project-development
This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. Route individual tool design to tool-design and individual skill-loading or context-budget tactics to context-optimization.
72
88%
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The skill’s provided runtime workflow is the staged LLM pipeline template (scripts/pipeline_template.py) where the Process stage reads arbitrary per-item `prompt.md` (derived from acquire) and sends its free-text contents into the LLM, enabling outsider-authored prompt injection if acquire pulls from an outsider-controlled feed/queue without preselecting a specific trusted item.
- Commit
a1841d1
- Audited
- Security analysis
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