Five-primitive battery for deployed agents
Measure why one agent will fail before rollout.
RPCS-1 turns task, entropy, stakes, predictability, context horizon, and commitment style into a five-primitive profile, a failure-risk score, and a next test for one configured agent.
What it measures
One configured agent, five primitives, one failure-risk read.
Who it is for
Teams shipping support, coding, research, and workflow agents.
What it catches
Overload, oscillation, freeze, and underdetermination.
Free results are directional. The paid diagnostic includes a written memo, five-primitive profile, recommended settings, implementation priorities, and a next test to run.
live demo
Try one workflow in under a minute.
Pick a preset, run RPCS-1, and see the status, configuration, language mode, and next check.
Best next check
Running the live demo now...
Five-primitive profile
TI
...
Temporal Integration
SG
...
Signal Gain
FT
...
Filtering Threshold
UE
...
Update Elasticity
AR
...
Ambiguity Resolution
What the memo gives you
Five-primitive profile
TI, SG, FT, UE, and AR measured for one configured agent.
Failure-risk score
A fast read on whether the workflow looks stable, oscillating, overloaded, or frozen.
Recommended posture
The runtime settings you should actually change before rollout.
Next test
A concrete follow-up check that tells you whether the configuration improved.
Sample output
status: stable
receiver profile: TI 78 · SG 61 · FT 43 · UE 66 · AR 22
configuration: explicit_confirmation · frequent_grounding
language mode: face-preserving
best next check: rerun 3 ambiguous cases
Buyers do not need a theory lecture. They need a clear answer, the right settings, and one next test that makes the workflow safer to ship.
free tool
RPCS-1 Translator Hub
Interpret ambiguous messages, normalize fragmented text, split mixed intents, rewrite for any audience, and score candidate interpretations — all powered by the HF-HATP v1.9 protocol.
Interpret
Detect ambiguity, extract intent, assess confidence
Rewrite
6 styles: plain, technical, gentle, concise, detailed, direct
Score
RPCS-1 Signature Ambiguity Framework with AR scale
// Live example — ambiguous input
$ curl -X POST /api/translate {"tool":"interpret","text":"I'm fine","risk":"advice"}
{
ar_level: "AR5",
ambiguities: ["neutral", "frustrated"],
margin: 0.015,
suggested: "clarify"
}
Buy path
Start free. Upgrade when one workflow needs a clear answer.
Most teams do not need a bigger theory. They need to know whether their agent is stable enough to ship, what to change, and which test will confirm the fix. That is what the diagnostic is for.