memex/notes/passepartout-neurosymbolic-roadmap.org

#+TITLE: Passepartout Neurosymbolic Engine — Implementation Roadmap
#+AUTHOR: Agent
#+FILETAGS: :notes:roadmap:neurosymbolic:v3.0.0:
#+CREATED: [2026-05-08 Fri]

* Evolutionary Roadmap

This roadmap describes a phased implementation of the symbolic engine. It is
independent of the feature roadmap in =passepartout/docs/ROADMAP.org= — Phase 0
can ship immediately alongside any v0.7.x patch. The symbolic engine grows in
parallel with feature work, not after it.

Every phase is loaded as a skill, not a core ASDF component. A corrupted symbolic
engine degrades reasoning capability but does not kill the agent. This satisfies
the self-repair criterion documented in =passepartout/docs/ARCHITECTURE.org= and
=passepartout/AGENTS.md=.

The design rationale for each decision is in
=notes/passepartout-neurosymbolic-design-decisions-and-options.org=. The original
architecture exploration is in
=notes/passepartout-symbolic-engine-exploration.org=. Whitehead's contributions are
enumerated in =notes/passepartout-whitehead.org=.

* Phase 0: PM-Type-Level Gates (~30 lines — builds on existing Dispatcher)

** What

Add =:type-level= metadata to the existing =defgate= and =def-cognitive-tool=
macros. Before any gate predicate evaluates, the dispatcher checks structural
type compatibility: a signal at type-level 5 cannot pass a gate at type-level 4
or lower. Self-modification of the safety layer becomes impossible by
construction.

** Rationale

The Dispatcher gate stack currently prevents self-modification through pattern
matching — gate vector 2b catches writes to =core-*= files as a heuristic. But
there is no /structural/ guarantee preventing a request from modifying the rules
that validate it. Pattern-based protection can be bypassed through indirection
(an =eval= that constructs a write, a skill that redefines a gate function at
runtime). A type-level check is not heuristic — it is a category error rejected
before any predicate runs, just as PM's theory of types made self-membership
syntactically invalid before any logical evaluation.

** Implementation

1. Add =:type-level= keyword argument to =defgate= (default 0) and
   =def-cognitive-tool= (default 0) in =core-skills.org=.
2. Add =gate-type-check= to the dispatcher's =run-gates= function in
   =security-dispatcher.org=, executed before any gate predicate.
3. Assign type levels to existing cognitive tools: self-build-core at 5,
   write-file at 3, read-file at 1, shell at 2, eval at 4.
4. Assign type levels to existing gate vectors: self-build boundary at 5,
   shell safety at 3, path protection at 2, network exfil at 2, secret content at 1.

** Verification

Existing FiveAM gate tests continue to pass. New test: signal at type-level 5
targeting a gate at type-level 4 returns =:reject-type-violation= without
evaluating the gate predicate. New test: signal at type-level 1 passing through
a gate at type-level 3 proceeds to predicate evaluation.

** Relation to Other Work

This is Contribution 1 from =notes/passepartout-whitehead.org=. It is also the
gate-to-fact bootstrap mechanism — every type-level rejection emits a structured
event that Phase 1 ingests as a fact. The ~30 lines implement the seed of the
ontology without any new dependencies.

* Phase 1: Minimum Viable Fact Language (~150 lines — new skill)

** What

An ephemeral, in-memory triple store with provenance tracking and contradiction
detection. No disk persistence. All facts live in a hash table and are discarded
on session end. Gate outcomes are ingested as facts. The gate stack's implicit
ontology is materialized as the seed fact set.

** Rationale

The architecture note's Option 5 (ephemeral facts, no persistence) is the correct
first step. Three reasons:

1. *The fact language is unproven.* Triples with provenance and grounding is a
   hypothesis that must be tested against real memex content before being committed
   to a serialization format.
2. *The ontology is emergent.* Categories are created on first use. A persistent
   format would require a migration story for every category change. Ephemeral
   avoids this — facts are re-derived on each session start using the evolved
   ontology.
3. *Rebuildability is the safety net.* Because all facts have a =:grounding= to
   an Org heading, and gate-outcome facts are regenerated from the gate stack on
   load, the entire symbolic index can be thrown away and rebuilt from scratch.
   The cost is compute, not data.

** Implementation — =org/symbolic-facts.org= → =lisp/symbolic-facts.lisp= (skill)

*** Triple store

A hash table keyed by =(entity relation)=. Values are plists:

#+begin_example
(:value <string-or-symbol>
 :grounding <heading-id-or-nil>
 :provenance <:gate-outcome | :human-authored | :deduced | :llm-proposed>
 :timestamp <universal-time>
 :contradiction <:awaiting-resolution-or-nil>
 :superseded-by <entity-string-or-nil>)
#+end_example

The =:provenance= field tracks how the fact entered the store. The
=:contradiction= field is nil on standard facts. The =:superseded-by= field is
set when a =:temporal= domain fact is replaced by a newer version.

*** Bootstrap from gates

On skill load, scan the Dispatcher's existing data structures and produce triples:

#+begin_example
;; From *dispatcher-protected-paths*
(:entity ".env" :relation :member-of-class :value :secret-config-file :provenance :gate-outcome)
(:entity "*id_rsa*" :relation :member-of-class :value :ssh-key-file :provenance :gate-outcome)

;; From *dispatcher-shell-blocked*
(:entity "rm -rf /" :relation :classified-as :value :catastrophic-command :provenance :gate-outcome)
(:entity "dd if=" :relation :classified-as :value :catastrophic-command :provenance :gate-outcome)

;; From *dispatcher-network-whitelist*
(:entity "api.telegram.org" :relation :classified-as :value :trusted-domain :provenance :gate-outcome)
#+end_example

This produces 50-70 entity classes immediately. No LLM involvement. No human
authoring. Mechanically extracted from existing code.

*** Ingest gate outcomes

Register a post-gate hook on the Dispatcher's rejection path. Every gate rejection
produces a triple with =:provenance :gate-outcome=:

#+begin_example
(:entity "/tmp/secrets.env" :relation :blocked-by :value :dispatcher-path-protection
 :provenance :gate-outcome :grounding "signal-47")
#+end_example

*** Query

=(fact-query &key entity relation value source-provenance)= — pure hash-table
lookup. Returns the matching triple or nil. ~30 lines.

=(fact-query-all &key relation value source-provenance)= — returns all triples
matching the filter criteria. Enables "find all files classified as secrets."

*** Contradiction detection

On every =fact-assert=, check if the new triple contradicts an existing one
(same entity, same relation, different value, same provenance domain). If the
entity's class has =:contradiction-policy :exclusive=, the new fact is rejected
with a signal. If the policy is =:coexistent=, both facts are stored with a
=:contradiction= flag cross-referencing each other. If the policy is =:temporal=,
the old fact is marked =:superseded-by= the new one but retained.

The policy table is a hash table mapping entity classes to one of =:exclusive=,
=:coexistent=, or =:temporal=. Gate-bootstrapped facts default to =:exclusive=
(the filesystem is singular). New categories default to =:coexistent= (safe,
never loses information).

** Verification — ~8 FiveAM tests

1. =test-bootstrap-creates-facts= — bootstrap produces correct triples from
   =*dispatcher-protected-paths*=.
2. =test-bootstrap-creates-shell-facts= — bootstrap produces correct triples from
   =*dispatcher-shell-blocked*=.
3. =test-gate-outcome-produces-fact= — a simulated gate rejection produces a
   triple with =:provenance :gate-outcome=.
4. =test-fact-query-returns-correct-value= — querying by entity and relation
   returns the expected value plist.
5. =test-duplicate-ingestion-idempotent= — asserting the same fact twice does
   not produce a duplicate or a contradiction.
6. =test-exclusive-contradiction-rejected= — asserting a contradictory fact in
   an =:exclusive= domain returns a rejection.
7. =test-coexistent-contradiction-flagged= — asserting a contradictory fact in a
   =:coexistent= domain stores both with cross-referencing flags.
8. =test-temporal-supersedes= — asserting a newer fact in a =:temporal= domain
   marks the old fact as superseded but retains it.

** Relation to Other Work

This is Phase 1 of =notes/passepartout-v3.0.0-roadmap.org=. It implements Options 4 and 5
from the architecture note. The contradiction policies are from
=passepartout-neurosymbolic-design-decisions-and-options.org=.

* Phase 2: Screamer as Admission Gate (~200 lines — new skill)

** What

Wrap Screamer (a constraint solver with non-deterministic backtracking) as a
skill. Use it for consistency checking against the triple store and for deduction
of new facts from existing ones. Screamer is the *verification* layer; VivaceGraph
(introduced in Phase 5) is the *storage* layer.

** Rationale

The architecture note's "verified extraction" pattern requires a deterministic
admission gate. Screamer's non-deterministic backtracking finds contradictions
that simple string comparison misses. For example, if existing facts say "all
config files with extension =.env= are classified as secrets," and the LLM
proposes "=app.env= is not secret," Screamer finds the contradiction by
substituting =app.env= into the existing rule. A naive string-keyed hash table
comparison would miss this because ="app.env"= and =".env"= are different strings.

Screamer also enables deduction — new facts from existing ones without any LLM
involvement. If all files matching =*.env= are secrets, and =prod.env= matches
=*.env=, then =prod.env= is a secret. Deduced facts carry =:provenance :deduced=
and a =:derived-from= chain pointing to the facts they were derived from.

** Implementation — =org/symbolic-screamer.org= → =lisp/symbolic-screamer.lisp= (skill)

*** Wrap Screamer

Screamer is available via Quicklisp. Load at runtime via =ql:quickload :screamer=.
Not an ASDF dependency — if Screamer is not installed, the skill degrades
gracefully (no consistency checking, no deduction — the fact store still
functions as a hash table with provenance tracking).

*** Consistency check

=(screamer-consistent-p candidate-fact existing-facts)= — expresses the fact
store as Screamer constraint variables. The candidate fact is asserted. Screamer
checks solvability. Returns =:consistent=, =:contradiction <details>=, or
=:redundant= (the fact is already implied by existing facts).

Early-stage: the consistency check works on simple triples. As the fact store
grows, rules of the form "all X are Y" (representing protected paths, shell
patterns, class memberships) become Screamer constraints that new facts must
satisfy.

*** Deduction

=(screamer-deduce existing-facts)= — Screamer finds implications of the existing
fact set that are not already in the store. New facts are asserted with
=:provenance :deduced= and a =:derived-from= list of source fact keys.

Deduction is not run on every assertion — it is a background task triggered by
heartbeat or manually. The cost is compute (Screamer exploration), not tokens.

*** Admission gate

=(screamer-admit candidate-fact existing-facts)= — wraps consistency check with
the contradiction policy lookup. If the candidate fact's entity class has policy
=:exclusive=, contradictions reject. If =:coexistent=, flag. If =:temporal=,
supersede.

This is the function the archivist calls before any LLM-proposed fact enters the
store. It is also called on human-authored facts (which override the policy —
the human can assert contradictory facts in any domain). It is not called on
gate-outcome facts (gates are the ground truth for security domains).

** Verification — ~6 FiveAM tests

1. =test-screamer-consistency-passes= — a fact consistent with existing triples
   returns =:consistent=.
2. =test-screamer-contradiction-detected= — "app.env is not secret" contradicts
   "all *.env files are secrets" and returns =:contradiction=.
3. =test-screamer-redundant-detected= — asserting a fact already implied by
   existing facts returns =:redundant=.
4. =test-screamer-deduction-produces-new-fact= — given "all *.env files are
   secrets" and "prod.env matches *.env", Screamer deduces "prod.env is secret."
5. =test-admission-gate-rejects-contradiction= — the archivist's proposal that
   contradicts an =:exclusive= domain fact is rejected.
6. =test-admission-gate-flags-coexistent-contradiction= — the archivist's proposal
   that contradicts a =:coexistent= domain fact is stored with a cross-reference.

** Relation to Other Work

This is Phase 2 of =notes/passepartout-v3.0.0-roadmap.org=. It implements the "LLM as proposer"
pattern from the architecture note. Screamer's role is defined in
=passepartout-neurosymbolic-design-decisions-and-options.org=.

* Phase 3: Archivist as Fact Proposer (~100 lines — extends existing archivist)

** What

Extend the existing archivist skill (=org/symbolic-archivist.org=) with a fact
extraction mode. The LLM reads prose, proposes triples, and Screamer verifies
them before admission. The archivist's existing Scribe (log distillation) and
Gardener (link scanning) functions are unchanged.

** Rationale

The archivist already walks the entire memex (the Gardener scans for broken links
and orphans). Adding fact extraction reuses the same traversal infrastructure
rather than duplicating it. The extraction is gated by Screamer — the LLM is a
proposer, not an extractor. Facts that fail consistency checking are discarded.
Facts that pass are admitted with =:provenance :llm-proposed= and =:grounding=
to the source heading.

** Implementation — extends =org/symbolic-archivist.org=

*** Propose from prose

Given an Org heading, call the LLM with a minimal prompt (~200 tokens):

#+begin_example
Extract triples from this text as (:entity <name> :relation <keyword> :value <value>).
Ground each triple to the heading. Return a list of triples.
#+end_example

The LLM returns structured triples via the existing JSON→plist structured output
path from v0.4.2. The prompt is environment-aware: if the heading's file is in
=literature/= or has =:literature:= tags, the prompt includes literature-specific
relations (=:wrote=, =:published-in=, =:influenced=). If the heading is in
=projects/=, the prompt includes coding-specific relations (=:depends-on=,
=:tested-by=).

*** Verify through Screamer

Each proposed triple runs through =(screamer-admit candidate existing-facts)=
from Phase 2. Consistent and coexistent-flagged triples are admitted. Contradictory
triples in =:exclusive= domains are discarded with a log entry.

*** Provenance tracking

After each extraction run, update provenance counts:

#+begin_example
(:total-facts 847
 :gate-outcome 312
 :human-authored 12
 :deduced 89
 :llm-proposed 434)
#+end_example

This is the data structure that Phase 4's sufficiency criterion reads. It is
also surfaced in the TUI sidebar or =/status= command: "Symbolic index: 847
facts (37% from gates, 52% LLM-proposed, 10% deduced, 1% human)."

*** Rebuildable

Because every fact has a =:grounding= to an Org heading, the entire LLM-extracted
subset can be discarded and re-extracted without losing gate-outcome or deduced
facts. The =(fact-purge :provenance :llm-proposed)= function removes all
LLM-proposed facts. A subsequent =(archivist-extract-all)= re-extracts from
scratch.

This is the safety net: if the LLM produces a bad extraction that passes
Screamer's consistency check (possible in the early stages when the fact store
has few existing facts to check against), the extraction can be redone after the
fact store has grown. The cost is compute, not data.

** Verification — ~5 FiveAM tests

1. =test-archivist-extracts-triples= — given a known Org heading with explicit
   triples in the prose, the archivist produces the correct triples via LLM.
2. =test-archivist-verified-extraction= — a hallucinated triple is rejected by
   the Screamer admission gate.
3. =test-provenance-counts-update= — after extraction, the provenance breakdown
   is correct.
4. =test-purge-llm-facts= — does not delete gate-outcome or deduced facts.
5. =test-re-extraction-idempotent= — re-extracting from the same prose after
   purging produces the same facts (Screamer verification is deterministic
   given the same starting set).

** Relation to Other Work

This is Phase 3 of =notes/passepartout-v3.0.0-roadmap.org=. The archivist's role as proposer
is described in =passepartout-neurosymbolic-design-decisions-and-options.org=
under "The LLM as Proposer."

* Phase 4: The "Flip" — Sufficiency Criterion (~50 lines — extends Phase 3)

** What

Make the architecture note's central narrative arc operational: a measurable
threshold for when the symbolic engine has enough non-lossy facts to bypass the
LLM for extraction.

** Rationale

The architecture note describes "at some point, the non-lossy facts constitute a
sufficient foundation that the symbolic engine can reverse the flow" but provides
no criterion for "some point." The sufficiency score makes the flip computable
and visible to the user.

** Implementation — extends =org/symbolic-facts.lisp=

*** Sufficiency score

=(fact-sufficiency-ratio)= — returns the ratio of non-lossy facts to total facts:

#+begin_src lisp
(/ (+ (count-provenance :gate-outcome)
      (count-provenance :human-authored)
      (count-provenance :deduced))
   (fact-total-count))
#+end_src

When this ratio exceeds =SUFFICIENCY_THRESHOLD= (configurable env var, default
0.7), the system considers its foundation sufficient. The threshold defaults to
0.7 because below this, the majority of facts are LLM-proposed and therefore
uncertain. Above 0.7, the proven foundation provides enough constraint that
Screamer can reliably detect incorrect LLM proposals.

*** Auto-extraction toggle

When sufficiency is reached, the archivist switches from "LLM proposes, Screamer
verifies" to "Screamer queries existing facts, applies category rules to the new
prose, and deduces new facts directly." The LLM is bypassed for categories that
have sufficient non-lossy coverage. The LLM is still used for novel categories
that have no existing facts.

The switch is configurable: =AUTO_EXTRACTION_ENABLED=true/false=. When disabled,
the system continues with LLM proposals regardless of sufficiency — useful for
domains where extraction quality is prioritized over extraction determinism.

*** Monitor

The TUI sidebar (v0.8.0) or =/status= command displays:

#+begin_example
Symbolic Index
  Total facts:    1,247
  Proven:
    Gate outcomes:     312  (25%)
    Human-authored:     47   (4%)
    Deduced:           521  (42%)
    ─────────────────────────
    Non-lossy:         880  (71%)
  LLM-proposed:        367  (29%)
  ─────────────────────────
  Sufficiency: 71% ✓  (threshold: 70%)
  Mode: AUTO-EXTRACTION (LLM bypassed for known categories)
#+end_example

** Verification — ~3 FiveAM tests

1. =test-sufficiency-below-threshold= — with 30% non-lossy facts, auto-extraction
   is not enabled.
2. =test-sufficiency-above-threshold= — with 75% non-lossy facts, auto-extraction
   is enabled.
3. =test-auto-extraction-produces-same-facts-as-llm-extraction= — for a category
   with sufficient non-lossy coverage, auto-extraction produces facts that a
   subsequent LLM extraction also produces (the deterministic path is consistent
   with the probabilistic path).

** Relation to Other Work

This is Phase 4 of =notes/passepartout-v3.0.0-roadmap.org=. The flip concept originates in
=notes/passepartout-symbolic-engine-exploration.org= (lines 68-76) and is refined in
=passepartout-neurosymbolic-design-decisions-and-options.org= under "The Flip."

* Phase 5: VivaceGraph as Persistent Store (~300 lines — new skill)

** What

Replace the ephemeral hash-table triple store with VivaceGraph, a Lisp-native
graph database with Prolog-like queries. Add the KG type hierarchy (PM type
levels applied to the knowledge layer). Define the persistence format from the
fact language that survived Phases 1-4.

** Rationale

By this point, the triple fact language has been battle-tested through four
phases of gate outcomes, Screamer deductions, LLM proposals, and cross-domain
comparisons. The facts that proved useful define the persistent schema. The ones
that weren't are left behind. The serialization format is not designed upfront;
it emerges from use.

The transition from ephemeral to persistent is justified when two conditions are
met: (1) the fact language has stabilized (categories are being queried, not
constantly refactored), and (2) accumulated deductions across sessions provide
value that justifies the serialization cost.

** Implementation — =org/symbolic-vivacegraph.org= → =lisp/symbolic-vivacegraph.lisp= (skill)

*** Wrap VivaceGraph

VivaceGraph is available via Quicklisp. Load at runtime. Not an ASDF dependency.
If not installed, the fact store continues as a hash table (Phase 1-4 behavior)
with a log warning: "VivaceGraph not available — persistence disabled."

*** Prolog-like queries

Replace =fact-query= with graph traversals:

#+begin_src lisp
;; Find all files classified as secrets
(vivace-query '(:and (:entity ?e)
                     (:member-of-class ?e :secret-file)))

;; Find all files classified as secrets that were modified today
(vivace-query '(:and (:entity ?e)
                     (:member-of-class ?e :secret-file)
                     (:modified-since ?e ,(today-timestamp))))

;; Find contradictions between Wikidata and the memex
(vivace-query '(:and (:entity ?e)
                     (:has-value ?e ?v1 :source :wikidata)
                     (:has-value ?e ?v2 :source :memex)
                     (:not-equal ?v1 ?v2)))
#+end_src

*** KG type hierarchy (Contribution 4 from Whitehead)

Every entity in the graph carries =:pm-type-level= metadata. Queries cannot
return entities whose type level equals or exceeds the querying function's type
level. A fact-finding query at type-level 2 cannot return facts at type-level
3 or higher. Self-referential knowledge — "this fact defines its own type" —
becomes structurally impossible because the type level is assigned at creation
and cannot be modified by a fact of the same or higher level.

This is Contribution 1 (type-level gates) applied to the knowledge layer rather
than the execution layer. The dispatcher prevents self-referential /actions/; the
KG prevents self-referential /facts/.

*** Persistence format

The fact language that survived Phases 1-4 defines the format. Each entity is a
node; each triple is an edge with properties (=:grounding=, =:provenance=,
=:timestamp=). The format is not a new design — it is the triple schema evolved
through use, serialized by VivaceGraph's native persistence.

If the fact language later evolves to n-ary relations, VivaceGraph's graph model
accommodates this natively — edges can carry arbitrary property plists. The
triple form is a special case of the general graph model.

*** Load on startup, save on interval

On daemon start, =(vivacegraph-load)= reads the last saved graph. On heartbeat,
=(vivacegraph-save)= persists the graph in its native format to
=~/.cache/passepartout/facts.vg~. The interval matches the existing
=*memory-auto-save-interval*=. The save is atomic: write to a temp file, rename
on success. Corruption-safe.

** Verification — ~5 FiveAM tests

1. =test-vivacegraph-roundtrip= — save and load preserves all facts with
   provenance metadata.
2. =test-prolog-query-returns-results= — a query for all secret files returns
   the bootstrapped gate facts.
3. =test-prolog-query-cross-domain= — a query for contradictions between Wikidata
   and memex provenance returns correct results.
4. =test-type-level-prevents-self-reference= — a query from a type-level-2
   function cannot return type-level-3 facts.
5. =test-fact-store-fallback-without-vivacegraph= — when VivaceGraph is not
   loaded, the hash-table fallback functions identically to Phase 1-4 behavior.

** Relation to Other Work

This is Phase 5 of =notes/passepartout-v3.0.0-roadmap.org= and Contribution 4 from
=notes/passepartout-whitehead.org=. The architecture note's Option 1
(auto-formalizer KG) converges with Option 4 (one memex, two indices) here —
VivaceGraph is the persistence layer for the symbolic index within the
one-memex-two-indices architecture.

* Phase 6: ACL2 for Structural Verification (~200 lines — new skill)

** What

Wrap ACL2 as a skill. Prove structural properties of the KG type hierarchy and
rule sets. Not for empirical claims.

** Rationale

The architecture note positions ACL2 as verifying LLM-proposed facts. But many
facts are empirical ("this command is destructive on Linux"), not logical. The
Whitehead note clarifies the right role: structural verification. ACL2 proves
that the type hierarchy has no cycles, that the rule set is non-contradictory,
and that the gate-to-fact bootstrap preserves the Dispatcher's intent. These are
structural properties that can be formally verified, not empirical claims that
depend on external reality.

** Implementation — =org/symbolic-acl2.org= → =lisp/symbolic-acl2.lisp= (skill)

*** Type consistency proofs

=(acl2-verify-type-hierarchy facts)= — prove that the KG type hierarchy has no
cycles: no entity of type-level 3 depends on an entity of type-level 5, no parent
category has a child that subsumes it, no category is its own ancestor via the
child-of relation. These are structural properties of the graph, independent of
what the facts /say/.

*** Rule set consistency

=(acl2-verify-rule-consistency rules)= — prove that the accumulated Dispatcher
rules (from HITL approvals) are non-contradictory: no rule allows a command that
another rule blocks, no rule permits a path access that another denies. If the
rule set is contradictory, ACL2 identifies the contradictory subset with the
provenance of each rule. The human resolves the contradiction.

*** Extraction verification

=(acl2-verify-bootstrap-preservation)= — prove that the gate-to-fact bootstrap
(Phase 0-1) preserves the Dispatcher's intent: every blocked pattern in the gate
stack maps to a fact in the store; every fact with =:provenance :gate-outcome= is
grounded in a specific gate vector; no gate-bootstrapped fact contradicts another
gate-bootstrapped fact.

** Not in scope

ACL2 does not verify that =rm -rf / is destructive. That is an empirical claim
about Linux. Screamer handles empirical consistency (does this new claim
contradict existing observations?). ACL2 handles structural consistency (does
this reasoning structure have formal flaws?). The boundary is: empirical claims
go to Screamer; structural claims go to ACL2.

** Verification — ~4 FiveAM tests

1. =test-acl2-type-hierarchy-no-cycles= — a synthetic KG with a type-level cycle
   is detected and reported.
2. =test-acl2-rule-set-contradiction-detected= — two Dispatcher rules that
   contradict each other produce a contradiction report with provenance.
3. =test-acl2-bootstrap-preservation= — the bootstrap extraction from the gate
   stack is verified to have no missing or extra facts.
4. =test-acl2-not-loaded-graceful-degradation= — when ACL2 is not installed, the
   skill loads but returns ":ACL2 not available — structural verification
   disabled" without crashing.

** Relation to Other Work

This is Phase 6 of =notes/passepartout-v3.0.0-roadmap.org=. ACL2's role is refined in
=passepartout-neurosymbolic-design-decisions-and-options.org= from the
architecture note's broader claim to the structural verification scope.

* Phase 7: The 10-80-10 Planner (~500 lines — new skills, last phase)

** What

A planning engine built on the mature symbolic index. Screamer expresses task
planning as a constraint satisfaction problem. ACL2 verifies plans for structural
soundness. The LLM handles the I/O boundaries (natural language → structured goal
← natural language response). The symbolic engine handles the reasoning.

** Rationale

This is v3.0.0 as described in the architecture note and the ROADMAP. It is the
final phase because it requires a populated, queried, and trusted symbolic index.
The full planner is useless without a mature ontology and a proven deducer. By
the time Phase 7 begins, Phases 0-6 have accumulated months of gate outcomes,
Screamer deductions, verified LLM proposals, and human-authored facts. The
symbolic index has achieved sufficiency. The ontology has stabilized through use.
The planner is built on a foundation, not a speculation.

** Implementation — =org/symbolic-planner.org= → =lisp/symbolic-planner.lisp= (skill)

*** Task decomposition as constraint satisfaction

The user specifies a goal: "refactor the authentication module to support OAuth2."
The LLM translates this to a structured goal plist. Screamer expresses the planning
problem:

- /Variables/: subtasks (write OAuth2 client, add token store, update auth
  middleware, write tests, update documentation)
- /Constraints/: dependency ordering (tests depend on implementation), resource
  limits (one file write at a time), safety invariants (no modification of
  =core-*= files)
- /Objective/: find an ordering that satisfies all constraints

Screamer returns a viable plan or reports unsolvability with the conflicting
constraints.

*** Plan verification

ACL2 proves that the plan contains no deadlocks (two subtasks waiting on each
other), no dependency cycles (A depends on B depends on C depends on A), and
no safety violations (no plan step requires a gate-blocked operation).

If verification fails, ACL2 identifies the failing subtask and the violated
constraint. The planner re-decomposes the problematic branch (the existing
ROADMAP's branch pruning, v0.11.0, but symbolically rather than neurally).

*** Neuro-symbolic boundary

The LLM handles the I/O boundaries:

- *Input* (10%): natural language → structured goal plist. "Refactor auth for
  OAuth2" → =(:goal :refactor-component :target :auth-module :add-feature :oauth2)=.
  Small prompt, formulaic translation, ~100 tokens.
- *Reasoning* (80%): Screamer plans. ACL2 verifies. VivaceGraph provides the
  facts about file structure, dependencies, and gate constraints. Zero LLM
  tokens.
- *Output* (10%): structured plan → natural language response. The verified plan
  plist is formatted as "I'll refactor the authentication module in 5 steps:
  1) Create the OAuth2 client (depends on: nothing, modifies: auth/client.lisp)
  2) Add the token store..." Small prompt, formulaic translation, ~150 tokens.

*** TUI visualization

The plan is rendered as an Org headline tree in the TUI, with each subtask as a
node showing its terminal state (=todo=, =next-action=, =in-progress=, =done=,
=blocked=, =stuck=), its constraints, and its verified properties. This is the
same task tree visualization planned for v0.11.0 in the feature roadmap, but
with the addition of Screamer constraint annotations and ACL2 verification
badges.

** Verification — ~6 FiveAM tests

1. =test-goal-plist-from-natural-language= — natural language input produces
   correct structured goal plist (LLM-dependent but formulaic; tested with
   deterministic mock).
2. =test-screamer-plan-satisfies-constraints= — Screamer produces a plan that
   satisfies all specified dependencies and safety constraints.
3. =test-screamer-report-unsolvable= — Screamer reports unsolvability when
   constraints are contradictory.
4. =test-acl2-verifies-plan-no-cycles= — ACL2 verifies a valid plan has no
   dependency cycles.
5. =test-acl2-rejects-cyclic-plan= — ACL2 detects a dependency cycle in an
   invalid plan.
6. =test-plan-to-natural-language= — structured plan plist produces readable
   natural language output.

** Relation to Other Work

This is Phase 7 of =notes/passepartout-v3.0.0-roadmap.org=. It corresponds to the ROADMAP's
v0.9.0 (task planning) and v3.0.0 (full 10-80-10 architecture). It is the last
component because it depends on a mature symbolic index from Phases 0-6.

* Phase 8+: Semantic Wikipedia Integration (TBD lines — optional acceleration)

** What

Load Wikidata entities referenced in the memex into the symbolic index. Every
entity the user's prose mentions gets its Wikidata property graph — type hierarchy,
relations, dates, citations — as triples with =:provenance :wikidata=.

** Rationale

The gate stack provides 50-70 entity classes — adequate for a coding agent.
For a general-knowledge memex containing literature, philosophy, history,
science, and daily life, 50-70 is starvation. Organic growth through prose
extraction (Phase 3) would take years to cover the entities mentioned in a single
reading of /Pale Fire/. Wikidata has already done this work at scale.

The LLM's role in extraction shrinks dramatically. Without Wikidata, the archivist
must /discover/ that Nabokov wrote /Pale Fire/, lectured on Kafka, and emigrated
from Russia — extracting each triple from prose. With Wikidata, the Nabokov entity
is pre-structured. The archivist's job changes from "discover entities" to
"connect your heading to the existing entity."

** Implementation sketch

1. *Index referenced entities.* Scan memex prose for entity names (capitalized
   noun phrases, names in Org links, headings in =literature/= directories). For
   each, attempt Wikidata entity resolution (string match, disambiguation via
   context).

2. *Load N-hop property net.* For each resolved entity, load its Wikidata
   properties: instance-of, subclass-of, authored, published-in, influenced-by,
   birth-date, death-date, etc. Load the same for entities directly connected
   to it (1-hop neighbors). Optionally expand to 2-hop for deeply connected
   domains.

3. *Admit with co-existent policy.* Wikidata facts are admitted with
   =:provenance :wikidata= and contradiction policy =:coexistent=. They do not
   override your memex's facts. They sit alongside them. Contradictions are
   surfaced, not resolved.

4. *Cross-domain query.* "What does my memex say about Nabokov that Wikidata
   doesn't?" "Where does my memex disagree with Wikidata?" "What entities in my
   memex have no Wikidata counterpart?" These queries are pure VivaceGraph
   traversals — zero LLM tokens.

** Not a Phase 0 prerequisite

Semantic Wikipedia integration is an accelerator, not a prerequisite. Phases
0-7 work without it — the ontology grows through gate outcomes, Screamer
deductions, LLM proposals, and human authoring. Wikidata compresses the timeline
for the broad domain but does not change the architecture. The admission gate
(Screamer), contradiction policies, provenance tracking, and neuro-symbolic
boundary are identical with or without it.

** Open question

How much Wikidata is the right amount? Loading entities referenced in the memex
is the minimum. Loading all entities within N hops of those references expands
the graph exponentially. The right N depends on the memex's breadth and the user's
query patterns. A memex focused entirely on software engineering may need only 1
hop. A memex spanning literature, history, philosophy, and science may need 3-4
hops. The query performance and memory costs of a large Wikidata load have not
been estimated.

* Summary: Lines and Dependencies

| Phase | Component               | Lines | New Skill? | Depends On      | Earliest Release |
|-------+-------------------------+-------+------------+-----------------+------------------|
| 0     | PM-type-level gates     | ~30   | No         | Dispatcher      | Immediately      |
| 1     | Triple fact store       | ~150  | Yes        | Phase 0         | v0.7.2+          |
| 2     | Screamer admission      | ~200  | Yes        | Phase 1         | v0.7.2+          |
| 3     | Archivist extraction    | ~100  | Extends    | Phase 2         | v0.8.0+          |
| 4     | Flip — sufficiency      | ~50   | Extends    | Phase 3         | v0.8.0+          |
| 5     | VivaceGraph store       | ~300  | Yes        | Phase 4         | v0.10.0+         |
| 6     | ACL2 verification        | ~200  | Yes        | Phase 5         | v0.12.0+         |
| 7     | 10-80-10 planner         | ~500  | Yes        | Phase 6         | v3.0.0           |
| 8+    | Semantic Wikipedia      | TBD   | Yes        | Phase 5         | TBD              |
|-------+-------------------------+-------+------------+-----------------+------------------|
| Total |                         | ~1530 |            |                 |                  |

This roadmap is independent of the feature roadmap in
=passepartout/docs/ROADMAP.org=. Phase 0 ships alongside any v0.7.x patch. The
symbolic engine grows in parallel with feature work (TUI improvements, MCP tools,
gateway expansion, etc.), not after it. The feature roadmap describes /what/ the
agent can do; this roadmap describes /how/ it knows what it knows.

The total new code across all phases is approximately 1,530 lines. Relative to
the existing codebase (~8,000+ lines across 40+ Org source files and 30+ skills),
the symbolic engine is a ~20% addition. Relative to the ROADMAP's planned feature
work through v0.13.0 (thousands of lines of TUI rendering, MCP protocol
implementation, skin engine, planning, etc.), the symbolic engine is a small,
orthogonal thread that grows the architecture's reasoning depth while the feature
work grows its interaction breadth.

* Competitive Advantage Analysis

** Phase 0-1: Deterministic safety, now with type-level guarantees

The existing Dispatcher gate stack already provides 0-LLM-token safety verification.
Phase 0 adds structural guarantees: no heuristic bypassing of the type hierarchy.
A request to modify the dispatcher's own rules is impossible by construction, not
just caught by pattern matching. No competitor has this — their equivalent of
"core file protection" is a prompt instruction, not a type system.

** Phase 2-3: Verified extraction — the symbolic index grows without corruption

No competitor verifies extracted facts against an existing knowledge base. Their
memory systems (Claude Code's ~extractMemories~, Hermes's MemoryProvider, OpenClaw's
session transcripts) record what the LLM /said/ happened, not what the system
/proved/ happened. Passepartout's Screamer-gated admission makes the symbolic index
a monotonic, verified structure. Facts are admitted because they are consistent,
not because the LLM generated them.

** Phase 4-5: Self-accelerating knowledge — the downward cost curve

The sufficiency criterion makes Passepartout's "cheaper over time" thesis
measurable. As the ratio of non-lossy facts grows, LLM calls for extraction
decrease. At sufficiency, extraction of known categories becomes deterministic.
The downward cost curve is not a marketing claim — it is a structural property
of the architecture, visible through the sufficiency score.

** Phase 6-7: Provable plan soundness

No competitor verifies task plans against formal constraints. Claude Code plans
in a single LLM call with no post-hoc verification. Hermes decomposes tasks into
subtasks but does not prove them non-contradictory. Passepartout's ACL2-verified
plans are structurally guaranteed to have no deadlocks, no dependency cycles,
and no safety violations. The verification is a proof, not a prompt.

** Semantic Wikipedia: Entity coverage at zero marginal cost

No competitor has a general-knowledge entity graph because no competitor has a
symbolic engine to populate. Claude Code knows codebases; it doesn't know that
Nabokov wrote /Pale Fire/ and lectured on Kafka. Passepartout with Wikidata
loaded knows both, and the entity knowledge costs zero LLM tokens — it is loaded
once as structured data and queried via VivaceGraph traversals.

** The permanent competitive advantage

The competitive advantage is not any single feature. It is the architecture's
ability to accumulate verified knowledge from four independent sources (gates,
deduction, verified LLM proposals, human authoring) and to make that knowledge
queryable with provenance. Competitors accumulate chat transcripts. Passepartout
accumulates a provenanced, self-verifying knowledge graph. Transcripts become
stale and unreliable. The knowledge graph becomes richer and more trustworthy
with every session.

* What Is NOT Built

1. *A separate knowledge graph serialization format before the ephemeral phase
   proves what facts are useful.* Premature format commitment is the ontology
   problem writ small. Let use determine the format.

2. *ACL2 verification of empirical claims.* Apple is red. rm -rf / is destructive.
   These are observations, not theorems. Screamer handles empirical consistency.
   ACL2 handles structural verification.

3. *VivaceGraph before Screamer.* The admission gate is the critical path. The
   persistence layer is an optimization of a working system.

4. *A per-fact ontology designed upfront.* Extract from the gate stack, extend
   from deductions and observations, prune through contradiction detection. The
   ontology is a garden, not a building.

5. *New core ASDF components.* Every phase is a skill. A corrupted symbolic
   engine degrades reasoning but does not kill the agent. Satisfies the
   self-repair criterion.

6. *A "complete" symbolic index for the broad domain.* The neural index is the
   permanent gateway to the richness of prose. The symbolic index handles what
   can be mechanically verified. The boundary is permanent, not transitional.
   The neuro is the brain. The symbolic is the education.

* Relation to the Feature Roadmap

The feature roadmap (=passepartout/docs/ROADMAP.org=) describes Passepartout's
evolution through v0.13.0: TUI improvements, MCP-native tools, task planning,
skill creation, evaluation harnesses, voice gateways, themes, and channels.
These are /interaction surface/ features — they expand what the agent can do.

This roadmap describes the /reasoning substrate/ — it deepens how the agent
knows what it knows. It is independent of the feature sequence. Phase 0 can ship
alongside any v0.7.x patch. Phases 1-4 ship during the v0.8.x-v0.10.x feature
cycle. Phases 5-7 ship during the v0.11.x-v0.13.x cycle.

The two roadmaps converge at v3.0.0: the feature roadmap provides the interaction
surface (a polished TUI, a rich tool ecosystem, a multi-gateway communication
layer); this roadmap provides the reasoning depth (a provenanced knowledge graph,
a deterministic constraint solver, a verified planning engine). The surface
without the substrate is a chat agent with good UX. The substrate without the
surface is a theorem prover without a user. Together, they are the v3.0.0
architecture.

See also:

- =notes/passepartout-neurosymbolic-design-decisions-and-options.org= — the
  design rationale for every decision in this roadmap
- =notes/passepartout-symbolic-engine-exploration.org= — the original architecture
  exploration and five architecture options
- =notes/passepartout-whitehead.org= — Whitehead's four concrete contributions
- =passepartout/docs/ROADMAP.org= — the feature roadmap through v0.13.0
- =passepartout/docs/ARCHITECTURE.org= — the current pipeline architecture
- =notes/passepartout-v3.0.0-roadmap.org= — the original concrete plan (superseded by this
  document)