| Name |
Type |
Description |
Notes |
| id |
str |
Agent-skill id. |
|
| app_id |
str |
The business-semantic scope this skill was written under. |
|
| project_id |
str |
Second half of that scope. |
|
| agent_id |
str |
The agent that owns this skill. |
|
| name |
str |
The skill's name. |
|
| description |
str |
What the skill is for, in a sentence. |
|
| content |
str |
The skill itself — the reusable procedure, ready to put in a prompt. |
|
| confidence |
float |
How much the distillation trusts this skill. Nominally 0.0–1.0, defaulting to 0.0 before anything scores it; the range is not enforced on the write path. Nothing in retrieval filters on it today, and how it divides labour with `maturity_score` is still open — so do not build a threshold on it yet. |
|
| maturity_score |
float |
How well-established the skill is. Nominally 0.0–1.0 and unenforced, and — unlike the other two scores — its default is 0.6 rather than 0.0, chosen so an unscored skill starts mid-optimistic. The cost is that an unscored 0.6 is indistinguishable from a scored 0.6: there is no "not evaluated" sentinel, and maturity scoring is skipped by default. Filtering near 0.6 is therefore unreliable. |
|
| source_case_ids |
List[str] |
The agent cases this skill was distilled from. Fetch them for the underlying evidence. |
[optional] |
| created_at |
datetime |
|
[optional] |
| updated_at |
datetime |
|
[optional] |
from everos_cloud.models.agent_skill_item import AgentSkillItem
# TODO update the JSON string below
json = "{}"
# create an instance of AgentSkillItem from a JSON string
agent_skill_item_instance = AgentSkillItem.from_json(json)
# print the JSON string representation of the object
print(AgentSkillItem.to_json())
# convert the object into a dict
agent_skill_item_dict = agent_skill_item_instance.to_dict()
# create an instance of AgentSkillItem from a dict
agent_skill_item_from_dict = AgentSkillItem.from_dict(agent_skill_item_dict)[Back to Model list] [Back to API list] [Back to README]