CD brag-slim
Launch video from a project or URL, upstream-maintained.
This skill launches video from a project or URL—straightforward, potentially useful. Scores suggest it works (quality 59%, process 39%), no critical issues found, safety checks pass. However, it's essentially a reference to upstream code with minimal original functionality.
The catch: no actual model runs or sandbox testing. Single file, no scripts. Works as a pointer, but don't rely on it as a primary tool. Install if you just need a reference implementation; otherwise, check the upstream source directly.
Launch video from a project or URL, upstream-maintained.
As a process D 39/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
The same skill appears in 1 more place: hermes-agent
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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-no-whenneither description nor a "## When to Use" section says when to use the skill
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 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
- 25Steps. 1 steps
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 60Consistency. The Hermes dialect needs category and tags
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Execution cost. Instruction body is 390 tokens
- 100Running it twice. No mutating operations
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 56: 120–800 characters recommended
- +4Structure: 2 headings, hard to scan
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.