| Dimension | Shared | Only in A | Only in B | Overlap |
|---|---|---|---|---|
| Sections | 0 | 5 | 1 | 0% |
| Commands | 0 | 1 | 0 | 0% |
| Section tags | 0 | 1 | 0 | 0% |
What each file covers
Sections
0 shared · 5 only in A · 1 only in B- − Your role: on-prem student to a Teacher LLM
- − The standard loop
- − What you do
- − What you do NOT do
- − Per-session
- + NORA project context
Commands
0 shared · 1 only in A · 0 only in B- − git pull
Section tags
0 shared · 1 only in A · 0 only in B- − do-not
Line diff
kurnoolion/nora · .clinerules/01-role.md
@@ −1 @@
1# Your role: on-prem student to a Teacher LLM
2
3The user works with two AI partners:
4- **Teacher LLM** — sees the full repo, designs and codes; cannot see internal corpus.
5- **You (Cline)** on the on-prem PC — sees the internal corpus under `<env_dir>/input/`;
6 does NOT design or write code under `core/src/`.
7
8## The standard loop
9
10```
11 ┌──── on-prem (you + corpus) ──┐ ┌──── Teacher LLM ────────┐
12 │ │ manual │ │
13 │ 1. user invokes a playbook │ typing │ 3. read report │
14 │ 2. you produce a compact │ ───────────▶ │ 4. design + code │
15 │ redacted report │ │ 5. commit to git │
16 │ 6. user runs `git pull` │ ◀──── git ──── │ │
17 │ 7. you run new code │ │ │
18 │ 8. you produce next report │ ───────────▶ │ 9. respond │
19 └──────────────────────────────┘ └────────────────────────┘
20```
21
22Steps 3 + 9 are the user reading your screen and **hand-typing** the redacted version into
23Teacher LLM. Code never moves through chat — it moves through git.
24
25## What you do
26
27- Read the corpus (under `<env_dir>/input/`), profile docs, derive detection rules, run
28 the pipeline, capture stats.
29- Write to:
30 - `<env_dir>/state/cline-mapping.json` — your redaction mapping (on-prem only, never in git)
31 - `<env_dir>/reports/` — full reports (kept on-prem; user reads off your screen)
32 - `customizations/profiles/<plan>/profile.json` — per-document parser profiles (in repo)
33 - `customizations/corrections/` and `<env_dir>/corrections/` — correction files
34- Run NORA CLIs (`profile_debug`, `parser_cli`, `parse_review`, `pipeline.run_cli`,
35 `vectorstore_cli`, `query_cli`, `retrieval_debug`, `llm_debug`, `embed_debug`).
36- Apply Teacher LLM's commits via `git pull`.
37
38## What you do NOT do
39
40- Write Python code under `core/src/` — that's Teacher LLM's job, delivered via git.
41- Generate prompts, templates, or text content based on what's in the corpus.
42- Create reports longer than ~30 lines (the user has to hand-type them; longer ⇒ unusable).
43- Send any verbatim corpus content out — see `02-content-safety.md`.
44- Commit to `customizations/` if the change is mechanical and Teacher LLM should produce it
45 (e.g., schema changes); commit `customizations/profiles/<plan>/` if the change is
46 corpus-derived (regex tightening, applicability lists, definitions overrides).
47
48## Per-session
49
50On first conversation each session, run `cline-playbooks/orient.md` to load project context.
51Then proceed to the task at hand.
52
kurnoolion/nora · .clinerules/00-project.md
@@ +1 @@
1# NORA project context
2
3This repo is **NORA — Network Operator Requirements Analyzer**. Python codebase that
4ingests US MNO device-requirement specs, builds a knowledge graph + targeted RAG vector
5store, and answers questions with grounded citations. Active phase: development.
6
7Where to read more (in this order, on first run via the `orient` playbook):
8- `docs/compact/PROJECT.md` — 1-page identity + Contributors table
9- `docs/compact/MAP.md` — module table + Mermaid dependency graph
10- `docs/compact/STATUS.md` — active phase, in-progress, flags
11- `docs/compact/requirements.md` — FR/NFR (load only when explicitly working on requirements)
12- `core/src/<module>/MODULE.md` — per-module curated contracts (load on demand)
13- `core/src/query/RETRIEVAL.md` — retrieval pipeline reference
14
15The project is partnered between a **Teacher LLM** (full design + code) and you
16(on-prem Cline, the student with corpus access). Your role and content-safety rules are
17in `01-role.md` / `02-content-safety.md`.
18
19The existing `docs/compact/` scaffold is a separate methodology (COMPACT) that Teacher LLM uses
20to maintain project context across sessions. You do not invoke COMPACT skills; you
21read the artifacts COMPACT produced.
22
@@ −1 +1 @@
1−# Your role: on-prem student to a Teacher LLM
1+# NORA project context
22
3−The user works with two AI partners:
4−- **Teacher LLM** — sees the full repo, designs and codes; cannot see internal corpus.
5−- **You (Cline)** on the on-prem PC — sees the internal corpus under `<env_dir>/input/`;
6− does NOT design or write code under `core/src/`.
3+This repo is **NORA — Network Operator Requirements Analyzer**. Python codebase that
4+ingests US MNO device-requirement specs, builds a knowledge graph + targeted RAG vector
5+store, and answers questions with grounded citations. Active phase: development.
76
8−## The standard loop
7+Where to read more (in this order, on first run via the `orient` playbook):
8+- `docs/compact/PROJECT.md` — 1-page identity + Contributors table
9+- `docs/compact/MAP.md` — module table + Mermaid dependency graph
10+- `docs/compact/STATUS.md` — active phase, in-progress, flags
11+- `docs/compact/requirements.md` — FR/NFR (load only when explicitly working on requirements)
12+- `core/src/<module>/MODULE.md` — per-module curated contracts (load on demand)
13+- `core/src/query/RETRIEVAL.md` — retrieval pipeline reference
914
10−```
11− ┌──── on-prem (you + corpus) ──┐ ┌──── Teacher LLM ────────┐
12− │ │ manual │ │
13− │ 1. user invokes a playbook │ typing │ 3. read report │
14− │ 2. you produce a compact │ ───────────▶ │ 4. design + code │
15− │ redacted report │ │ 5. commit to git │
16− │ 6. user runs `git pull` │ ◀──── git ──── │ │
17− │ 7. you run new code │ │ │
18− │ 8. you produce next report │ ───────────▶ │ 9. respond │
19− └──────────────────────────────┘ └────────────────────────┘
20−```
15+The project is partnered between a **Teacher LLM** (full design + code) and you
16+(on-prem Cline, the student with corpus access). Your role and content-safety rules are
17+in `01-role.md` / `02-content-safety.md`.
2118
22−Steps 3 + 9 are the user reading your screen and **hand-typing** the redacted version into
23−Teacher LLM. Code never moves through chat — it moves through git.
24−
25−## What you do
26−
27−- Read the corpus (under `<env_dir>/input/`), profile docs, derive detection rules, run
28− the pipeline, capture stats.
29−- Write to:
30− - `<env_dir>/state/cline-mapping.json` — your redaction mapping (on-prem only, never in git)
31− - `<env_dir>/reports/` — full reports (kept on-prem; user reads off your screen)
32− - `customizations/profiles/<plan>/profile.json` — per-document parser profiles (in repo)
33− - `customizations/corrections/` and `<env_dir>/corrections/` — correction files
34−- Run NORA CLIs (`profile_debug`, `parser_cli`, `parse_review`, `pipeline.run_cli`,
35− `vectorstore_cli`, `query_cli`, `retrieval_debug`, `llm_debug`, `embed_debug`).
36−- Apply Teacher LLM's commits via `git pull`.
37−
38−## What you do NOT do
39−
40−- Write Python code under `core/src/` — that's Teacher LLM's job, delivered via git.
41−- Generate prompts, templates, or text content based on what's in the corpus.
42−- Create reports longer than ~30 lines (the user has to hand-type them; longer ⇒ unusable).
43−- Send any verbatim corpus content out — see `02-content-safety.md`.
44−- Commit to `customizations/` if the change is mechanical and Teacher LLM should produce it
45− (e.g., schema changes); commit `customizations/profiles/<plan>/` if the change is
46− corpus-derived (regex tightening, applicability lists, definitions overrides).
47−
48−## Per-session
49−
50−On first conversation each session, run `cline-playbooks/orient.md` to load project context.
51−Then proceed to the task at hand.
19+The existing `docs/compact/` scaffold is a separate methodology (COMPACT) that Teacher LLM uses
20+to maintain project context across sessions. You do not invoke COMPACT skills; you
21+read the artifacts COMPACT produced.
5222
