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12 changes: 11 additions & 1 deletion 10-prd/behavior/capabilities.md
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## Capability: Semantic retrieval

- related claim(s): expose info-base information for retrieval and downstream use; retrieve semantically related info-base entities
- non-goal: semantic retrieval does not generate an answer, create transient information units, silently maintain its index while reading, or imply that feature and graph-navigation retrieval are implemented
- non-goal: semantic retrieval does not generate an answer, create transient information units, silently maintain its index while reading, or subsume feature and graph-navigation retrieval

## Capability: Lexical feature retrieval

- related claim(s): expose info-base information for retrieval and downstream use; recall blocks from lexical feature evidence
- non-goal: lexical feature retrieval does not generate an answer, recursively index the graph, replace semantic or graph-navigation retrieval, or imply perceptual/hybrid retrieval is implemented

## Capability: Media interpretation

- related claim(s): organize information in one reusable info-base; recall blocks from lexical feature evidence
- non-goal: system-driven interpretation is one additive organization approach; it does not replace faithful Resolver materialization, write retrieval records directly, or define all media organization

## Capability: Focal-block rumination

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11 changes: 10 additions & 1 deletion 10-prd/behavior/claims.md
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- evidence expectation: a real provider embeds graph state collected through ordinary Memos, RSS, Atom, storage, resolver, and organization boundaries; judged primary entities enter the global top three and outrank explicit distractors.
- source rationale: `../_drivers/market-and-user-pressures.md`, `../_drivers/business-and-service-objectives.md`
- realization pointers: `../../20-product-tdd/semantic-retrieval-and-peer-capabilities.md`, `../../20-product-tdd/claim-realization-matrix.md`
- impact on existing claims: this realizes semantic retrieval only; feature retrieval, graph-navigation retrieval, answer generation, and Chat InKCre remain independent product capabilities.
- impact on existing claims: this realizes semantic retrieval only; feature retrieval, graph-navigation retrieval, answer generation, and Chat InKCre remain independent product capabilities even when another capability is also implemented.

## Claim: InKCre recalls blocks from lexical feature evidence

- claim intent: a person, Agent, or downstream capability should be able to recover an existing block from exact clues remembered from its label, content, metadata, transcript, subtitle, OCR, or useful interpretation.
- evaluation dimensions: one bounded query returns existing blocks with an explainable literal or term-match reason and a plain excerpt; contiguous Chinese fragments do not depend on a Chinese tokenizer; missing or stale derived support is maintained separately from the read.
- evidence expectation: ordinary collected and organized graph state proves exact identifiers, Chinese fragments, metadata-only clues, document bodies, faithful image/audio/video text, and model-authored media interpretation through the same retrieval contract.
- source rationale: `../_drivers/market-and-user-pressures.md`, `../_drivers/business-and-service-objectives.md`
- realization pointers: `../../20-product-tdd/feature-retrieval-and-media-interpretation.md`, `../../20-product-tdd/claim-realization-matrix.md`
- impact on existing claims: this realizes lexical feature retrieval only; semantic similarity, graph-navigation, perceptual matching, hybrid composition, answer generation, and Chat InKCre remain independent capabilities.

## Claim: InKCre accepts memo-like capture through familiar clients

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12 changes: 12 additions & 0 deletions 10-prd/behavior/rules-and-invariants.md
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- violation impact: block semantics become harder to reason about and downstream use loses clarity.
- linked claim(s): organize information in one reusable info-base; expose info-base information for retrieval and downstream use

## Retrieval projections remain derived and independently maintained

- rationale: lexical records and embeddings accelerate application queries but do not become information authority or a hidden read-time organization path.
- violation impact: a query could mutate graph/index state unexpectedly, stale support could be mistaken for authored truth, or collection/organization ownership could leak into retrieval.
- linked claim(s): expose info-base information for retrieval and downstream use; retrieve semantically related info-base entities; recall blocks from lexical feature evidence

## Faithful media text and interpretation keep different meaning

- rationale: transcript, subtitle, and OCR aim to preserve source evidence, while a model-authored description or summary adds an interpretation for later use.
- violation impact: users and downstream capabilities could no longer tell source-derived information from organization-authored meaning, and Resolver materialization would silently acquire organization authority.
- linked claim(s): organize information in one reusable info-base; recall blocks from lexical feature evidence

## Exact source evidence outranks heuristic duplicate reduction

- rationale: stable native identity can justify reconciliation, while content fingerprints and time cutoffs provide weaker and less stable guarantees.
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16 changes: 16 additions & 0 deletions 10-prd/behavior/workflows.md
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- exception flow: unavailable projections and stale records remain absent until explicit maintenance; a missing profile or eligible provider fails explicitly; uncertain post-dispatch outcomes are not replayed automatically
- observable outcome: at least one useful existing block or relation is returned under a stated ranking contract without an answer-generation step

## Workflow: Lexical Feature Retrieval

- actor: a person, Agent, or downstream application capability
- trigger: the actor submits one textual clue remembered from an information unit
- normal flow: the capability compares the clue with fresh Block-local label/text projections and returns a small ranked set of existing blocks with plain excerpts and explicit match evidence
- exception flow: unavailable projections and stale records remain absent until independent maintenance; the query does not repair records or recursively pull text through graph relations
- observable outcome: an existing target block can be recovered from an exact identifier, fragment, metadata clue, document body, faithful media text, or prior interpretation without generating an answer

## Workflow: System-Driven Media Interpretation

- actor: organization capability running through a capable peer
- trigger: a typed one-shot job starts, normally after a configured Cron occurrence
- normal flow: the capability selects media blocks still missing an interpretation, routes each modality to its configured Agent, and adds useful interpretation blocks and relations through ordinary graph authority
- exception flow: one unavailable modality, provider failure, or honest no-output result does not block useful independent candidates; completed graph effects remain and the next job derives its candidate set from current graph state
- observable outcome: useful image, audio, or video meaning is added as an explicit interpretation graph that later application capabilities may retrieve

## Workflow: Focal-Block Rumination

- actor: a person or application surface choosing one existing block
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12 changes: 12 additions & 0 deletions 10-prd/glossary.md
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- user-visible or business lifecycle language: finding or navigating information and its context.
- notes on ambiguity with framework terms: an application capability may use a sink, index, embedding, or resolver projection without transferring graph authority.

## feature retrieval

- canonical business meaning: retrieving information from observable features that do not require semantic-similarity ranking or an already-materialized graph path.
- user-visible or business lifecycle language: finding something from a clue remembered about it.
- notes on ambiguity with framework terms: lexical and future perceptual retrieval are feature-retrieval families; graph-navigation owns facts already expressed as graph structure, and hybrid retrieval composes rather than redefines the primitive capabilities.

## lexical retrieval

- canonical business meaning: feature retrieval over a block's bounded textual projection, including labels, literal fragments, terms, document text, faithful media text, and explicit interpretations.
- user-visible or business lifecycle language: finding an information unit by a word, phrase, identifier, filename, transcript, subtitle, OCR clue, or description.
- notes on ambiguity with framework terms: lexical retrieval returns existing blocks; it is not Chat, answer generation, recursive graph indexing, or a promise of language-specific tokenization.

## memo-like capture

- canonical business meaning: low-friction collection of thoughts, surrounding events, and small pieces of information through a memo client or collector.
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5 changes: 3 additions & 2 deletions 20-product-tdd/claim-realization-matrix.md
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| Reliably collect RSS and Atom feeds | RSS extension maps bounded RSS 2.0/Atom snapshots to feed, item, enclosure, full-text, and semantic-content graph state | `core-py` | Real-protocol HTTP doubles, PostgreSQL graph acceptance, optional live endpoint smoke, exact replay/update/state/enrichment cases; not a feed-reader product |
| Preserve email communication records for later use | Mail extension maps protocol-neutral Mail facts to source, mailbox, canonical email, participant, body, MIME, flag, and reply/reference graph state; remote MIME bytes are materialized lazily | `core-py`; `client-web` as Job peer, info-base navigation host, and resolver consumer | Real Dovecot/IMAP plus PostgreSQL proves ordinary collection, bounded backfill, remote materialization, and built-browser rendering; not a Mail-only inbox or complete email agent |
| Accept memo-like capture through familiar clients | Memos extension provides the first memo-family backend access mode | `core-py`; `client-web` for deployment-scoped extension configuration | Backend write/read, comments, attachments, hot credential replacement, hot enable/disable, and graph round-trip |
| Organize information in one reusable info-base | Explicit focal-block rumination is the first admitted organization approach; an Agent may add an ordinary graph interpretation while preserving the focal graph | `core-py`; `client-web` as an explicit trigger surface | Real-provider Resolver/Agent/Tool/graph journey and meaningful no-write boundary; not a complete organization taxonomy, periodic organizer, replacement, merge, or linking realization |
| Expose information for retrieval and downstream use | Semantic retrieval returns one bounded global ranking of existing Blocks/Relations and score metadata; feature and graph-navigation retrieval remain future | `core-py`; `client-web` and future Agent/application consumers | Pinned real Memos/RSS/Atom/HTML/storage corpus, real provider embedding and rumination, four top-three/distractor judgments, local and delegated Peer journeys; not answer generation or Chat InKCre |
| Organize information in one reusable info-base | Explicit focal-block rumination and system-driven media interpretation are admitted organization approaches; Agents may add ordinary graph interpretations while preserving existing graph authority | `core-py`; `client-web` as an explicit rumination trigger and retrieval consumer | Real-provider Resolver/Agent/Tool/graph journeys, meaningful no-write boundary, and bounded independent media candidates; not a complete organization taxonomy, replacement, merge, or linking realization |
| Expose information for retrieval and downstream use | Semantic retrieval ranks existing Blocks/Relations by meaning; lexical feature retrieval recalls existing Blocks from explainable textual clues; graph-navigation and hybrid composition remain independent | `core-py`; `client-web` and future Agent/application consumers | Pinned real multi-source/document/media corpus, real embedding and multimodal providers, local/delegated Peer journeys, and browser List navigation; not answer generation or Chat InKCre |
| Retrieve semantically related info-base entities | Resolver/Relation projections feed profile-scoped derived embeddings; one domain facade executes locally or delegates the exact capability to an eligible Peer | `core-py`; `client-web` Peer consumer | Freshness/invalidation/maintenance checks, global Block/Relation ranking, real provider quality gate, exact-target and failover/outcome-unknown protocol cases |
| Recall blocks from lexical feature evidence | Block-local Resolver labels/text feed one derived record per Block; one facade ranks exact/substring/term evidence locally or through an eligible Peer | `core-py`; `client-web` Peer consumer and InfoBaseListView host | Exact identifiers, Chinese fragments, Mail metadata, PDF body, real image/audio/video faithful text, Agent interpretation, freshness/Jobs, delegated Peer, and built-browser navigation |
10 changes: 10 additions & 0 deletions 20-product-tdd/cross-unit-contracts.md
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- Peer discovery and invocation remain separate. The generic Peer layer sees exact capability
identities and opaque protocol payloads; each business capability keeps its typed request,
result, and local execution semantics.

## Feature Retrieval And Media Interpretation Contract

- Block-local lexical projection,derived-record maintenance,explainable ranked results,
multimodal AI content parts,faithful Resolver text materialization,system-driven media
interpretation and List-host navigation are owned by the
[Feature Retrieval And Media Interpretation Contract](feature-retrieval-and-media-interpretation.md).
- Resolver materialization and Organization may add graph facts,but the lexical retrieval
owner alone maintains lexical records。Exact synchronous retrieval uses the generic Peer
protocol without giving PeerManager the query or result meaning。
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