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Agent skill

Omh Source Finder

by rlaope in rlaope/oh-my-hermes

[omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite…

MITAuto-check passedResearch & Science

Install Omh Source Finder

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

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

GitHub CLI
$ gh skill install rlaope/oh-my-hermes omh-source-finder --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-source-finder .claude/skills/omh-source-finder && 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-source-finder
GitHub stars
3.2k
Token cost
~2.1k tokens
SKILL.md length
921 words
Files
1
Skills in repo
143
Repo updated
First seen
Licence
MIT

At a glance

[omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite…

  • The user says: source-finder
  • 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
  • Source acquisition

What it does

Omh Source Finder is an agent skill from rlaope/oh-my-hermes. [omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite them, or research-brief to turn them into a decision-ready brief. Use when the user says: source-finder, source finder, source acquisition, source intake, find papers and datasets, find datasets and repos, find papers, find arxiv link.

Its SKILL.md is about 2.1k 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 Research & Science, covering Academic paper search and Deep research. It works with arXiv. 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: source-finder
  • Source acquisition
  • Find papers and datasets
  • Find datasets and repos

Example prompts

  • “/omh-source-finder”

What it can do on your machine

Read from SKILL.md and the folder at commit 7cd0d02. 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 Source Finder loads about 2.1k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 921 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~113
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

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 7cd0d02, republished under its MIT licence (© rlaope). 921 words, ~2,069 tokens.

Download SKILL.mdSave it as .claude/skills/omh-source-finder/SKILL.md (or your agent's skills folder).
name
omh-source-finder
description
[omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite them, or research-brief to turn them into a decision-ready brief. Use when the user says: source-finder, source finder, source acquisition, source intake, find papers and datasets, find datasets and repos, find papers, find arxiv link.

Source Finder

This is a Hermes-native source-finder workflow skill.

Why This Exists

source-finder exists so Hermes can turn vague source discovery requests into typed candidates, acquisition status, and downstream workflow choice without pretending OMH searched, downloaded, or verified the material.

Do Not Use When

  • The requested output is factual findings, comparison, or a summary rather than a typed candidate inventory and acquisition status; use research.
  • The user needs a business decision brief with evidence-versus-inference treatment; use research-brief.
  • The user asks for current citations, fact-finding, or source-backed synthesis; use research.
  • The user supplies a paper/PDF/arXiv/DOI/excerpt and wants explanation; use paper-learning.
  • The user asks for recurring monitoring, source inbox, or Scout/Analyst/Briefer operations; use research-department.
  • The user asks to export, convert, render, package, or attach a file; use materials-package or deliverable-package.
  • The user asks for an image card or visual summary; use img-summary.

Examples

Good example:

  • Prompt: source-finder find papers, datasets, and GitHub repos for evaluating browser agent benchmarks.
  • Expected behavior: Prepare source_finder_plan/v1 with typed candidates, acquisition states, missing observed evidence, and downstream choices.
  • Why: The user needs source candidates before deciding whether to learn, research, package, or implement.

Bad example:

  • Prompt: source-finder find current citations and summarize what the sources say.
  • Expected behavior: Route to research because the user asks for current evidence and synthesis, not candidate acquisition status.
  • Why: Source-finder prepares acquisition lifecycle metadata; research owns current evidence synthesis.

Completion Checklist

  • Source kinds, source boundaries, and downstream intent are named.
  • Each candidate has a source_candidate/v1 shape and acquisition state.
  • Observed states include provenance before being treated as evidence.
  • The next downstream workflow is recommended without claiming it ran.
  • Search, download, clone, extraction, hash, license, verification, and downstream processing gaps are explicit.

Recovery Notes

  • If the user asks for facts or citations, route to research.
  • If a candidate lacks a link or file reference, keep it candidate_prepared and ask for the next observable source step.
  • If the user wants to process a selected source, route to the downstream workflow instead of continuing source acquisition.

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 the requested output is a typed source candidate inventory and acquisition status across papers, web links, datasets, GitHub repositories, public presentations, docs/specs, or unknown source material before choosing paper-learning, research, research-brief, research-department, materials-package, or an ultrawork delivery cycle.

Strong routing signals: `source-finder`, `source finder`, `source acquisition`, `source intake`, `find papers and datasets`, `find datasets and repos`, `find papers`, `find arxiv link`, `find arxiv paper`, `find datasets`, `find github repos`, `find oss repos`, `find presentations`, `find public slides`, `find docs and specs`, `find source candidates`, `download candidate`, `source candidate`, `acquisition status`, `자료 후보`, `출처 후보`, `arxiv 링크`, `arxiv 링크 찾아`, `논문 데이터셋 찾아`, `깃허브 저장소 찾아`, `공개 발표자료 찾아`, `문서 스펙 찾아`
Show full SKILL.md (428 more words)Show less

Catalog Metadata

Category: research Phase: source-acquisition Hermes role: researcher Quality tier: source-acquisition-gated Reasoning demand: standard

Quality bar:

  • Name source kinds from: paper, web_link, dataset, github_repo, presentation, docs_spec, unknown.
  • Record acquisition state from: candidate_prepared, link_observed, download_link_prepared, download_observed, file_hash_recorded, text_extraction_observed, license_checked, verification_observed, downstream_selected.
  • Separate candidate preparation, observed link, observed download, file hash, text extraction, license check, verification, and downstream selection.
  • Attach observation provenance before treating any acquisition state as evidence.
  • Vary search angles across official docs, academic work, implementations, datasets, and criticism until each requested source kind has candidates or another angle change adds nothing new.
  • Recommend the next downstream workflow without pretending that downstream work already ran.

Handoff policy:

Keep source acquisition planning in Hermes. Do not claim search, download, clone, extraction, license check, verification, or downstream processing unless a wrapper or user records observed evidence.

Required inputs:

  • source target or topic
  • desired source kinds
  • source boundaries or exclusion criteria
  • downstream intent when known

Expected outputs:

  • source_finder_plan/v1
  • source_candidate/v1
  • source_candidate_set/v1
  • source_acquisition_status/v1
  • downstream workflow recommendation
  • not-evidence boundary

Artifact expectations:

  • source_finder_plan/v1 under .omh/source-finder when a wrapper or CLI records it

Safety rules:

  • Do not claim web search, download, repository clone, file extraction, file hash verification, license verification, or source correctness from a prepared candidate.
  • Do not redefine research-department's source_inbox/v1; source-finder owns source_candidate_set/v1 and source_acquisition_status/v1 only.
  • Route current citations and source-backed synthesis to research, supplied-paper explanation to paper-learning, recurring monitoring to research-department, file export to materials-package, and image cards to img-summary.

Runtime Evidence

Preferred harness for this skill: source-finder.

sh
omh runtime record --skill source-finder --harness source-finder --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-source-finder of rlaope/oh-my-hermes.

Open the folder on GitHubat commit 7cd0d02

Compare with similar skills

Omh Source Finder 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 Source Finder compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Omh Source Finder this skillrlaope/oh-my-hermes3.2k—~2.1kAutomated safety check: PassMIT
Scientific Writingneflibata-feng/MyArxiv-Agent12618 repos~8.4kAutomated safety check: NotesMIT
Paper Expert Generatorguhaohao0991/PaperClaw250—~2kAutomated safety check: PassNone
Rival Search MCPdamionrashford/RivalSearchMCP132—~796Automated safety check: PassMIT
Deep Research Literature SurveyHKUSTDial/Supervisor-Skills8.8k—~2.4kAutomated safety check: PassCC-BY-NC-SA-4.0
Argo Search and Verificationtaxueseek/argo188—~1.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Omh Source Finder

What does Omh Source Finder do?

[omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite…. Omh Source Finder is an agent skill from rlaope/oh-my-hermes. [omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite them, or research-brief to turn them into a decision-ready brief.

When should I use Omh Source Finder?

Omh Source Finder fits situations like: the user says: source-finder; source acquisition; find papers and datasets; find datasets and repos.

How do I install Omh Source Finder in Claude Code?

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

How do I install Omh Source Finder in Codex?

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

Can I use Omh Source Finder 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-source-finder -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-source-finder, .gemini/skills/omh-source-finder, .github/skills/omh-source-finder and .opencode/skills/omh-source-finder in your project.

What does Omh Source Finder need to run?

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

Does Omh Source Finder 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 Source Finder 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 Source Finder use?

Omh Source Finder 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 Source Finder use?

About 2.1k tokens (SKILL.md is roughly 8.3k 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 Source Finder?

Skills that share tags, products or a category with Omh Source Finder: Scientific Writing (neflibata-feng/MyArxiv-Agent, 126 stars), Paper Expert Generator (guhaohao0991/PaperClaw, 250 stars), Rival Search MCP (damionrashford/RivalSearchMCP, 132 stars) and Deep Research Literature Survey (HKUSTDial/Supervisor-Skills, 8.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Omh Source Finder?

rlaope (a GitHub user) maintains it in rlaope/oh-my-hermes, which has 3,243 GitHub stars. The repository holds 143 skills in this directory. The repository was last updated on October 10, 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.