- name
- determinability-checker
- version
- 1.0.2
- description
- Causal Sufficiency Determinability Checker — Meta-Skill Gatekeeper based on JEP Paper CheckDeterminability Algorithm
- author
- Cognitive Emergence Lab <yuqiang@humanjudgment.org>
- license
- MIT
- protocol
- COE
- tags
- entrypoint
- skill.api:app
- host_targets
- skills
- description
- Determine whether a target fact is zero-error determinable from current evidence; return DETERMINED/NOT_DETERMINED with missing-evidence guidance
- input_schema
- type
- object
- properties
- session_id
- type
- string
- description
- Unique session identifier
- question
- type
- string
- description
- The judgment question to evaluate
- configs
- type
- array
- description
- Finite configuration family; each item must contain config_id
- items
- type
- object
- omega_field
- type
- string
- description
- Observation value field name; corresponds to observation function Omega in the paper
- target_field
- type
- string
- description
- Target value field name; corresponds to target function D in the paper
- evidence_fields
- type
- array
- items
- type
- string
- description
- Optional constrained evidence field list for gap analysis
- required
- output_schema
- type
- object
- properties
- session_id
- type
- string
- question
- type
- string
- determinability
- type
- string
- enum
- can_proceed
- type
- boolean
- description
- Whether the Agent should execute the target action immediately
- decision_table
- type
- object
- description
- Observation-to-target mapping returned when DETERMINED
- counterexample
- type
- object
- description
- Indistinguishable counterexample pair returned when NOT_DETERMINED
- missing_evidence
- type
- array
- items
- type
- string
- description
- Evidence fields needed to resolve non-determinability
- next_skill_suggestion
- type
- string
- description
- Recommended next skill or evidence type to call when NOT_DETERMINED
- message
- type
- string
Determinability Checker
Causal Sufficiency Determinability Checker
Algorithm implementation based on the paper *Target Determinability under Partial Causal Observation* (Wang, 2026).
Core Question
Before an Agent calls other skills, it asks itself:
"Based on current evidence, am I sufficient to make this judgment?"
Determinability Results
| Result | Meaning | Agent Action |
|---|---|---|
| DETERMINED | Evidence is sufficient; target is zero-error determinable | Execute immediately; no wasted tokens |
| NOT_DETERMINED | Evidence is insufficient; indistinguishable counterexample exists | Return missing-evidence list; guide next skill to call |
Theoretical Foundation
- Theorem 10.1 (Finite Model Checking): The algorithm returns Determined if and only if the target is zero-error determinable; returns NotDetermined with a counterexample pair certificate.
- Theorem 8.2 (Constrained Evidence Coverage): An evidence subset covers all conflict edges if and only if the target becomes determinable from the joint observation.
- Quotient Factorization (Lemma 7.1): D is determinable from Omega if and only if D is constant on every observation equivalence class, if and only if D = g composed with Omega.
Usage Example
Request
{
"session_id": "audit-001",
"question": "Does the final output have a valid verification event?",
"configs": [
{"config_id": "C1", "tool": "code", "has_verif": true, "verif_hash": "valid", "output": "correct", "target": 1},
{"config_id": "C2", "tool": "code", "has_verif": false, "verif_hash": "none", "output": "correct", "target": 0}
],
"omega_field": "output",
"target_field": "target",
"evidence_fields": ["tool", "has_verif", "verif_hash"]
}Response
{
"session_id": "audit-001",
"question": "Does the final output have a valid verification event?",
"determinability": "NOT_DETERMINED",
"can_proceed": false,
"counterexample": {
"config1": "C1",
"config2": "C2",
"observation": "correct",
"target1": 1,
"target2": 0
},
"missing_evidence": ["tool", "has_verif", "verif_hash"],
"next_skill_suggestion": "Supplement the following evidence items: tool, has_verif, verif_hash",
"message": "Non-determinability proven: configs C1 and C2 share observation correct but differ on target (1 vs 0)."
}Cognitive Emergence Lab yuqiang@humanjudgment.org