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# DAMS V5 / Memory Control Plane — Worked Examples and Fixtures

**Document type:** Review fixtures appendix.  
**Purpose:** Stress-test the proposed concept model across legal and non-legal examples, from extraction through canonicalization, use, uncertainty, promotion, degradation, injection, and learning.

---

## Fixture format

Each fixture should specify:

```text
Input / source
Extraction route
Extraction output
Canonical resolution
Policy result
Organization / membership
Injection product
Learning signal
Expected failure mode if incorrectly handled
```

---

# Fixture 1 — “Qwen is not working”

## Scenario

User says in chat:

```text
Qwen isn't working.
```

## Correct classification

```text
Source: chat / current session / possible system observation
Extraction route: chat_capture or incident_capture
Temporal profile: instant_status or short_incident
Extraction output: IncidentObservation and/or FrictionEvent
Default disposition: retain_ephemeral_observation / record_friction_event
Not default: durable Assertion
```

## Canonical resolution

Do not create durable Assertion unless recurrence, logs, or explicit diagnosis support it.

If repeated:

```text
FrictionPattern:
  structural_fingerprint = qwen_embedding_failure
  recurrence_count = n
  severity = computed
```

If diagnosed:

```text
Assertion:
  “Qwen embedding fails when MLX cache path is unavailable.”
Procedure:
  “When Qwen embedding fails, check MLX cache path and restart embedding service.”
```

## Injection

Same session:

```text
Recent operational caution:
Qwen embedding failed in this session. If embedding is required, verify availability before relying on extraction.
```

After TTL without recurrence:

```text
Do not inject as current fact.
```

## Learning

- storage/extraction: do not promote transient status;
- friction learning: recurrence may create prevention candidate;
- injection learning: caution should be capped and recent-only.

## Failure mode

If stored as durable Assertion, Elnor may keep injecting “Qwen is broken” long after the issue is fixed.

---

# Fixture 2 — “Qwen3-Embedding-0.6B via MLX is locked”

## Scenario

System status / architecture note states:

```text
Qwen3-Embedding-0.6B via MLX is the locked embedding infrastructure.
```

## Correct classification

```text
Source: status/spec source
Extraction route: source/corpus extraction or manual architecture memory
Temporal profile: rolling_operational
Extraction output: AssertionCandidate
Disposition: create_or_merge_assertion if source-supported
```

## Canonical resolution

```text
Assertion:
  canonical_statement: “Qwen3-Embedding-0.6B via MLX is the locked embedding infrastructure.”
  temporal_profile: rolling_operational
  staleness_state: fresh / verification_required if model-stack status changes
```

## Injection

```text
Direct Memory Item or Assertion Packet:
Role: system configuration assertion
Warrant: assert if current status source is fresh; verify_before_use if model stack may have changed
```

## Learning

If repeatedly helpful in architecture decisions, strengthen utility for embedding-infrastructure questions. Do not use BDSM utility as epistemic confidence.

## Failure mode

If treated as permanent historical fact only, Elnor may fail to verify after model-stack changes. If treated as transient incident, it may be forgotten incorrectly.

---

# Fixture 3 — “The memory system broke because specs were underspecified”

## Scenario

During design discussion:

```text
My memory system is broken because the specs weren't correct.
```

## Correct classification

```text
Source: user/assistant design discussion
Extraction route: chat_capture / architecture review
Temporal profile: project_bounded design diagnosis
Extraction output: IssueFrameUpdate + AssertionCandidate
Disposition: update_issue_frame; create Assertion only if supported by review evidence
```

## Canonical resolution

Initial:

```text
IssueFrame:
  question: “Why did the memory architecture fail / what must V5 fix?”
  hypothesis: “Failures were caused by underspecified spec boundaries and phantom seams.”
```

If supported by red-team findings:

```text
Assertion:
  “Prior memory architecture failures were materially caused by under-specified owner boundaries and phantom seams.”
  support_edges: red-team findings, examples, architect confirmation
  warrant: hedge or assert depending support
```

## Injection

For architecture review:

```text
IssueFrame Orientation:
Working hypothesis: prior memory failures trace to underspecified boundaries, duplicate truth stores, and phantom DOC8 seams.
```

If promoted:

```text
Assertion Packet:
Use as architecture constraint.
```

## Learning

- issue-frame learning: working diagnosis useful;
- injection learning: distinguish working hypothesis from settled design conclusion;
- storage learning: promotion only after evidence.

## Failure mode

If injected as settled fact too early, it may over-anchor design. If ignored entirely, Elnor loses the live diagnostic frame.

---

# Fixture 4 — Ninth Circuit scienter elements from Topic and Library/corpus

## Scenario

The same legal proposition is found through:

1. A Ninth Circuit case in a case-law Library.
2. A Marex brief inside a deeply ingested litigation Library/corpus.
3. TopicCollectionDirective: “Collect Ninth Circuit scienter law.”

Proposition:

```text
Ninth Circuit scienter pleading requires facts supporting a strong inference of intent or deliberate recklessness under the PSLRA/Tellabs comparative-inference framework.
```

## Correct classification

```text
Source A: case law
Route A: library/corpus extraction
Output A: AssertionCandidate + EvidenceSupportEdge(primary_authority)

Source B: party brief
Route B: corpus extraction
Output B: AssertionCandidate or EvidenceRecord + EvidenceSupportEdge(party_argument)

Source C: Topic directive
Route C: topic_collection
Output C: AssertionCandidate or membership edge
```

## Canonical resolution

All routes converge to one canonical Assertion:

```text
Assertion:
  canonical_question: “What are the Ninth Circuit scienter pleading requirements?”
  variants:
    - deliberate recklessness formulation
    - Tellabs comparative-inference formulation
    - core operations formulation if applicable
    - insider-sales formulation if applicable
```

Topic and Library attach memberships/support; they do not create separate truth objects.

## Injection

User asks:

```text
What are the Ninth Circuit scienter elements?
```

Inject:

```text
Assertion Packet:
- Assertion: Ninth Circuit scienter pleading standard
- Source support: primary authority
- Warrant: verify_before_use unless current authority sweep is fresh
- Search more: Topic and Library affordances
```

User asks:

```text
How did Marex plead scienter?
```

Inject:

```text
Library Source Slice / CU:
- source-bound synthesis of Marex briefing
- Marex-specific facts and arguments
- reusable scienter Assertion only as background law
```

## Learning

- Topic extraction recall/precision;
- Library Source Slice usefulness;
- Assertion Packet correctness;
- stale-authority detection.

## Failure mode

If Topic and corpus each create their own truth object, Elnor may inject duplicate or conflicting scienter rules.

---

# Fixture 5 — Marex briefing ConsolidatedUnderstanding

## Scenario

Deep ingestion of a Marex briefing Library/corpus produces:

```text
The Marex briefing record shows plaintiff relied on confidential witnesses, insider sales, and accounting irregularities to plead scienter, while defendants attacked particularity and innocent inferences.
```

## Correct classification

```text
Source: Marex briefing Library/corpus
Extraction route: corpus_deep_extraction
Extraction mode: synthesized
Output: ConsolidatedUnderstanding
Temporal profile: source_bounded
```

## Canonical resolution

Do not create a general scienter Assertion directly from the CU unless assertion resolution finds source support.

Possible downstream outputs:

- EvidenceRecord: what the brief said.
- AssertionCandidate: “Insider sales may support scienter if unusual or suspicious.”
- IssueFrameUpdate: “Marex scienter theory may be weak unless sale timing/amount is suspicious.”
- TopicMembership: Marex knowledge, Ninth Circuit scienter, insider sales.

## Injection

For source-specific prompt:

```text
Library Source Slice / CU Context:
Role: source-bound synthesis
Warrant: use to describe Marex briefing record, not general law
```

For general legal prompt:

```text
Do not inject CU as law. Pull resolved Assertions and authority support instead.
```

## Failure mode

Treating the CU as universal law contaminates general answers with matter-specific argument summaries.

---

# Fixture 6 — “Call me Will”

## Scenario

User says:

```text
Call me Will.
```

## Correct classification

```text
Source: user direct statement
Extraction route: chat_capture
Output: DirectiveCandidate
Temporal profile: standing_preference
Disposition: create directive if intent is clear
Not: Assertion, unless separately needed as identity fact
```

## Injection

```text
Directive Block:
Use “Will” when addressing the user.
```

## Degradation

Superseded only by later user instruction.

## Failure mode

If stored as Assertion “user’s name is Will,” Elnor may misuse it as legal/identity fact.

---

# Fixture 7 — “This mix sounds harsh around 3kHz”

## Scenario

User says after audio work:

```text
This mix sounds harsh around 3kHz.
```

## Correct classification

Possible outputs:

```text
AssertionCandidate:
  “Mix A sounds harsh around 3kHz.”
  temporal_profile: source_bounded / project_bounded

IssueFrameUpdate:
  open issue: “Determine whether harshness is vocal EQ or guitar bus.”

ProcedureCandidate:
  “When a mix feels harsh, check 2.5–4kHz before adding compression.”
```

## Resolution

- Specific observation → source/project-bounded Assertion.
- Unresolved cause → IssueFrameUpdate.
- General method → ProcedureCandidate.

## Injection

For Mix A work:

```text
IssueFrame Orientation:
Open issue: harshness source unresolved.

Procedure Block:
Check 2.5–4kHz before adding compression.
```

For unrelated music prompt:

```text
Do not inject unless relevant to mixing / same project.
```

## Failure mode

If generalized too quickly, Elnor may apply one track’s subjective observation to unrelated mixes.

---

# Fixture 8 — Pineapple allergy updated

## Scenario

Prior memory:

```text
Will is allergic to pineapple.
```

User correction:

```text
I can have pineapple now if I take medication.
```

## Correct classification

```text
Source: user direct correction
Extraction route: chat_capture
Output: AssertionCandidate + possibly ProcedureCandidate/DirectiveCandidate
Temporal profile: standing_preference / health condition
```

## Canonical resolution

One Assertion with variants:

```text
Assertion: User pineapple tolerance condition
Variant 1: “User is allergic to pineapple.”
  state: superseded / historical_only
Variant 2: “Pineapple is conditionally acceptable if medication condition is met.”
  state: active
```

Possible procedure/directive:

```text
When suggesting food involving pineapple, ask or mention medication condition if relevant.
```

## Injection

```text
Warning/Constraint:
Prior pineapple allergy memory has been updated. Pineapple is conditionally acceptable if medication condition applies.
```

## Failure mode

If flat replacement deletes history, the system loses safety provenance. If old variant remains active, the system continues false exclusion.

---

# Fixture 9 — Topic extraction over same corpus as Library ingestion

## Scenario

User has:

```text
Library: Securities cases
Topic: Ninth Circuit scienter law
```

The Library ingestion and TopicCollectionDirective both process the same Ninth Circuit case.

## Expected result

Two dedupe layers:

```text
Source dedupe:
  same SourceArtifact / ArtifactSegment / citation / span

Assertion dedupe:
  same Assertion / AssertionVariant for the scienter proposition
```

Topic gets membership edge.
Library retains source membership.
No duplicate truth.

## Injection

If user asks about Topic:

```text
Topic Slice renders the Assertion once, with source support from the Library.
```

If user asks about Library:

```text
Library Source Slice renders source spans; may include linked Assertion.
```

## Failure mode

Rendering the same proposition as Topic fact, Library fact, and direct Assertion causes prompt bloat and conflicting confidence.

---

# Fixture 10 — RecentActivityRollup orientation only

## Scenario

RecentActivityRollup says:

```text
Yesterday you worked on Marex scienter arguments and flagged insider sales as weak.
```

## Correct classification

```text
Object: RecentActivityRollup
Role: framing_context / recent_work_orientation
Not: source evidence
```

## Injection

```text
Recent Work Orientation:
Yesterday’s work flagged insider sales as a weak point in Marex scienter strategy.
Use as orientation only; pull source-backed evidence before asserting.
```

## Failure mode

If treated as evidence, Elnor may assert a legal/factual point based only on a recent-work summary.

---

# Fixture 11 — Topic Notice vs Topic Slice

## Scenario A — vague prompt

User asks:

```text
What do we have on scienter?
```

Expected:

```text
Topic Notice + search affordances.
Maybe concise Topic Slice if core pinned items are obvious.
```

## Scenario B — direct prompt

User asks:

```text
What is the Ninth Circuit standard for pleading scienter based on insider sales?
```

Expected:

```text
Topic Slice + Notice.
Include only directly relevant Assertions/evidence.
```

## Failure mode

Always injecting the full Topic floods context. Always showing only a notice under-serves direct prompts.

---

# Fixture 12 — Library Notice vs Library Source Slice

## Scenario A — broad source availability

User asks:

```text
Do we have source material on DAMS red-team reviews?
```

Expected:

```text
Library Notice:
Library exists, contains red-team reviews, search affordances available.
```

## Scenario B — source-grounded answer

User asks:

```text
What exactly did the red teams say about ScopeRoot overload?
```

Expected:

```text
Library Source Slice:
source-backed excerpts / extracted findings with citations or provenance.
```

## Failure mode

Notice-only when source-grounded answer is needed forces user to ask again. Source-slice when only availability is needed wastes context.

---

# Fixture 13 — Cross-scope / ethical-wall block

## Scenario

Prompt appears to relate to Henderson, but high-value memory is from Marex privileged strategy.

## Correct handling

Scope model detects:

```text
active/relevant scope: Henderson
candidate memory scope: Marex
relation: cross-scope / potentially firewalled
policy: deny or reference-only
```

## Injection

```text
Warning / Constraint:
Potentially relevant material exists in a different protected scope and is unavailable for this prompt.
```

No substantive Marex content.

## Failure mode

Cross-matter leakage through “framing context.”

---

# Fixture 14 — Policy drift restamping

## Scenario

Assertion was stamped under policy generation N. Policy generation N+1 tightens export/carryover.

## Expected

```text
PolicyStampInvalidation emitted.
Runtime use requires restamp or conservative fallback.
```

Injection/carryover:

```text
local_only / reference_only / blocked until restamped
```

## Failure mode

Old permissive stamp allows unsafe export.

---

# Fixture 15 — False suppression sampling

## Scenario

Learning suppresses a category of memory that later proves useful.

## Expected

- suppressed memory sampled within policy-eligible partitions;
- if user engages with sampled item, update false-suppression metric;
- do not sample policy-blocked content into cloud prompts.

Metrics:

```text
learning_suppression_false_positive
budget_pressure_false_negative
staleness_false_negative
policy_eligible_suppressed_false_negative
policy_blocked_not_sampled
```

## Failure mode

Wrongly suppressed memory stays invisible forever.

---

# Fixture 16 — KDA reference-only rendering

## Scenario

Policy permits reference-only presence but not inline substantive rendering.

## Expected

DOC24 resolves card presence:

```text
included_reference_only
```

KDA renders diagnostic/reference label only.

Not allowed:

```text
compact substantive rendering
```

## Failure mode

Sensitive content leaks through “compact” rendering.

---

# Fixture 17 — Final prompt proof before utility

## Scenario

Memory candidate was retrieved and rendered in an intermediate packet but excluded before final prompt.

## Expected

BDSM/DOC8 utility:

```text
no utility signal for absent card
```

Learning only from final-prompt proof.

## Failure mode

Utility learning attributes success to memory the LLM never saw.