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BC omh-paper-learning

[omh] Paper or paper PDF to understand: explain a supplied paper or paper/PDF at a selected level while preserving full section coverage and source evidence boundaries. Use when the user says: paper-learning, paper learning, paper-explainer, paper explainer, paper explanation, explain this paper, explain this arxiv paper, paper walkthrough.

rlaope/oh-my-hermes Hermes author: rlaope 1 file body ≈ 2 344 tokens Open the sourcegithub.com↗ analyzed 15 h ago

[omh] Paper or paper PDF to understand: explain a supplied paper or paper/PDF at a selected level while preserving full section coverage and source evidence…

As a process C 63/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

ProcedureResearchtype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: omh-paper-learning (rlaope/oh-my-hermes)

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 342 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)

Process rating: all ten parameters 63/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 49 steps
  • 100When it triggers. States when to use and when not to
  • 100Execution cost. Instruction body is 2344 tokens
  • low The response is described with custom markup (8 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 342: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 49 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.