BC litmedia-skill
Generate, Edit, Collaborate. Access all mainstream AI models in one toolkit. Simply describe your vision to create videos, images, and avatars—zero manual operations.
As a process C 60/100 · Has gaps — weak spots: result and completion, consistency, running it twice
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 skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 Broad scope
meta-agent-memory-dumpreferences/user.mdAgent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokensreferences/user.md
-
low Secrets in code
secret-password-literalscripts/auth.py:99Hard-coded password / key literal (may be an example)api_key = api_keys[0] if api_keys else ""
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low Secrets in code
secret-password-literalscripts/auth.py:194Hard-coded password / key literal (may be an example)api_key = api_keys[0] if api_keys else "(none)"
Files scanned: 24. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 5983 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 7 mutating operations with no state check
- 40Consistency. Frontmatter name (litmedia-skill) differs from the folder (litmedia)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5983 tokens
- 100Steps. 79 steps
- 100Failures and branches. 8 branches, has a failure section
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 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
- -31 of 7 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 166: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 79 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.