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