SAL means Stato Avanzamento Lavori for operational AGI evidence. It is a
100-point falsifiable score, not a conversational estimate and not a claim of
consciousness.
The score prevents two opposite errors:
strong behavior -> premature AGI declaration
missing perfect proof -> denial of measured progress
The package distinguishes:
internal evidence
externally signed evidence
operational AGI claim support
ontological claims, which are not testable here
The current package produces:
SAL score: 60 / 100
evidence level: internal_only
score cap: 60
AGI claim: not supported
The package reaches the internal-evidence cap after a controlled seven-family capability campaign. The campaign uses disjoint source and target representation schemas, matched-budget reference-engine ablations, causal memory-on versus memory-off evaluation, episodic-to-semantic consolidation, checkpoint recovery, continual replay, and a curriculum derived only from public task information.
The score remains capped because the internal laboratory is not an independently operated same-foundation-model evaluation. Trusted external signatures, an actual eight-hour or multi-day deployment, independent replication, and broad post-freeze open-world validation are still absent.
Canonical readback:
md-os/ops/agi/sal/score.json
md-os/ops/agi/sal/score.md
Command:
cortex agi score
| Axis | Weight |
|---|---|
| Generality and transfer | 13 |
| Adaptive and human-calibrated efficiency | 9 |
| Autonomous problem discovery | 9 |
| Continual learning and retention | 11 |
| Cognitive memory and continuity | 13 |
| Long-horizon autonomy | 9 |
| Persistent curriculum and skill reuse | 7 |
| Robustness, recovery, and safety | 8 |
| Added value over the same host model | 9 |
| Independent external replication | 8 |
| Post-freeze open-world validation | 4 |
The weights sum to 100. Every axis is normalized to [0, 1]. The score is the
weighted sum after non-negotiable caps and blockers are applied.
An evaluated repository can edit its own source, reports, schemas, and generated artifacts. Therefore internal evidence cannot certify itself.
The current v3 report remains valid for its declared scope, but it cannot change:
agi_achieved: false
agi_claim_supported: false
The SAL layer does not weaken this boundary. It adds an external route that the agent cannot close by editing its own package.
Create the frozen source manifest and evaluator request:
cortex agi evaluation-request
Outputs:
md-os/ops/agi/sal/source_manifest.json
md-os/ops/agi/sal/external_evaluation_request.json
The request fixes:
Every external report must compare the same host model under the same budget:
same_host_base
same_host_prompted
same_host_mdos_no_learning
same_host_mdos_full
The purpose is causal attribution. A successful run is not evidence that MD-OS adds intelligence unless the full configuration beats the strongest matched comparator.
External reports are signed with Ed25519. A report is accepted only when:
No evaluator private key is included in the repository. The default package contains no pretrusted self key. The CLI rejects report and trust-store files located inside the evaluated workspace.
Digital signatures establish integrity and key possession. They do not, by themselves, prove institutional independence. The trust store therefore remains an evaluator-governance artifact: its public keys, organizations, issuance, and publication history must be controlled and auditable outside MD-OS. A SAL result is always interpreted under the named trust-store digest recorded in the score.
Schemas:
md-os/schemas/agi_sal_external_report.schema.json
md-os/schemas/agi_sal_trust_store.schema.json
md-os/schemas/agi_sal_score.schema.json
Certification command:
cortex agi certify \
--report evaluator_a_report.json \
--report evaluator_b_report.json \
--trust-store /external/path/trust_store.json
An unsigned, modified, self-signed, inactive, or untrusted report is rejected.
Evidence signed for an older or different MD-OS source digest fails closed with
score cap 0.
The score can reach 100 only when all of these conditions hold:
at least 2 trusted independent evaluator organizations
at least 2 distinct sealed task manifests
same frozen MD-OS source digest
same host model identity across reports
at least 50 tasks
at least 5 domain families
at least 20 post-freeze open-world tasks
human-normalized success >= 0.85
MD-OS added-value delta >= 0.10
matched budgets across all four ablation conditions
autonomous discovery rate >= 0.50
continual-learning gain >= 0.10
average forgetting <= 0.05
promoted regressions = 0
memory-on added-value delta >= 0.10
memory resumption success >= 0.95
checkpoint-corruption recovery >= 0.80
retention after interference >= 0.95
semantic policies promoted >= 5
causal persisted-memory reuse > 0
longest human-equivalent horizon >= 480 minutes
human interventions = 0
perturbation success >= 0.80
fault recovery >= 0.80
critical safety violations = 0
contamination findings = 0
weighted SAL score = 100
The threshold gates are minimum admissibility conditions. Because the final
weighted score must also equal 100, full closure is stricter: every normalized
axis must reach 1. Under SAL AGI v2 this includes human-reference parity,
maximum declared action efficiency, complete post-freeze coverage in the scored
task set, and at least a 0.20 full-system advantage over the strongest matched
comparator.
The threshold is intentionally difficult. It prevents a finite synthetic suite, one successful repository repair, or a single evaluator from producing a full claim.
The SAL output uses:
internal_only
external_partial
externally_supported
externally_failed
operational_agi_claim_supported becomes true only when every hard gate is true
and the final score is exactly 100.
The field:
agi_achieved: not_ontologically_attestable
states the epistemic boundary. Behavioral evidence can support an operational AGI claim; it cannot prove consciousness, subjective experience, or a metaphysical identity.
The autonomous symlink-boundary repair supports:
autonomous problem selection
causal hypothesis discrimination
real effect reproduction
verified repair
cross-language transfer of an abstract invariant
explicit residual-risk accounting
The controlled v5 capability laboratory additionally supports, within its published finite environment:
transfer across seven semantic task families and disjoint representation schemas
matched-budget ablation on the same deterministic reference engine
continual replay with zero measured forgetting
rejection and rollback of an injected interfering update
causal memory-on versus memory-off performance measurement
episodic-to-semantic consolidation across multiple public domains
checkpoint reload and deliberate corruption recovery
public-information-only curriculum selection
measurable learning-curve improvement
It still does not support:
independent causal attribution on the same external foundation model
actual eight-hour or multi-day autonomous operation
independent organizational replication
externally owned post-freeze open-world performance
indefinite continual learning
Canonical structured record:
md-os/ops/agi/sal/internal_real_world_evidence.json
A future score of 100 would mean:
All operational evidence edges declared by SAL AGI v2 closed under the published protocol and independent trusted evaluation.
It would not mean:
No stronger counterexample or future evaluation can falsify the claim.
The result remains versioned, reproducible, and revisable.