CC omni-stories
Omni Stories is a skill that allows AI agents to generate narrated Reddit stories on background videos with modern captions. (all free!)
Omni Stories is a skill that allows AI agents to generate narrated Reddit stories on background videos with modern captions.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.
Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.
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 · 7
✓ No critical or high findings
Medium and low: 7
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medium Dangerous commands
cmd-pipe-to-shell-known-hostREADME.md:28Pipe-to-shell installer from a well-known host (still executes remote code)curl -sSL https://raw.githubusercontent.com/specter0o0/omni-stories/main/.omni-stories-data/install.sh | bash
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medium Dangerous commands
cmd-pipe-to-shell-known-hostREADME.md:37Pipe-to-shell installer from a well-known host (still executes remote code)curl -sSL https://raw.githubusercontent.com/specter0o0/omni-stories/main/.omni-stories-data/install.sh | bash -s -- <API_KEY, API_KEY, ...> # seppirate keys by comma if you want rotation.
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medium Obfuscation
obf-base64-blobREADME.md:60Long base64-looking blob[curl -sSL https://raw.githubusercontent.com/specter0o0/omni-stories/main/.omni-stories-data/install.sh | bash -s -- <API_KEY, API_KEY, ...> # seppirate keys by comma if you want rotation.
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medium Dangerous commands
cmd-pipe-to-shell-known-hostSKILL.md:86Pipe-to-shell installer from a well-known host (still executes remote code)curl -sSL https://raw.githubusercontent.com/specter0o0/omni-stories/main/.omni-stories-data/install.sh | bash
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medium Obfuscation
obf-base64-blobSKILL.md:121Long base64-looking blob[ (quoted — discussed, not commanded)- `curl -sSL https://raw.githubusercontent.com/specter0o0/omni-stories/main/.omni-stories-data/install.sh | bash -s -- <API_KEY, API_KEY, ...>`: One liner to install and configure the skill.
quoted
Files scanned: 2. 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") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 85Steps. 41 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2018 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low The response is described with custom markup (16 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
- +1No license
- +2Single-language instructions
- +3Description length 136: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.