refactor(skill): replace claude-specific dirs with agentskills.io standard

Replace AGENTS.md / claude-skill/ with a proper agentskills.io-compliant
skill directory. Any AI agent that supports the open Agent Skills standard
(Claude Code, OpenCode, Cursor, Codex, etc.) can now install and use this
skill generically.

Changes:
- Remove AGENTS.md (was Claude-specific convention)
- Remove claude-skill/ directory (was Claude-specific naming)
- Add timesfm-forecasting/SKILL.md with compliant frontmatter:
    name: timesfm-forecasting
    description: ...
    license: Apache-2.0
    metadata: author, version
- Rename claude-skill/examples/ → timesfm-forecasting/examples/
- Rename claude-skill/scripts/  → timesfm-forecasting/scripts/
- Rename claude-skill/references/ → timesfm-forecasting/references/
- Update .gitattributes paths to match new directory

Skill installs via:
  cp -r timesfm-forecasting/ ~/.claude/skills/
  cp -r timesfm-forecasting/ ~/.cursor/skills/
  # or any agent that supports agentskills.io

Spec: https://agentskills.io/specification

timesfm-forecasting/examples/global-temperature/output/forecast_output.csv

@@ -0,0 +1,13 @@
+date,point_forecast,q10,q20,q30,q40,q50,q60,q70,q80,q90,q99
+2025-01-01,1.2593384,1.248188,1.140702,1.1880752,1.2137158,1.2394564,1.2593384,1.2767732,1.297132,1.32396,1.367888
+2025-02-01,1.2856668,1.2773758,1.1406044,1.1960833,1.2322671,1.2593892,1.2856668,1.3110137,1.3400218,1.3751202,1.4253658
+2025-03-01,1.2950127,1.2869918,1.126852,1.1876173,1.234988,1.2675052,1.2950127,1.328448,1.354729,1.4035482,1.4642649
+2025-04-01,1.2207624,1.2084007,1.0352504,1.1041918,1.151865,1.1853008,1.2207624,1.256663,1.2898555,1.3310349,1.4016538
+2025-05-01,1.1702554,1.153313,0.9691495,1.0431063,1.0932612,1.1276176,1.1702554,1.201966,1.2390311,1.2891905,1.3632389
+2025-06-01,1.1455553,1.1275499,0.94203794,1.0110554,1.0658777,1.1061188,1.1455553,1.1806211,1.2180579,1.2702757,1.345366
+2025-07-01,1.1702348,1.1510556,0.9503718,1.0347577,1.0847733,1.1287677,1.1702348,1.2114835,1.2482276,1.2997853,1.3807325
+2025-08-01,1.2026825,1.1859496,0.9709255,1.0594383,1.1106675,1.1579902,1.2026825,1.2399211,1.2842004,1.3408126,1.419526
+2025-09-01,1.1909748,1.1784849,0.95943713,1.0403702,1.103606,1.1511956,1.1909748,1.2390201,1.2832941,1.3354731,1.416972
+2025-10-01,1.1490841,1.1264795,0.9079477,0.99529266,1.0548235,1.1052223,1.1490841,1.1897774,1.240414,1.2868769,1.3775467
+2025-11-01,1.0804785,1.0624356,0.8361266,0.9259792,0.9882403,1.0386353,1.0804785,1.1281581,1.1759715,1.228377,1.3122478
+2025-12-01,1.0613453,1.0366092,0.80220693,0.89521873,0.9593707,1.0152239,1.0613453,1.1032857,1.15315,1.216908,1.2959521

timesfm-forecasting/examples/global-temperature/output/forecast_output.json

@@ -0,0 +1,188 @@
+{
+  "model": "TimesFM 1.0 (200M) PyTorch",
+  "input": {
+    "source": "NOAA GISTEMP Global Temperature Anomaly",
+    "n_observations": 36,
+    "date_range": "2022-01 to 2024-12",
+    "mean_anomaly_c": 1.09
+  },
+  "forecast": {
+    "horizon": 12,
+    "dates": [
+      "2025-01",
+      "2025-02",
+      "2025-03",
+      "2025-04",
+      "2025-05",
+      "2025-06",
+      "2025-07",
+      "2025-08",
+      "2025-09",
+      "2025-10",
+      "2025-11",
+      "2025-12"
+    ],
+    "point": [
+      1.25933837890625,
+      1.285666823387146,
+      1.2950127124786377,
+      1.2207623720169067,
+      1.170255422592163,
+      1.1455552577972412,
+      1.1702347993850708,
+      1.2026824951171875,
+      1.1909748315811157,
+      1.1490840911865234,
+      1.080478549003601,
+      1.0613453388214111
+    ],
+    "quantiles": {
+      "10%": [
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+        1.2773758172988892,
+        1.286991834640503,
+        1.2084007263183594,
+        1.1533130407333374,
+        1.1275498867034912,
+        1.1510555744171143,
+        1.1859495639801025,
+        1.1784849166870117,
+        1.1264795064926147,
+        1.0624356269836426,
+        1.036609172821045
+      ],
+      "20%": [
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+        1.1406043767929077,
+        1.126852035522461,
+        1.0352504253387451,
+        0.9691494703292847,
+        0.9420379400253296,
+        0.9503718018531799,
+        0.970925509929657,
+        0.9594371318817139,
+        0.9079477190971375,
+        0.8361266255378723,
+        0.8022069334983826
+      ],
+      "30%": [
+        1.1880751848220825,
+        1.1960833072662354,
+        1.187617301940918,
+        1.104191780090332,
+        1.0431063175201416,
+        1.01105535030365,
+        1.0347577333450317,
+        1.0594383478164673,
+        1.040370225906372,
+        0.9952926635742188,
+        0.9259791970252991,
+        0.8952187299728394
+      ],
+      "40%": [
+        1.2137157917022705,
+        1.232267141342163,
+        1.2349879741668701,
+        1.151865005493164,
+        1.0932612419128418,
+        1.0658776760101318,
+        1.084773302078247,
+        1.1106674671173096,
+        1.1036059856414795,
+        1.0548235177993774,
+        0.9882403016090393,
+        0.9593706727027893
+      ],
+      "50%": [
+        1.2394564151763916,
+        1.2593891620635986,
+        1.267505168914795,
+        1.1853008270263672,
+        1.127617597579956,
+        1.1061187982559204,
+        1.128767728805542,
+        1.1579902172088623,
+        1.1511956453323364,
+        1.1052223443984985,
+        1.03863525390625,
+        1.0152238607406616
+      ],
+      "60%": [
+        1.25933837890625,
+        1.285666823387146,
+        1.2950127124786377,
+        1.2207623720169067,
+        1.170255422592163,
+        1.1455552577972412,
+        1.1702347993850708,
+        1.2026824951171875,
+        1.1909748315811157,
+        1.1490840911865234,
+        1.080478549003601,
+        1.0613453388214111
+      ],
+      "70%": [
+        1.27677321434021,
+        1.3110136985778809,
+        1.3284480571746826,
+        1.2566629648208618,
+        1.2019660472869873,
+        1.1806211471557617,
+        1.2114834785461426,
+        1.2399210929870605,
+        1.2390201091766357,
+        1.1897773742675781,
+        1.1281580924987793,
+        1.1032856702804565
+      ],
+      "80%": [
+        1.2971320152282715,
+        1.3400218486785889,
+        1.3547290563583374,
+        1.2898554801940918,
+        1.2390310764312744,
+        1.2180578708648682,
+        1.248227596282959,
+        1.2842004299163818,
+        1.2832940816879272,
+        1.240414023399353,
+        1.175971508026123,
+        1.153149962425232
+      ],
+      "90%": [
+        1.3239599466323853,
+        1.3751201629638672,
+        1.403548240661621,
+        1.3310348987579346,
+        1.2891905307769775,
+        1.2702757120132446,
+        1.2997852563858032,
+        1.3408125638961792,
+        1.3354730606079102,
+        1.286876916885376,
+        1.2283769845962524,
+        1.2169079780578613
+      ],
+      "99%": [
+        1.3678879737854004,
+        1.4253658056259155,
+        1.4642648696899414,
+        1.40165376663208,
+        1.3632389307022095,
+        1.3453660011291504,
+        1.380732536315918,
+        1.4195259809494019,
+        1.416972041130066,
+        1.3775466680526733,
+        1.3122477531433105,
+        1.2959520816802979
+      ]
+    }
+  },
+  "summary": {
+    "forecast_mean_c": 1.186,
+    "forecast_max_c": 1.295,
+    "forecast_min_c": 1.061,
+    "vs_last_year_mean": -0.067
+  }
+}