clay-borg/specs/InnerLoop.md

# The Inner Loop — Assimilate and Surpass

Status: **v0.2 draft** — becomes v1.0 only after surviving its first full
pass (CB-WP-0001-T09 retrospective). v0.2 adds loop tiers with the chaos
roll, adversarial survey review, and the runnable-baseline option
(maintainer decision, 2026-07-31).

Normative process for building every Clay-Borg capability. Referenced by
all workplans. The loop's own optimization target is **agentic efficiency**:
every artifact it produces must be small enough to load whole, structured
enough to act on without interpretation, and falsifiable enough that an
agent can judge its own work without a human in the iteration.

---

## The five steps

```text
1 RESEARCH  → research/CB-RES-NNNN-<slug>.md     (survey, baselines)
2 APPROVE   → decision recorded in the ADR        (gate: survey complete?)
3 DECIDE    → decisions/ADR-NNNN-<slug>.md        (assimilate/reimplement/hybrid)
4 SPECIFY   → specs/<Capability>.md               (contracts + acceptance metrics)
5 CODE LOOP → code + scenarios + benchmarks       (iterate until metrics beat baseline)
```

**Hard gate: no implementation code for a capability exists before its ADR
(step 3) is committed.**

## Loop tiers and the chaos roll

Every work packet declares a tier before work starts. The tier sets how
heavy steps 1–3 are; steps 4–5 (spec with metrics, code loop with evidence)
are never skipped for code-producing work.

| Tier | Weight of steps 1–3 | Structural trigger (forces at least this tier) |
|---|---|---|
| **L** | Full: separate survey, adversarial review, ADR | Creates a new capability port, or is named a high-leverage pass by the maintainer |
| **M** | Survey and ADR merged into one document; review optional | Touches a canonical interface, or adds/updates an external dependency |
| **S** | One provenance paragraph in the commit message | Everything else (utilities, fixes, refactors inside a boundary) |

**The chaos roll.** After deriving the structural tier, roll d10
(`shuf -i 1-10 -n 1`). On a **10**, the tier is instead picked uniformly at
random (`shuf -e S M L -n 1`), overriding the structural derivation — up or
down. Both rolls are recorded in the tier declaration
(`tier: M (structural L, chaos 10→M)`). Purpose: an occasional random
reweighting keeps the classification honest — arguing everything into S
stops paying off when audits can compare argued tiers against the random
sample — and occasionally forces a deep look at something "obviously
trivial", which is where local optima hide.

Chaos limits: a rolled-down tier relaxes *process* weight only. Invariants
(zero foreign types in canonical interfaces, determinism, passing
conformance suites) bind at every tier, and a rolled-down pass touching a
canonical interface still requires the interface change to be flagged in
the commit for retrospective review.

### Step 1 — Research

Identify the best implementation in existence for this capability. Produce
`research/CB-RES-NNNN-<slug>.md` following the survey template (below).
The survey is done when it can name, per dimension, a concrete
**benchmark-to-beat**: a number, a property, or a reproducible comparison —
not an impression.

**Runnable-baseline option.** For passes judged high-leverage (declared by
the maintainer or proposed in the survey and confirmed in the ADR), cited
numbers are not enough: the survey must ship a reproducible **baseline
harness** that runs the leading candidate on our machine against our
workload — the same scenario files where feasible. The harness ships with a
*fidelity note* stating what was and wasn't faithfully reproduced, so a
hastily wired competitor setup cannot silently inflate our advantage.
Where the option is not invoked (or the candidate isn't practically
runnable), comparisons against cited-only numbers are **directional**: the
evidence verdict for those rows caps at `parity`, never `better`.

### Step 2 — Approve (adversarial review)

For tier-L passes, approval is earned through an **adversarial review**: a
separate session (or agent), given only the survey document, attempts to
break it — an omitted candidate, a stale or unverifiable benchmark, an
unmeasured claim presented as measured. Exactly **one round**: challenge,
then response. The survey is approvable only when every challenge is either
answered with evidence or conceded and folded into the survey.

**Documentation requirement:** the research process, the challenge, and the
resulting improvements to the research are each documented in timestamped
markdown files under `history/`:

```text
history/YYMMDD-<slug>-research.md    # how the survey was conducted: sources,
                                     # queries, what was measured vs cited, dead ends
history/YYMMDD-<slug>-challenge.md   # the adversarial attack, verbatim
history/YYMMDD-<slug>-response.md    # answers/concessions and what changed in the survey
```

The polished survey artifact remains `research/CB-RES-NNNN-<slug>.md`; the
history files preserve the unpolished trail so a later reader can judge how
hard the survey was actually tested. For tier-M passes the review is
optional but, when performed, follows the same format. If not approvable
after the round, the loop returns to step 1 with the named gaps.

### Step 3 — Decide

`decisions/ADR-NNNN-<slug>.md`: assimilate behind a port, reimplement, or
hybrid — with the **expected advantage stated per dimension** (see rubric).
An honest "worse here, better there, and why that trade is right" beats a
claimed sweep of all four dimensions.

### Step 4 — Specify

`specs/<Capability>.md`: the contracts, invariants, and — mandatory — the
**acceptance metrics table**, each row tied to a baseline from step 1.
A spec without measurable acceptance criteria is not done. Metrics follow
the conventions in [MetricsAndScenarios.md](MetricsAndScenarios.md),
including the rule that metric selection itself passes through a mini
research step (metric provenance).

### Step 5 — Code loop

Implement iteratively. Each iteration:

```text
change → cb-check (fmt, clippy, tests) → scenarios → benchmarks
       → compare against acceptance table → evidence row appended
```

Done when every acceptance metric meets or beats its baseline and the
comparison numbers are committed as an evidence file
(`evidence/CB-EV-NNNN-<slug>.md`). A failed scenario must yield a replay
artifact an agent can re-execute locally.

---

## The four-dimension rubric

Every survey, ADR, and acceptance table is organized by these dimensions:

| Dimension | Question | Example measurable proxies |
|---|---|---|
| **D1 Ease of specification** | How simply can behavior be stated, tested, understood? | rules-to-scenario coverage %, spec lines per rule, time-to-first-correct-scenario for a fresh agent session |
| **D2 Efficiency of implementation** | How cheap to build and keep building? | source LOC, dependency count/weight, clean-build and incremental-build time, tokens-per-completed-task |
| **D3 Speed of execution** | How fast does it run? | benchmark wall-time vs baseline, events/sec, memory footprint, determinism overhead |
| **D4 Optionality** | How cleanly does it integrate, extend, get replaced? | public API surface size, count of leaked foreign types (must be 0), effort-to-swap measured by null/reference impl existence, WIT-expressibility |

Scoring is always **relative to the step-1 baseline**, never absolute:
`better / parity / worse / unmeasured` per proxy, with the number attached.
`unmeasured` is legal in a survey, illegal in an evidence file.

---

## Survey template (research/CB-RES-NNNN-<slug>.md)

```markdown
# CB-RES-NNNN: <capability>
capability: <canonical.capability.id>
status: draft | approved

## Candidates
Per candidate: origin, license, maturity, adoption; data model; mutation
mechanism; determinism/replay story; relevant performance (measured if
runnable locally, cited with source otherwise).

## Baselines (benchmark-to-beat)
| Dimension | Baseline holder | Metric | Value | Provenance |
(one row minimum per dimension; provenance = measured / cited / estimated)

## Verdict
Which candidate leads per dimension; what none of them do well
(the surpass opportunity); risks in the baselines themselves.
```

---

## Agentic-efficiency requirements

The loop exists to be driven by agents. Therefore:

1. **Whole-file loadability** — every loop artifact stays under ~400 lines;
   split before exceeding, link with relative paths.
2. **Structured over prose** — tables and fenced blocks for anything a
   later step must parse (baselines, acceptance metrics, evidence rows).
3. **One command surface** — all checks runnable through repo-root
   commands (eventually `cb *`; until then, `make`/`cargo` aliases declared
   in one place), each supporting deterministic, greppable output.
4. **Self-contained tasks** — a workplan task names its input artifacts and
   output artifacts; a fresh session must be able to execute it from the
   task text plus linked files alone.
5. **Evidence or it didn't happen** — claims of "better" live in committed
   evidence files with numbers, never only in commit messages or chat.
6. **Token discipline** — per the global budget policy, a loop iteration
   that exceeds its budget without measurable progress is stopped and
   decomposed, not pushed through.

---

## Definition of done — one loop pass

A capability has completed the loop when all of the following are committed:

- [ ] research/CB-RES-NNNN with approved status and full baseline table
- [ ] decisions/ADR-NNNN with per-dimension expected advantage
- [ ] specs/<Capability>.md with acceptance-metrics table
- [ ] passing scenarios covering every numbered spec rule
- [ ] evidence/CB-EV-NNNN with final comparison vs baseline, no `unmeasured`
- [ ] retrospective note (may be one paragraph appended to the evidence
      file): what the loop itself should change
```