DF dingo
(no description)
As a process F 55/100 · Will not run — References files that are not bundled: input_args, InputArgs(**config
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- Add a description to the frontmatter: without it the skill never triggers.
- The text references files that are not there: add them or drop the references.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
medium Exfiltration
net-redirectable-api-keyscripts/fact_check.py:359Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
-
low Exfiltration
net-credential-useSKILL.md:114Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded){"name": "Faithfulness", "config": {"model": "deepseek-chat", "key": "${OPENAI_API_KEY}", "api_url": "https://api.deepseek.com/v1"}},quoted -
low Exfiltration
net-credential-useSKILL.md:115Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded){"name": "ContextPrecision", "config": {"model": "deepseek-chat", "key": "${OPENAI_API_KEY}", "api_url": "https://api.deepseek.com/v1"}}quoted
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
frontmatterSKILL.md: no YAML frontmatter block found - error
name-missingSKILL.md: frontmatter has no `name` - error
description-missingSKILL.md: no `description` — the skill can never trigger - warning
missing-refreference to a missing file: input_args - warning
missing-refreference to a missing file: InputArgs(**config
Process rating: all ten parameters 55/100
- 0Tools and files. 2 referenced file(s) missing: input_args, InputArgs(**config
- 0When it triggers. No condition that starts the skill
- 0Progress reporting. Says nothing while it works
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4347 tokens
- 85Steps. 47 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 16 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 0: 120–800 characters recommended
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +4Structure: 40 headings
- +3Step-by-step instructions: 47 items
- +3Output format is stated explicitly
- +4Has examples (17 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.