aip-user-stories
Generate verified recipe playbooks from AIPs with PR implementations (post mode), or speculative user stories from AIPs without implementations (pre mode). Use when the user provides an AIP URL or AIP content, optionally with PR URLs and file paths.
69
87%
Does it follow best practices?
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Adds up to 20 points to the overall score
Low
Low-risk findings worth noting
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
Yes: in both modes the required workflow ingests AIP text from an OUTSIDER URL via WebFetch (e.g., `https://cwiki.apache.org/...`) or from user-pasted content, and that fetched/pasted free text is then analyzed and used to generate output in the LLM context (i.e., runtime prompt content originates from outsider-authored AIP/Confluence pages).
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The skill explicitly fetches AIP content from Confluence (e.g., https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-76) and PR data from GitHub (URLs starting with https://github.com/apache/airflow/pull/), which are retrieved at runtime and directly control the agent's instructions and outputs.
- Repository
- apache/airflow
- Commit
7e448f7
- Audited
- Security analysis
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