[omh] 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.
SkillScore95Maintained
Automatic
◆Research pack
Last verified 8/19/2026
What it changes
Passed 20 of 21 test cases with the skill, and 4 of 21 without it.
Without skill18%
With skill95%
Checks it passed that the model alone missed
Assigns candidate_prepared state
Outputs source_finder_plan/v1 structure
Sets candidate state to candidate_prepared
and 26 more in the full report
18 fixed3 passed either way0 still failing1 broke
Pass-rate lift
+77 pp
Tokens
+62%
Agent turns
0%
Response time
-11%
Model gemini-3.6-flashMeasured 8/19/2026v321 of 22 cases passed with skill · 21 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 17 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 17
Prompt
We have a paper candidate titled 'LLM Memory Architectures' but no URL or DOI was supplied. What state should be assigned and what action requested?
What was checked, without and with the skill
Checked
Without skill
With skill
Assigns candidate_prepared state
Missed
Passed
Prompts for next observable link or reference step before advancing acquisition stage
Passed
Passed
case-22 · gemini-3.6-flash · 8/19/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md121 linessingle file
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.