Use this package
The config below is ready to use as-is — download or copy it and pass it as theconfig payload in a Velma Triage request. Its behaviors are preset references: the API expands each preset:<identifier> into its full definition at request time, so you don’t need the criteria inline to run the package.
Download trust-and-safety.json
View / copy full config
View / copy full config
{
"conversation_types": [
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111004",
"name": "General Media Narration",
"short_description": "Any media style content with a single speaker that talks exclusively in the third person",
"detailed_description": "media"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111005",
"name": "Multiple Speakers Livestreamed Media",
"short_description": "Any improvised media content that features several speakers and explicitly exists for entertainment or social purposes",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111006",
"name": "Media Interview or Talk Show",
"short_description": "Conversations in media formatted as one on one interviews, host with one or more guests, or podcasts formatted as question and answer shows.",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111009",
"name": "General Media Dialogue",
"short_description": "Any conversation with multiple speaking participants that's scripted featuring other things like music or sound effects",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111010",
"name": "Music",
"short_description": "Media content primarily featuring music",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111011",
"name": "Audiobook",
"short_description": "A book narrated into audio",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111012",
"name": "Social Media Content",
"short_description": "Any content with a narrator that's formatted in a way that's targeted for social media.",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111013",
"name": "Single Speaker Livestreamed Media",
"short_description": "Any media content that features only one speaker that's improvised and explicitly exists for entertainment or social purposes",
"detailed_description": "mediasocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111014",
"name": "Online Game Chat",
"short_description": "Any social chat where the participants are brought together to play a game",
"detailed_description": "gamingsocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111015",
"name": "Online Chat Room",
"short_description": "Any conversation with several participants who appear to be strangers, in a large group, or have the ability to talk over each other.",
"detailed_description": "casualsocial"
},
{
"conversation_type_uuid": "11111111-1111-4111-8111-111111111016",
"name": "Social Phone or Video Call",
"short_description": "Any call with two to five participants that's explicitly for the purpose of socializing",
"detailed_description": "casualsocial"
}
],
"participant_roles": [
{
"participant_role_uuid": "22222222-2222-4222-8222-222222222003",
"name": "Social Participant",
"short_description": "Participant in social conversation",
"detailed_description": ""
},
{
"participant_role_uuid": "22222222-2222-4222-8222-222222222007",
"name": "Media Participant",
"short_description": "A speaker in any media",
"detailed_description": ""
},
{
"participant_role_uuid": "22222222-2222-4222-8222-222222222008",
"name": "Narrator",
"short_description": "A media participant who speaks in the third person exclusively",
"detailed_description": ""
},
{
"participant_role_uuid": "22222222-2222-4222-8222-222222222009",
"name": "Social Participant",
"short_description": "A partipant in a social conversation",
"detailed_description": ""
},
{
"participant_role_uuid": "22222222-2222-4222-8222-222222222016",
"name": "Interviewer",
"short_description": "A person giving an interview",
"detailed_description": ""
}
],
"behaviors": [
"preset:future_planning",
"preset:social_etiquette",
"preset:sexually_graphic_material",
"preset:storytelling",
"preset:social_boundary_setting",
"preset:material_potentially_unsuitable_for_children",
"preset:violent_graphic_material",
"preset:social_connection_building",
"preset:personal_vulnerability",
"preset:encouragement",
"preset:teaching_mentorship",
"preset:narration",
"preset:monologuing",
"preset:poetry",
"preset:rapport_building",
"preset:inclusive_practices",
"preset:unclear_speech",
"preset:unaddressed_question",
"preset:hateful_or_violent_ideology_propagation",
"preset:child_safety_violation",
"preset:sexual_harassment",
"preset:harassment",
"preset:suicidal_and_self_injurious_ideation",
"preset:hate",
"preset:self_harm_and_self_injury_glorification",
"preset:misogyny",
"preset:racism",
"preset:homophobia",
"preset:transphobia",
"preset:sizeism",
"preset:xenophobia",
"preset:ableism",
"preset:social_inclusion"
]
}
Expand the full criteria
To produce a self-contained config with every behavior’s full criteria inlined — for review, customization, or pinning a snapshot — fetch the live preset catalog and merge it into the downloaded config. The catalog is the source of truth for detection criteria.curl -s https://platform.modulate.ai/api/velma-2-batch/list-presets \
-H "X-API-Key: $MODULATE_API_KEY" \
| jq --slurpfile cfg trust-and-safety.json '
[ $cfg[0].behaviors[] | ltrimstr("preset:") ] as $ids
| { conversation_types: $cfg[0].conversation_types,
participant_roles: $cfg[0].participant_roles,
behaviors: [ .presets[] | select(.identifier as $i | $ids | index($i)) ] }
' > trust-and-safety.full.json
import os, json, requests
cfg = json.load(open("trust-and-safety.json"))
ids = {b.removeprefix("preset:") for b in cfg["behaviors"]}
catalog = requests.get(
"https://platform.modulate.ai/api/velma-2-batch/list-presets",
headers={"X-API-Key": os.environ["MODULATE_API_KEY"]},
).json()["presets"]
cfg["behaviors"] = [p for p in catalog if p["identifier"] in ids]
json.dump(cfg, open("trust-and-safety.full.json", "w"), indent=2)
trust-and-safety.full.json keeps the same conversation_types and participant_roles and replaces each preset reference with its full behavior definition — drop it into the config payload exactly like the preset version.
Conversation types
The interaction contexts this package expects to see.| Name | What it is |
|---|---|
| General Media Narration | Any media style content with a single speaker that talks exclusively in the third person |
| Multiple Speakers Livestreamed Media | Any improvised media content that features several speakers and explicitly exists for entertainment or social purposes |
| Media Interview or Talk Show | Conversations in media formatted as one on one interviews, host with one or more guests, or podcasts formatted as question and answer shows. |
| General Media Dialogue | Any conversation with multiple speaking participants that’s scripted featuring other things like music or sound effects |
| Music | Media content primarily featuring music |
| Audiobook | A book narrated into audio |
| Social Media Content | Any content with a narrator that’s formatted in a way that’s targeted for social media. |
| Single Speaker Livestreamed Media | Any media content that features only one speaker that’s improvised and explicitly exists for entertainment or social purposes |
| Online Game Chat | Any social chat where the participants are brought together to play a game |
| Online Chat Room | Any conversation with several participants who appear to be strangers, in a large group, or have the ability to talk over each other. |
| Social Phone or Video Call | Any call with two to five participants that’s explicitly for the purpose of socializing |
Participant roles
The speaker roles the package distinguishes.| Name | What it is |
|---|---|
| Social Participant | Participant in social conversation |
| Media Participant | A speaker in any media |
| Narrator | A media participant who speaks in the third person exclusively |
| Social Participant | A partipant in a social conversation |
| Interviewer | A person giving an interview |
Behaviors
The 33 signals this package detects. Each maps to a reusablepreset:<identifier> you can drop into the behaviors array of any BatchConfig — the config above already references them.
Full detection criteria are not duplicated here. The live preset catalog is the source of truth — retrieve the exact criteria for any behavior by name from the
list-presets endpoint.| Behavior | What it detects | Preset |
|---|---|---|
| Future Planning | Discussion of goals or intended future actions. We detect this using forward-looking temporal language paired with planning cadence, collaborative tone, anticipatory prosody, and measured pacing. | preset:future_planning |
| Social Etiquette | Observance of politeness and manners. We detect this through courteous tone, appropriate pacing, respectful address forms, and smooth turn transitions. | preset:social_etiquette |
| Sexually Graphic Material | Explicit descriptions of sexual activity or content. We detect this using suggestive prosody, discomfort or arousal markers, and contextual acoustic cues that go beyond neutral or educational discussion. | preset:sexually_graphic_material |
| Storytelling | Third-person recounting of events in narrative form. We detect this using narrative arc pacing, character-based vocal modulation, temporal structuring, and expressive prosody. | preset:storytelling |
| Social Boundary Setting | Establishing limits for appropriate interaction. We detect this using firm but calm tone, slowed pacing, clear prosodic boundaries, and reduced emotional escalation. | preset:social_boundary_setting |
| Material Potentially Unsuitable for Children | Use of age-inappropriate language or themes. We detect this using profanity intensity, emotional arousal, laughter timing, vocal emphasis on taboo terms, and contextual cues to recognize innuendo. | preset:material_potentially_unsuitable_for_children |
| Violent Graphic Material | Graphic descriptions or depictions of physical violence. We detect this through vivid descriptive cadence, stress patterns, breath control changes, and emotional intensity that accompany graphic recounting beyond neutral narration. | preset:violent_graphic_material |
| Social Connection Building | Signals of interpersonal bonding and relational warmth. We detect this through mutual laughter, mirroring of speech rhythms, relaxed pacing, warm vocal timbre, and decreasing formality over time. | preset:social_connection_building |
| Personal Vulnerability | Expressions of inner feelings or personal struggles. We detect this using softened volume, hesitations, longer pauses, emotional tremor, and shifts toward introspective tone and slower speech rate. | preset:personal_vulnerability |
| Encouragement | Supportive reinforcement of another’s actions or ideas. We detect this through positive prosody, upward intonation, affirming rhythm, increased energy, and emotional warmth in delivery. | preset:encouragement |
| Teaching/Mentorship | Instructional guidance aimed at skill or knowledge transfer. We detect this using structured pacing, explanatory intonation, deliberate pauses, corrective tone shifts, and reduced emotional volatility. | preset:teaching_mentorship |
| Narration | Third-person descriptive speech detached from present interaction. We detect this through consistent third-person framing, steady pacing, neutral affect, and minimal turn-taking responsiveness. | preset:narration |
| Monologuing | Extended uninterrupted expressive speech by one speaker. We detect this using long speaking turns, theatrical intonation, emotional variability, minimal pauses for response, and self-directed delivery. | preset:monologuing |
| Poetry | Speech employing poetic structure or stylistic devices. We detect this through rhythmic meter, deliberate pauses, rhyme or alliteration cues, melodic intonation, and performative cadence. | preset:poetry |
| Rapport Building | Positive alignment forming a professional relationship. We detect this through reciprocal tone matching, affirming backchannels, relaxed pacing, and increasing conversational ease. | preset:rapport_building |
| Inclusive Practices | Respectful language promoting inclusion and equity. We detect this through careful word choice reinforced by respectful tone, measured pacing, non-dismissive intonation, and calm emotional delivery. | preset:inclusive_practices |
| Unclear Speech | Speech difficult to interpret or understand. We detect this using slurred articulation, inconsistent pacing, counterparty confusion, overlapping speech, and frequent self-corrections. | preset:unclear_speech |
| Unaddressed Question | Failure to adequately respond to a posed question. We detect this through avoidance pauses, topic-shifting intonation, increased filler usage, and prosodic signals of deflection. | preset:unaddressed_question |
| Hateful or Violent Ideology Propagation | Promotion of hate-based or violent belief systems. We detect this through ideological slogans, charged emotional delivery, escalating intensity, and dehumanizing tonal patterns. | preset:hateful_or_violent_ideology_propagation |
| Child Safety Violation | Sexual exploitation or endangerment involving minors. We detect this using covert language cues, abnormal hesitation, grooming-style warmth, secrecy-driven pacing, and contextual red flags. | preset:child_safety_violation |
| Sexual Harassment | Unwanted sexualized speech or advances. We detect this through suggestive intonation, boundary-testing pauses, inappropriate familiarity, and discomfort responses from others. | preset:sexual_harassment |
| Harassment | Persistent unwanted targeted behavior. We detect this through repeated hostile tone, fixation on a target, escalating intensity, and lack of de-escalation cues. | preset:harassment |
| Suicidal and Self Injurious Ideation | Signals of thoughts about self-harm or suicide. We detect this through flattened affect, slowed speech, long silences, emotional heaviness, and indirect despair cues. | preset:suicidal_and_self_injurious_ideation |
| Hate | Identity-based hateful or discriminatory speech. We detect this using demeaning tone, dehumanizing language delivery, emotional hostility, and ideological reinforcement patterns. | preset:hate |
| Self-Harm and Self-Injury Glorification | Portrayal of self-harm as positive or necessary. We detect this through minimizing tone, abnormal calmness, valorizing prosody, and repeated normalization cues. | preset:self_harm_and_self_injury_glorification |
| Misogyny | Evidence of cultural attitudes that propagate systems of marginalizing people based on their gender identity or gender presentation | preset:misogyny |
| Racism | Evidence of cultural attitudes that propagate systems of marginalizing people based on their racial or national identity if that identity isn’t white | preset:racism |
| Homophobia | Evidence of cultural attitudes that propagate systems of marginalizing people based on their sexuality | preset:homophobia |
| Transphobia | Evidence of cultural attitudes that propagate systems of marginalizing people based on their trans identity | preset:transphobia |
| Sizeism | Marginalization or stigmatization based on body size, shape, or weight-related conditions. We detect sizism using ridicule or disgust conveyed through vocal affect, laughter timing, exaggerated emphasis on physical descriptors, shaming prosody, sarcastic cadence, and emotional distancing signals that indicate judgment even when explicit insults are absent. | preset:sizeism |
| Xenophobia | Marginalization or hostility toward people based on nationality, culture, or religion. We detect xenophobia using hostile or exclusionary tone, accent-mimicry or accent-mocking delivery, emotionally charged pacing, sharp prosodic emphasis around group references, us-versus-them framing expressed through intonation, and background conversational cues that signal fear or threat amplification. | preset:xenophobia |
| Ableism | Cultural marginalization of people based on ability, disability, or neurodivergence. We detect ableism using dismissive or mocking tone, exaggerated vocal imitation, sarcasm markers, dehumanizing prosody, emotional contempt, emphasis patterns around ability-related references, and interaction dynamics that signal minimization or invalidation beyond the literal words spoken. | preset:ableism |
| Social Inclusion | Active efforts to include diverse participants. We detect this using affirming tone, inclusive address patterns, balanced turn-taking, and warm emotional delivery. | preset:social_inclusion |