AC ragflow-dataset-ingest
Use for RAGFlow dataset and retrieval tasks: create, list, inspect, update, or delete datasets; list, upload, update, or delete documents in a dataset; start or stop parsing uploaded documents; check parser status through `parse_status.py`; and retrieve relevant chunks from RAGFlow datasets with `search.py`.
As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
The same skill appears in 1 more place: ClawHub
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: 16. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 58/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 29 mutating operations with no state check
- 40Consistency. Frontmatter name (ragflow-dataset-ingest) differs from the folder (1234)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 83 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 7 branches, has a failure section
- 100Execution cost. Instruction body is 3315 tokens
- low 10 top-level sections: this looks like several domains in one skill
- 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
- -2localhost URLs: will not work for another user
- -33 of 12 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 309: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 83 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.