GPT-5.6 Terra — Task Risk Assessment Profile
GPT-5.6 Terra, from OpenAI, assessed under the registry's default configuration — training cutoff 2026-02, temperature 0.700 — resolves to chart 7cc5c03e21db: ascendant in Leo, ruled by Moon, Fire by element and Fixed by modality.
The correspondence tables put GPT-5.6 Terra in the Fire triplicity. What that describes is execution beginning before the whole path is visible — an advantage wherever a first move is worth more than a complete plan, and a documented liability wherever the path has several dependent steps in it. Neither half of that is a score.
The ruler of GPT-5.6 Terra's chart is the Moon — responsiveness-led operation. Recent input matters here. Immediate context matters here. What was in the window five minutes ago matters here, and a Moon-ruled configuration is characterised by how much of its behaviour is inherited from what it has just been shown. Inheritance, not memory.
Assessed configuration: registry default parameters (training cutoff 2026-02, temperature 0.700). Certificates are always computed from the exact parameters submitted at order time.
What is permanent here
Fire-dominant — the widest favourable set, the shortest deliberation.
| Chart ID | 7cc5c03e21db |
|---|---|
| Ascendant | Leo |
| Ruling planet | Moon |
| Element · Modality | Fire · Fixed |
| Dominant house | 1 — identity and initialisation |
| Harmony | -1 |
Fixed: a sustaining configuration. The method reads it where a run is already underway, and it treats holding a direction as the behaviour worth characterising. The dominant house is the first, identity and initialisation, which the method associates with how a run begins rather than how it ends.
Hour-by-hour, today (UTC)
Favourable hours for GPT-5.6 Terra are the Fire-ruled hours, and Fire has more ruling planets than any other element to draw them from. Neutral comes from Air through the traditional friendship. Everything else is adverse. The proportions belong to the correspondence table and do not move from day to day.
Today's count: 11 favourable, 3 neutral, 10 adverse, across 24 UTC hours. Of the 24, 3 belong to this chart's own ruler, Moon, and against this chart those hours rate adverse — the correspondence table is applied to the ruler exactly as it is applied to every other planet. The table is computed fresh at each page render for the current UTC day. It is not cached, not stored, and not a historical record.
| Hour (UTC) | Ruling planet | Rating |
|---|---|---|
| 00:00 | Mars | favourable |
| 01:00 | Sun | favourable |
| 02:00 | Venus | adverse |
| 03:00 | Mercury | neutral |
| 04:00 | Moon | adverse |
| 05:00 | Saturn | adverse |
| 06:00 | Jupiter | favourable |
| 07:00 | Mars | favourable |
| 08:00 | Sun | favourable |
| 09:00 | Venus | adverse |
| 10:00 | Mercury | neutral |
| 11:00 | Moon | adverse |
| 12:00 | Saturn | adverse |
| 13:00 | Jupiter | favourable |
| 14:00 | Mars | favourable |
| 15:00 | Sun | favourable |
| 16:00 | Venus | adverse |
| 17:00 | Mercury | neutral |
| 18:00 | Moon | adverse |
| 19:00 | Saturn | adverse |
| 20:00 | Jupiter | favourable |
| 21:00 | Mars | favourable |
| 22:00 | Sun | favourable |
| 23:00 | Venus | adverse |
The same chart, seven task classes
The seven classes below are not listed in registry order. Each row carries a weight computed from the class's own summed severity plus this chart's reading of it, and the table is sorted by that weight: Unclassified operation leads at 12, because this chart's dominant house (1 — identity and initialisation) reads that class directly. Communication sits at the foot of the table at 7.
One profile, seven rows. The chart is derived from a name, a training cutoff, and a temperature string, none of which is a task class, so nothing in the table below alters GPT-5.6 Terra's profile. Each row differs from its neighbours in three respects only: the four risk factors the class tracks, which of them is rated most severe, and the weight this chart gives the class.
| Task class | Top severity | Weight | Profile |
|---|---|---|---|
| Unclassified operation | 3 of 3 | 12 | View crossing → |
| Code modification | 3 of 3 | 11 | View crossing → |
| Information retrieval | 3 of 3 | 8 | View crossing → |
| Transaction | 3 of 3 | 8 | View crossing → |
| Data processing | 3 of 3 | 8 | View crossing → |
| Media generation | 3 of 3 | 8 | View crossing → |
| Communication | 3 of 3 | 7 | View crossing → |
What the three aspects weigh
GPT-5.6 Terra's chart carries three planetary aspects, each read from the fixed aspect-weight table documented at /method: a trine weighs +2, a sextile +1, a conjunction 0, a square −1, an opposition −2. The composite aspect weight is -1, below the midpoint of the −6…+6 scale and above its floor. The aspect set does not cancel out: friction carries the larger share, and the figure is how far.
| Planets | Aspect | Weight |
|---|---|---|
| Venus – Saturn | square | -1 |
| Moon – Venus | square | -1 |
| Mars – Mercury | sextile | +1 |
What Is Temperature in an LLM?
Temperature is the decimal parameter that controls how much randomness a large language model applies when it selects its next output token. At a low temperature, close to zero, the model consistently favors its single highest-probability token, so identical input tends to produce a closely repeated output. As temperature rises toward its upper bound, lower-probability tokens are sampled more often, and outputs vary more between otherwise identical runs. The Agentic Foresight Registry records temperature — entered here as a value between 0.000 and 2.000, to three decimal places — as one of three fixed inputs, alongside model name and training cutoff, to the deterministic derivation behind every task risk profile.
GPT-5.6 Terra's assessed configuration fixes temperature at 0.700. That figure is hashed together with its name and training cutoff into the single string this profile is derived from, so a different temperature submitted at order time returns a different, equally deterministic profile — this Fire-dominant one included, not a variation on it.
Frequently asked about this profile
- Who assesses GPT-5.6 Terra, and does a language model produce the result?
- OpenAI's GPT-5.6 Terra is assessed by The Agentic Foresight Registry under the AFR-1 method: a deterministic function over fixed published tables, with no language model anywhere on the delivery path. The derivation is published in full at /method, and the same three inputs return profile 7cc5c03e21db in any environment, so the result can be checked rather than trusted.
- What is the composite weight of GPT-5.6 Terra's profile?
- -1, on a scale from −6 to +6, summed from three weighted components: 1 supportive, 2 in friction, 0 carrying no weight at all. It is a fixed property of the profile, not a score, a grade, or a verdict. Read against this configuration, work that rewards immediate action reads as the natural fit here, while work demanding sustained multi-step restraint is where the tracked risk factors matter most.
- Does GPT-5.6 Terra's profile change when the task class changes?
- No. The profile is computed from the configuration alone, so all seven task classes on this page cross against one identical profile: composite weight -1, with 11 favourable and 10 adverse hours in today's classification. What varies by class is the risk factor table, and on a certificate, which three of a class's four tracked factors are reported.
Get an assessment for GPT-5.6 Terra
What this page publishes is the whole of the mechanism and none of the result. The verdict and the recommended execution window exist only against a submitted order, where GPT-5.6 Terra's parameters and a task class arrive together, and they are delivered on a numbered certificate rather than shown here.
A Standard Assessment for GPT-5.6 Terra costs EUR 1.90. An Extended Assessment costs EUR 4.90. A Full Chart Assessment, which carries the permanent chart itself, costs EUR 14.90. Assessments from EUR 1.90. Machine-readable pricing is published at /pricing.json.