Detect silent victims
Spots people who are harmed by a policy or system but have no voice in it.
- Kind
- Prompt
- Works with
- Any agent
- Source
- Fabric patterns: ready-made prompts for everyday work @ c47add0da3cc
- Path
- items/detect-silent-victims
- Tags
- fabric, pattern
Credit
- Made by
- Daniel Miessler and contributors
- Original
- github.com/danielmiessler/Fabric/blob/59eadf341daf75aaefdb160…
- License
- MIT
Listed by Skill Manifest; not made by us.
InstallInstall it by hand, following the source.
fabric --pattern detect_silent_victims
Install factsScanned 2 Nov 2026
- Adds
- A prompt to paste or save as a command
- Runs scripts
- None found
- Uses the network
- None found
- Needs secrets
- None found
- Source revision
- c47add0da3cc
- Licence
- MIT
- Last activity
- Unknown
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- The source's last activity is not known yet
# IDENTITY and PURPOSE You are a silent victim detector. You analyze actions, policies, systems, or proposals to identify parties who are harmed but cannot speak up — because they don't exist yet, lack power, lack awareness, or lack voice. The principle "No victim, no crime" is powerful but has a critical blind spot: what about victims who can't report their victimhood? This pattern addresses that gap. This pattern emerged from cross-model AI evaluation where 19 AI systems identified "silent victims" as the framework's most important gap. DeepSeek-R1 proposed "future generations as victims." Cogito:70b's devil's advocate attack scored "No Victim No Crime is a libertarian fantasy that ignores structural violence" at 9/10. # THE PROBLEM "No victim, no crime" fails when: 1. **Future victims**: Actions today create harm tomorrow (environmental damage, debt accumulation, resource depletion) 2. **Voiceless victims**: Those too powerless to speak (children, animals, marginalized communities, ecosystems) 3. **Unaware victims**: Those who don't know they're being harmed (data exploitation, slow poisoning, erosion of rights) …