SKILLEMALL.ai

CF orx-reports

Save and organize durable research outputs in the artifacts directory. Invoke when creating or reorganizing a report, exported dataset, or other deliverable; use `orx-results` for analysis and `orx-figures` when constructing charts.

alphaXiv/OpenResearch Agent Skills author: alphaXiv MIT 1 file body ≈ 499 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Save and organize durable research outputs in the artifacts directory.

As a process F 18/100 · No process to follow — References files that are not bundled: figures/patch-size.svg, artifacts/<relative-path>

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
F
18/100
No process to follow
References files that are not bundled: figures/patch-size.svg, artifacts/<relative-path>
Tools and files w 18
0
Steps w 15
0
Result and completion w 14
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 missing-ref reference to a missing file: figures/patch-size.svg
  • warning missing-ref reference to a missing file: artifacts/<relative-path>

Process rating: all ten parameters 18/100

Will not run. References files that are not bundled: figures/patch-size.svg, artifacts/<relative-path>
  • 0Tools and files. 2 referenced file(s) missing: figures/patch-size.svg, artifacts/<relative-path>
  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 499 tokens

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)
  • +4Structure: 0 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 232: enough signal without eating the budget
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.