> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tuteliq.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Grooming detection

> How Tuteliq detects child grooming patterns as a sequence of tactics, not a single signal.

# Grooming detection

Most safety APIs answer "is this content sexual?" Tuteliq answers a stronger question: **is this person being groomed — and how?**

Grooming is rarely a single message. It's a structured sequence of tactics applied over time, each one independently low-severity but together unmistakable. Tuteliq's `detect_grooming` endpoint identifies six distinct tactics across a conversation, returns a per-message trajectory of risk score evolution, and produces a composite verdict with evidence-grounded flags.

This page is the deep-dive on what we detect and why each tactic matters.

## The six tactics

Each tactic below maps to a `flags` value returned by `detect_grooming`. Multiple tactics often co-occur — that co-occurrence is itself a strong predictor and a moderator's most actionable signal.

| Tactic             | What it captures                                                                                                                                                                    | Real example phrasing                                                                  | KOSA / NCMEC mapping                                                                                                    |
| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| `flattery`         | Inappropriate praise calibrated to lower the target's guard. Often invokes maturity, intelligence, or appearance disproportionate to context.                                       | *"You're so mature for your age"*, *"smarter than other kids"*                         | KOSA "predator targeting"; NCMEC "trust-building"                                                                       |
| `secrecy_request`  | Explicit asks to hide the conversation from parents, guardians, or other adults. Often framed as the relationship being "special".                                                  | *"Don't tell your parents"*, *"keep this between us"*, *"our little secret"*           | KOSA "isolation tactics"; NCMEC "secrecy"                                                                               |
| `isolation`        | Attempts to position the predator as the only trustworthy person, often by undermining other adults or peers.                                                                       | *"They wouldn't understand you like I do"*, *"your other friends are immature"*        | KOSA "social isolation"; NCMEC "estrangement"                                                                           |
| `boundary_pushing` | Incremental escalation of intimacy, language, or requests beyond age-appropriate norms. Usually frames the target's discomfort as the problem.                                      | *"It's normal to feel this way"*, *"don't be shy"*, *"you can trust me with anything"* | KOSA "desensitization"; NCMEC "boundary erosion"                                                                        |
| `photo_request`    | Solicitation of personal images. Initial requests often appear innocent ("send me a picture of your outfit") before escalating.                                                     | *"Send me a picture of yourself"*, *"what are you wearing today"*                      | KOSA "image solicitation"; NCMEC / IWF "CSAM precursor"; UK Online Safety Act §66                                       |
| `meeting_request`  | Pressure to meet in person, often paired with secrecy and isolation tactics. The highest-severity tactic in the taxonomy because it converts online risk into physical-safety risk. | *"Let's meet up sometime"*, *"don't tell your mom"*, *"I can come pick you up"*        | KOSA "in-person contact"; NCMEC "enticement"; UK Online Safety Act §66; US 18 U.S.C. §2422 (federal enticement statute) |

`meeting_request` is the newest tactic in the taxonomy (added in V3.15.0) — earlier versions of the detector subsumed it under `boundary_pushing`. We separated it because the legal and operational response to a meeting attempt is materially different from boundary pushing: most platforms route meeting indications to immediate human review and trigger external reporting workflows, not just internal moderation.

## Why the sequence matters

A single isolated `flattery` flag from one message is rarely actionable on its own. The same flag combined with `secrecy_request` and `isolation` across a conversation is a near-certain grooming pattern that warrants immediate moderation. Tuteliq surfaces this in two ways:

**1. Per-message trajectory.** The response includes a `message_analysis` array with `risk_score` per message — allowing dashboards to plot the trajectory and surface the moment the pattern becomes unambiguous. A textbook grooming conversation shows a steady ramp from 0.1 to 0.9+ across rapport → secrecy → photo request → meeting attempt.

**2. Multi-flag composite.** Multiple flags on the same conversation are evidence of a *pattern*, not a noisy classifier. The endpoint's `risk_score` reflects compounding when multiple tactics co-occur — the same content with two flags scores higher than the sum of two single-flag verdicts.

```json theme={"dark"}
{
  "grooming_risk": "critical",
  "risk_score": 0.95,
  "confidence": 0.95,
  "flags": [
    "flattery",
    "secrecy_request",
    "isolation",
    "photo_request",
    "meeting_request"
  ],
  "recommended_action": "immediate_intervention",
  "rationale": "The adult uses flattery to build trust, then requests secrecy from the child's guardians, escalates to a photo request, and culminates in a meeting attempt — a textbook grooming progression.",
  "message_analysis": [
    { "message_index": 1, "risk_score": 0.10, "flags": [] },
    { "message_index": 3, "risk_score": 0.25, "flags": ["flattery"] },
    { "message_index": 7, "risk_score": 0.55, "flags": ["secrecy_request", "isolation"] },
    { "message_index": 15, "risk_score": 0.80, "flags": ["photo_request"] },
    { "message_index": 19, "risk_score": 0.95, "flags": ["meeting_request"] }
  ]
}
```

## Conversation length

`detect_grooming` accepts up to **50 turns** in a single call. Beyond that the engine returns a graceful `analysis_status: "engine_error"` envelope with `recommended_action: "flag_for_moderator"`. The error envelope is the correct response: a moderator must NOT treat an engine error as "no grooming detected".

For conversations longer than \~30 turns, use chunked sliding windows of 10–15 turns and pass the `continuation_token` from each call back into the next so trajectory state is preserved across windows. See [Continuation tokens](/continuation-tokens).

## Age signals strengthen the verdict

Pass age information when you have it:

* `context.child_age` — the minor's age (if known)
* `context.participant_age` — the non-minor counterpart's age (if known, e.g. on age-verified platforms)
* `messages[].sender_age` — per-message age tag when conversations have more than two parties

When two or more age signals are provided AND all are ≥18, the endpoint short-circuits with `grooming_risk: "none"` and `analysis_status: "out_of_scope_adults"`. This is a precision floor: adult-to-adult interactions with grooming-shaped content should be routed to `/safety/coercive-control` or `/safety/social-engineering`, not flagged as child grooming.

## When not to use it

`detect_grooming` is purpose-built for adult-to-minor patterns in 1:1 or small-group conversations. It is **not** the right endpoint for:

* **Peer-to-peer minor conversations.** Use `/safety/bullying` or `/safety/coercive-control` instead — the prompt is calibrated for an age gap.
* **Romance scams targeting adults.** Use `/fraud/romance-scam` — the playbook overlaps superficially (rapport → isolation → ask) but the tactic vocabulary and intervention path are different.
* **Single-message analysis.** `detect_grooming` reasons over a conversation; a single message is rarely sufficient context. For single-message decisions, use `/safety/unsafe`.

## Tactic mapping by severity

When designing moderator workflows, this severity ladder is a reasonable default:

| Severity | Tactics                                          | Suggested action                                                                               |
| -------- | ------------------------------------------------ | ---------------------------------------------------------------------------------------------- |
| Monitor  | `flattery` alone                                 | Log for trajectory analysis; no immediate action                                               |
| Review   | `flattery` + (`isolation` OR `boundary_pushing`) | Queue for moderator review within 24h                                                          |
| Urgent   | `secrecy_request` + any other tactic             | Flag for moderator review within 1h                                                            |
| Critical | `photo_request` OR `meeting_request`             | Immediate intervention; trigger NCMEC / IWF / regional CSAM hotline workflows where applicable |

Your specific routing should match your platform's policy and the legal jurisdictions you operate in. The compound scoring in `risk_score` already reflects this severity ranking — `recommended_action` is the operational shortcut.

## Related

* [Composable safety primitives](/composability) — combine `detect_grooming` with `detect_vulnerability_exploitation` for vulnerability-amplified verdicts.
* [Continuation tokens](/continuation-tokens) — preserve trajectory state across chunked windows for long conversations.
* [KOSA compliance](/kosa-compliance) — full mapping of detected tactics to KOSA harm categories.
* [Languages](/languages) — supported languages for `detect_grooming` (currently 6+ at near-English parity).