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feat: Added Agent skills for AI Agents#6007

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patelchaitany wants to merge 3 commits intofeast-dev:masterfrom
patelchaitany:agent-skills
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feat: Added Agent skills for AI Agents#6007
patelchaitany wants to merge 3 commits intofeast-dev:masterfrom
patelchaitany:agent-skills

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@patelchaitany
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@patelchaitany patelchaitany commented Feb 23, 2026

What this PR does / why we need it:

This PR adds the SKILLS for the AI Agents.

Which issue(s) this PR fixes:

#5976

Misc

For creating this Agent SKILLS i used the skill-creator skill from the https://github.com/anthropics/skills


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✅ Devin Review: No Issues Found

Devin Review analyzed this PR and found no potential bugs to report.

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@soooojinlee soooojinlee left a comment

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would it make sense to place these under .claude/skills/ (or similar) instead of a top-level Agent-Skill/ directory? I think the https://github.com/anthropics/skills convention typically uses that path.

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Exactly @soooojinlee - those .claude/skills usually live in the User Directory rather than the main Git repo. Most devs either create a specific subdirectory for skills within the project or manage them in a separate Git repo entirely.

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Devin Review found 1 new potential issue.

🐛 1 issue in files not directly in the diff

🐛 Inverted default value logic in _construct_random_input for singleton vs batch mode (sdk/python/feast/on_demand_feature_view.py:1014)

In _construct_random_input, the default value for missing types has its condition inverted. When singleton=False (batch mode), sample_values contains lists (e.g., ["hello world"]), but default_value is set to None (a scalar). When singleton=True, sample_values contains scalars (e.g., "hello world"), but default_value is set to [None] (a list).

Root Cause

The condition on line 1014 reads:

default_value = None if not singleton else [None]

This produces:

  • singleton=Falsedefault_value = None (should be [None] to match list-based sample values)
  • singleton=Truedefault_value = [None] (should be None to match scalar sample values)

The condition is backwards. Lines 1010-1011 show that when singleton=True, sample_values are converted to scalars via {k: v[0] for k, v in sample_values.items()}. So the default should also be a scalar (None) for singleton and a list ([None]) for non-singleton.

Impact: When a feature's ValueType is not found in the sample values map (e.g., an unusual or custom type), the wrong shape of default value is used. In batch mode, a None scalar is passed where a list is expected, potentially causing transformation inference (infer_features) to fail or produce incorrect results. In singleton mode, a [None] list is passed where a scalar is expected.

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