AC nextcloud
Nextcloud file and folder management via WebDAV + OCS API. Use when: (1) creating, reading, writing, renaming, moving, copying, or deleting files/folders, (2) listing or searching directory contents, (3) toggling favorites or managing system tags, (4) checking storage quota. NOT for: Nextcloud Talk, Calendar/Contacts (use CalDAV), app management (requires admin), large binary transfers, or creating share links (share capability not included by default - see README).
Nextcloud file and folder management via WebDAV + OCS API.
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
How to improve
- 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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "ontology"
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 10 mutating operations with no state check
- 40Consistency. Frontmatter name (nextcloud) differs from the folder (nextcloud-files)
- 50Failures and branches. 0 branches, has a failure section
- 85Steps. 13 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 1587 tokens
- 100Progress reporting. Reports progress
- low 11 top-level sections: this looks like several domains in one skill
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
- +3Output format is not stated: the model decides each time
- -31 of 5 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 470: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 13 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.