Required inputs:

  • user request
  • target context
  • delivery or status expectation
  • known missing evidence

Expected outputs:

  • data_analysis_task_card/v1
  • dataset_scope/v1
  • analysis_method_plan/v1
  • operations_data_harness/v1
  • product_evidence_loop/v1
  • analysis_result_summary/v1 when observed
  • next action
  • prepared-vs-observed boundary

Artifact expectations:

  • data_analysis_task_card/v1 metadata-only wrapper card when prepared
  • dataset_scope/v1 with source, row/record scope, columns or schema, filters, and stop condition
  • analysis_method_plan/v1 naming summary, anomaly, trend, segment, schema, or log-pattern methods
  • operations_data_harness/v1 for relationship and causal boundaries
  • product_evidence_loop/v1 for prepared opaque data reference metadata
  • analysis_result_summary/v1 only from observed data, calculations, query output, or supplied evidence

Safety rules:

  • A data analysis card is not file extraction, query execution, chart generation, statistical proof, data correctness, hallucination-safe numeric evidence, association, or causality unless observed data and method evidence records it.
  • Do not claim connector, gateway, runtime, file generation, memory mutation, or host automation evidence from prepared guidance.

Runtime Evidence

Preferred harness for this skill: data-analysis.

sh
omh runtime record --skill data-analysis --harness data-analysis --status started

Record observed delegation results; otherwise return not_available or not_observed. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence.

  • Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. Preserve workflow intent and stop conditions; verify before claiming completion. Reply in the user's own words and the host's own voice: its SOUL.md persona owns reply language, tone, speech level, and sentence endings, progress updates included (where it sets no language, use the one the user wrote in), and OMH shapes structure and content only; OMH's record terms (surface, lane, wrapper, handoff, evidence boundary, not_observed) stay in records and tool calls, never in the sentence the user reads unless they ask about one; and when a stop condition or a decision the user owns ends the turn, offer the next action as a question rather than declaring what will not be done.

Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.

Shared product, compatibility, topology, memory, harness, and execution rules: omh-routing/references/skill-common-rail.md. Load it when applicable; otherwise name an unavailable capability.

© rlaope, MIT. 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 skills/omh-data-analysis of rlaope/oh-my-hermes.

Open the folder on GitHubat commit f772a94

Compare with similar skills

Omh Data Analysis 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.

Omh Data Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Omh Data Analysis this skillrlaope/oh-my-hermes3.2k—~1.8kAutomated safety check: PassMIT
Excel and CSV Data Analysisbytedance/deer-flow83k4 repos~2.2kAutomated safety check: PassMIT
Exploratory Data AnalysisOleafly/Oleafly2063 repos~3.4kAutomated safety check: NotesMIT
Eqtl Catalogue Region FetchClawBio/ClawBio1.2k1 repos~4.3kAutomated safety check: PassMIT
Raccoon DataanalysisSenseTime-Copilot/raccoon-dataanalysis-skill137—~1.9kAutomated safety check: PassNone
CSV Data Analysis5zjk5/prompt-engineering127—~2.6kAutomated safety check: PassNone

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Categories

Questions about Omh Data Analysis

What does Omh Data Analysis do?

[omh] Dataset or table to analyze: scope supplied data with provenance, causal-claim, and hallucination guards. Omh Data Analysis is an agent skill from rlaope/oh-my-hermes. [omh] Dataset or table to analyze: scope supplied data with provenance, causal-claim, and hallucination guards.

When should I use Omh Data Analysis?

Omh Data Analysis fits situations like: the user says: data-analysis; dataset analysis.

How do I install Omh Data Analysis in Claude Code?

Run `npx skills add rlaope/oh-my-hermes --skill omh-data-analysis -a claude-code`. Or copy the skill folder (skills/omh-data-analysis in rlaope/oh-my-hermes) into .claude/skills/omh-data-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Omh Data Analysis in Codex?

Run `npx skills add rlaope/oh-my-hermes --skill omh-data-analysis -a codex`. Or copy the skill folder (skills/omh-data-analysis in rlaope/oh-my-hermes) into .agents/skills/omh-data-analysis in your project. Codex loads it when a task matches its description.

Can I use Omh Data Analysis 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 rlaope/oh-my-hermes --skill omh-data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/omh-data-analysis, .gemini/skills/omh-data-analysis, .github/skills/omh-data-analysis and .opencode/skills/omh-data-analysis in your project.

What does Omh Data Analysis need to run?

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

Does Omh Data Analysis 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 Omh Data Analysis 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 Omh Data Analysis use?

Omh Data Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Omh Data Analysis use?

About 1.8k tokens (SKILL.md is roughly 7.2k 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 Omh Data Analysis?

Skills that share tags, products or a category with Omh Data Analysis: Excel and CSV Data Analysis (bytedance/deer-flow, 83k stars), Exploratory Data Analysis (Oleafly/Oleafly, 206 stars), Eqtl Catalogue Region Fetch (ClawBio/ClawBio, 1.2k stars) and Raccoon Dataanalysis (SenseTime-Copilot/raccoon-dataanalysis-skill, 137 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Omh Data Analysis?

rlaope (a GitHub user) maintains it in rlaope/oh-my-hermes, which has 3,207 GitHub stars. The repository holds 143 skills in this directory. The repository was last updated on October 8, 2026.

Source: rlaope/oh-my-hermes on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.