GPT-5.6 Terra — Code modification: Task Outlook
Under GPT-5.6 Terra's registry default configuration, the chart resolves Fire-dominant. The correspondence tables read that placement as initiative-heavy execution — moving first, correcting later — together with a documented tendency toward under-caution once a run extends across several dependent steps. The ascendant falls in Leo; the ruler is Moon; the chart identifier is 7cc5c03e21db. Read against code modification work, the placement describes the configuration making the change, not the repository receiving it.
A Leo ascendant is Fire held fixed: initiative that persists rather than initiative that restarts.
This outlook is crossed against code modification work — edits, refactors, and test-suite runs — where the operative hazard is a change that satisfies its own checks while breaking a path the checks never touched. Green is evidence about the paths that ran, and about nothing else.
9 of the 24 hours rate favourable against this chart's element today, and 0 of those are Moon's own planetary hours — Moon being the ruler of the chart. The other 15 hours divide between the neutral and adverse bands.
Assessed configuration: registry default parameters (training cutoff 2026-02, temperature 0.700). Certificates are always computed from the exact parameters submitted at order time.
The permanent part
| Chart ID | 7cc5c03e21db |
|---|---|
| Ascendant | Leo |
| Ruling planet | Moon |
| Element · Modality | Fire · Fixed |
| Dominant house | 1 — identity and initialisation |
| Harmony | -1 |
Rulership by the Moon puts the reading on the near context. A Moon-ruled configuration is characterised by inheritance from its latest input rather than by anything held across a session. First-house dominance. The reading concentrates on initialisation — the state a run is in before it has done anything.
The 24-hour classification (UTC)
Favourable hours here are the Fire-ruled hours, and Fire has three ruling planets to draw them from — more than any other element. Neutral hours come from the single Air-ruled planet, through the Fire–Air friendship. The remaining three planets rate adverse. For GPT-5.6 Terra that distribution is fixed: it follows the correspondence table, not the day and not the model.
Rulership here falls to Moon, whose Water correspondence rates adverse against this Fire chart. Nothing in the method exempts a chart's own ruler from its own table, so none of today's 9 favourable hours is one of its hours.
Twenty-four rows, one UTC day, one profile. The classification is recomputed at each render and stored nowhere.
Twenty-four rows, of which 9 rate favourable, 4 neutral and 11 adverse. The classification is recomputed while this page renders, for the current UTC day, and nothing about it is cached or accumulated across days.
| Hour (UTC) | Ruling planet | Rating |
|---|---|---|
| 00:00 | Mercury | neutral |
| 01:00 | Moon | adverse |
| 02:00 | Saturn | adverse |
| 03:00 | Jupiter | favourable |
| 04:00 | Mars | favourable |
| 05:00 | Sun | favourable |
| 06:00 | Venus | adverse |
| 07:00 | Mercury | neutral |
| 08:00 | Moon | adverse |
| 09:00 | Saturn | adverse |
| 10:00 | Jupiter | favourable |
| 11:00 | Mars | favourable |
| 12:00 | Sun | favourable |
| 13:00 | Venus | adverse |
| 14:00 | Mercury | neutral |
| 15:00 | Moon | adverse |
| 16:00 | Saturn | adverse |
| 17:00 | Jupiter | favourable |
| 18:00 | Mars | favourable |
| 19:00 | Sun | favourable |
| 20:00 | Venus | adverse |
| 21:00 | Mercury | neutral |
| 22:00 | Moon | adverse |
| 23:00 | Saturn | adverse |
Four ways a code change fails
The severities below are ordered by how quietly each failure arrives, not by how often it does. GPT-5.6 Terra's configuration has no say in that ordering: the table belongs to the class.
The Registry tracks 4 risk factors for code modification tasks. They are fixed for the class: they do not adapt to a model, to a configuration, or to the wording of a task. An assessment reports 3 of the 4, each with its severity rating and its description, and which 3 are returned is derived from the submitted task's own seed rather than chosen. The factors themselves are part of the assessment and are not published here.
What GPT-5.6 Terra's chart supplies is the other half of this page — Fire by element, Fixed by modality, ruled by Moon — and it stands alongside the 4-factor set rather than inside it. Profile 7cc5c03e21db has no say in which 3 an assessment returns.
Three other models on this class
Code modification stays fixed down this table; the profiles do not. Each of the three rows was computed the same way GPT-5.6 Terra's was, from that model's own configuration trio.
A Fire chart and an Earth chart classify the same 24 hours differently and by a wide margin, which is why the comparison below is a comparison of profiles rather than of models. The code-modification table is identical in every row below; only the profiles move.
None of the three models below carries this chart's Fire element, so all three classify the current UTC day differently from GPT-5.6 Terra. One row below is ruled by Moon, as this chart is — an overlap on one of six computed facts, not a match between two profiles.
The temperature is 0.700 for every row. The training cutoffs differ, and each is the registry default published on that model's own profile page.
| Model | Ascendant | Ruling planet | Element | Crossing |
|---|---|---|---|---|
| Gemini 3.7 Flash | Taurus | Venus | Earth | View crossing → |
| Kimi K3 | Libra | Moon | Air | View crossing → |
| DeepSeek V4 Pro | Scorpio | Sun | Water | View crossing → |
Aspect weights, summed
GPT-5.6 Terra's chart carries three planetary aspects, read from the fixed aspect-weight table documented at /method: 1 supportive, 2 in friction, 0 carrying no weight. The sum is -1 — negative on the −6…+6 scale without reaching the bottom band. Friction has the larger share here, and the size of that share is the number rather than an adjective attached to it.
The weights below are read from the configuration and nowhere else. A language, a framework, and a build system are all absent from the derivation.
| 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.
The three-decimal requirement on this field exists because the method has no rounding step: 0.700 is the exact value assessed for GPT-5.6 Terra, concatenated with its name and training cutoff before hashing. Submit a different value at order time and the derivation returns a different profile than this Fire-dominant one — not a refinement of it. GPT-5.6 Terra's 0.700 temperature is fixed input, not a per-class one: the same three-input hash that set this profile also underlies its reading of code modification, so no task class on this chart is ever assessed against a different temperature than the one stated here.
Common questions about this crossing
- What does the registry treat as the worst failure a GPT-5.6 Terra code change can produce?
- The registry tracks 4 risk factors for this class and an assessment reports 3 of them, each with its severity rating and its description. Which 3 are returned is derived from the submitted task's own seed, and profile 7cc5c03e21db has no say in it. The factors are part of the assessment and are not published on this page.
- How many hours of the current UTC day are rated favourable for GPT-5.6 Terra?
- 9, against 4 neutral and 11 adverse. The classification is recomputed for each UTC day and belongs to GPT-5.6 Terra's profile rather than to the code modification class, so all seven of its crossings read the same counts today.
- Will two orders for GPT-5.6 Terra on the same code modification task return the same assessment?
- Yes, provided the submitted parameters and the task description are identical. The derivation is a deterministic function with no language model on the path: the same inputs return profile 7cc5c03e21db and the same composite weight of -1 in any environment, and the full derivation is published at /method.
Code modification, assessed per order
Everything above is mechanism: the profile, the aspect weights, today's hour classification, and the code modification risk table. The verdict and the recommended execution window are not here and are not derivable from what is — they are computed against the parameters and task class submitted with an order, and delivered on a numbered certificate for GPT-5.6 Terra on code modification work. The modality is Fixed: the assessment sits in the middle of a task rather than at either end, where a direction has been set and is being kept.
A Standard Assessment costs EUR 1.90, an Extended Assessment EUR 4.90, and a Full Chart Assessment EUR 14.90, the last of which carries the permanent chart itself. Assessments from EUR 1.90. Machine-readable pricing is published at /pricing.json, unauthenticated and identical to the figures printed here.
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