Initial v3 spec + plan for the major nagent review update. Covers 24 new nagent commits + 2 case-study repos (pep-copt, differentiable-collisions-optc) across 11 clusters. v2.3 historical reviews preserved; v3 is the canonical going forward.
v2.3 (nagent_review_v2_3_20260612.md, 271703 bytes / 3965 lines) is the
FULL REWRITE of the latest nagent corpus. Per user instruction:
- 'I want a full rewrite via a v2.3 I guess'
- 'don't ref v1 ref v2 related I want his latest corpus not something
outdated mixed in with my intent-based report mixed in'
- 'I want LONG REPORTS. make v2.3 the longest'
- 'You actually trucated info with 2.3. 2.1 had the breadth. you
should make 2.3 have both 2.1 breadth and 2.2 terse DSL stuff'
Stand-alone (no references to v1/v2/v2.1/v2.2 or the intent_dsl_survey).
Pure nagent corpus focus.
Length: 271703 bytes (longer than v2 at 68KB, v2.1 at 59KB, v2.2 at
35KB). Combined v2.1's breadth with v2.2's terse DSL style + full
source-line citations + new content the prior reviews did not have.
Structure (13 sections):
- §0 TL;DR (terse table)
- §1 The latest nagent corpus (the 8 commits; the 33-file tree; the
new 7-Part + 14-section README structure)
- §2 The 14 patterns in depth (one per pattern, with file:line refs)
- §3 The 12 new big additions (knowledge harvest, cache, compaction,
project context, claude-code, shared DOD, CLAUDE.md, per-file notes,
'delete to turn off', graceful save, delegation reframing)
- §4 The harvest pattern in detail (the new big one; full pipeline,
data shapes, codepath, retry budget, test surface, Manual Slop
implementation outline)
- §5 The cache strategy in detail (block order table, cache boundary
computation, Anthropic cache_control, the GUI exposure gap with
ASCII sketch)
- §6 The compaction pattern in detail (the 12-section structure, the
10-question self-review, the codepath, the Manual Slop prompt)
- §7 nagent architecture (4 reading levels + tag protocol + state
model + write boundaries + large-file pipeline)
- §8 The vocabulary patterns (8 tags + per-tag guidance + 4-tier
structure + cross-MCP mapping)
- §9 File splits, patches, summaries (4-stage pipeline + 12 languages
+ O(n) fix + cascade)
- §10 16 future-track candidates (full specifications + priority +
effort + dependencies + sequencing)
- §11 14 proposed new artifacts (canonical DOD + AGENTS.md + 5
styleguides + 3 project docs + 4 workflow updates; format commitment)
- §12 Recommended next steps (the action plan: foundation -> styleguides
-> project docs -> workflow updates; then the HIGH-priority candidates)
- §13 References (nagent source + Manual Slop source + docs + external;
the file:line citation index)
Format commitment applied throughout:
- 7-column tables (Symbol, Name, Signature, Semantics, Example, Source,
Shape) where applicable
- No JSON code blocks (JSON becomes tables or line-based arrays)
- SSDL shape tags: [I], ===>, o==>, ===>W===>, ===>M===>, ===>B===>, [B],
[M], [N], [Q], [S], [T], ───
- Forth/array notation in code examples (a b + for postfix math;
name := value for assignment; if cond { body } for control flow)
- File:line citations into both nagent source and Manual Slop source
- ASCII sketches for GUI panels (per docs/reports/ascii_sketch_ux_workflow
convention: [+/-], [Role: AI v], |text|, <click to expand>,
in:N out:N cache:N, @YYYY-MM-DDTHH:MM:SS)
v2, v2.1, v2.2 are preserved (per repeated user instructions).
Readme.md and docs/Readme.md stay human-facing. v1 review artifacts
preserved.
v2.2 (nagent_review_v2_2_20260612.md, ~35KB) is a focused delta, not a full
rewrite. Two user inputs drove it:
1. The user published intent_dsl_survey_20260612/report_v1.2.md (1367 lines,
10 prior-art clusters, 4 anchor claims, ~42-verb vocab, 10 AI-Agent
Properties in §6). The survey's §6 Claims 4 and 5 explicitly cite
nagent_review_v2_1 §2.1 and §2.2 as the source for the 4 memory
dimensions and stable-to-volatile cache ordering — so the v2.1 patterns
are now formally codified by the survey.
2. The user said: 'I don't really like JSON, I like table based formats
more, or things that are forth/array-like.'
v2.2 applies the data-format preferences:
- JSON block in v2.1 §2.1 (harvest output schema) replaced with a §4.4
7-column table (Symbol, Name, Signature, Semantics, Example,
Borrowed from, Shape)
- Comparison table (§5) reformatted with SSDL shape tags
- Future-track candidate list (§6) reformatted as a single 16-row table
with all metadata columns
- Proposed new artifacts (§8) in table form
v2.2 adopts survey grammar primitives (name := value, for x .. n,
if cond { ... }, tape { ... }, try { ... } recover err { ... },
sandbox { ... }, audit msg, fuzzy { ... }) where applicable.
v2.2 adds:
- Candidate 12b (cache TTL GUI controls) - the v2.1 sub-candidate
- Candidate 16 (AGENTS.md @import + canonical DOD file) - HIGH priority,
the foundation for all the other styleguides
- New §11 'In dialogue with intent DSL survey' - the 9 mutual cross-refs
v2 and v2.1 are preserved (per user instruction). All v1 artifacts and
the human Readme files are preserved. Format commitment for the
next-turn artifacts: all new styleguides and project docs will follow
the §4.4 table format.
- v2 (nagent_review_v2_20260612.md, ~68KB): first delta report on the 8 new
nagent commits between 2026-06-08 and 2026-06-12. Introduces 5 new
future-track candidates (11-15): knowledge harvest, stable-to-volatile
context ordering for caching, conversation compaction, project context
files, save-with-graceful-summary-failure. Notes heavy RAG emphasis as
the comparison frame for knowledge harvest (later corrected in v2.1).
- v2.1 (nagent_review_v2_1_20260612.md, ~59KB): user-driven revision of v2.
Five corrections applied:
1. CLAUDE.md -> AGENTS.md swap (Manual Slop has AGENTS.md, not CLAUDE.md)
2. Reframed Candidate 11 from 'RAG alternative' to 'third memory
dimension' (curation + discussion + RAG + knowledge)
3. Cache TTL GUI controls added (sub-candidate 12b) per user request
4. RAG integration discipline added (new sub-section 2.10) per user's
'be conservative' rule
5. v2 preserved as draft; v2.1 is non-destructive new file
v2.1 also proposes new agent-facing artifacts (canonical DOD file,
AGENTS.md update, new ./docs/AGENTS.md) and 8 new styleguides/docs.
v2.1 source-citations grounded in 18 nagent source files read in full.
- state.toml and metadata.json updated with v2.1 tasks and a v2.1_review
block; v1 artifacts preserved per original user instruction.
Pending: style preferences (table-based, forth/array-like, not JSON) and
the user's upcoming intent-based-scripting-languages report.
Reference/analysis track. Produces 0 code changes.
Artifacts (conductor/tracks/nagent_review_20260608/):
- spec.md (240 lines) - track wrapper with Application/Meta-Tooling framing
- report.md (571 lines) - 14-section deep-dive; primary deliverable
- comparison_table.md (79 lines) - flat side-by-side reference
- decisions.md (286 lines) - 10 future-track candidates with priority matrix
- nagent_takeaways_20260608.md (363 lines) - 10 actionable patterns grounded
in code (file:line refs into nagent source and Manual Slop source)
- metadata.json (132 lines) - structured metadata + verification criteria
- state.toml (113 lines) - per-task tracking + user-corrections log (7 entries)
14 nagent principles covered in report.md (durable work, text-in/text-out,
editable state, visible protocol, the loop, per-file memory, repo history,
neighborhoods, sub-conversations, controlled writes, large files, tool
discovery, framework differences, build your own).
6 pitfalls (revised from 8 after user-corrections):
1. No structured output protocol in Application AI (opaque function calling)
2. Provider-specific history in process globals (ai_client._anthropic_history
+ _deepseek_history + _minimax_history)
3. RAG is not 'history as data' (fuzzy, not auditable)
4. AI client is a stateful singleton (2,685-line ai_client.py)
5. No non-MMA disposable sub-conversations (1:1 gap; user-flagged want)
6. Hard-coded tool discovery (45-tool if/elif in mcp_client.py)
User-corrections applied (3 rounds, 7 total corrections recorded):
- Editable discussions: PARTIAL -> PARITY (DIFFERENT FOCUS) with full A1-A7
per-entry + B1-B11 discussion-level + C1-C5 undo/redo operation matrix
- Per-file memory: DOMAIN MISMATCH -> MANUAL SLOP IS STRONGER IN
CURATION DIMENSION (FileItem + ContextPreset vs nagent's inode-keyed
conversation log; complementary, not equivalent)
- Sub-conversations: MMA has it; 1:1 does not -> 'PARITY for MMA; GAP for
1:1 discussions' (user wants this)
- RAG: opt-in, not gap; user wants pre-staging via sub-conversation
- Personas: config bundling (can opt out via AI settings)
- Tool discovery: deferred (user has 'intent based DSL' idea but 'no where
near that ideation yet')
10 actionable takeaways (separate from the 6 pitfalls - those are
diagnosis, these are prescription):
1. State visibility (UI inspector for in-process state)
2. Readable conversation log (text-greppable, not just JSON-L)
3. Sub-agents for 1:1 (HIGH priority - user-flagged)
4. File-identity over file-path (st_dev:st_ino rename-safe)
5. One loop shape visible in diagnostics
6. Visible retry on protocol failure
7. Meta-Tooling DSL (intent-based, deferred)
8. Self-describing tools (subsumed by mcp_architecture_refactor_20260606)
9. Single source of truth for disc_entries + provider history
10. Sub-agent return type constraint (bake into candidate #1 spec)
Domain classification: every recommendation tagged Application / Meta-Tooling
/ Both per docs/guide_meta_boundary.md. nagent lives in the Meta-Tooling
domain; Manual Slop's Application AI is a different kind of thing.
No code modified by this track (reference/analysis only). All 7 files
parse cleanly (JSON, TOML, Markdown). All internal cross-links resolve.
Track is 'active' awaiting human review; future-track candidates live in
decisions.md and nagent_takeaways_20260608.md.
ed
conductor-tier2