clay-borg/workplans/CB-WP-0004-mechanical-work.md

---
id: CB-WP-0004
title: "Move mechanical turns off the token budget, and prove it worked"
status: in_progress
state_hub_workstream_id: "6880ac78-d817-41b9-b267-f12ff9deea28"
---

# Purpose

`research/CB-RES-0003-agent-vs-deterministic.md` measured every turn in
both clay-borg sessions by the tool calls it made:

```text
    MECHANICAL (deduplicated)          290 turns  $   51.26  = 38% of pass
```

**38% of spend went through turns doing work a deterministic tool could
do.** The largest single category is `cd` and `export PATH` — 84 turns and
$15.33 of pure environment friction. The second is inline heredocs
string-patching markdown, which is also the mechanism behind the
duplicated-fact-drift error class InnerLoop v1.2 named and could not gate.

This workplan converts the five worthwhile categories to classic compute
and **measures whether that actually recovered anything**. The predicted
recovery is $33–41 per pass, 25–30%.

**The control loop is the point, not a formality.** The named failure mode
is *relocation*: an agent that can no longer write a heredoc may simply
write more prose, and the pass costs the same. `make cost-mix` emits the
same categories that produced the baseline, so the claim is falsifiable by
the same instrument that made it. A saving that cannot be demonstrated in
that table did not happen.

Per InnerLoop v1.2, targets here are **provisional until the instrument
emits them**, and no target may be moved in the commit that measures it
unless the instrument disproved it (§Step 4, correction vs retarget).

## Phase A — The certain wins

## Task: Remove environment friction

```task
id: CB-WP-0004-T01
status: done
priority: high
state_hub_task_id: "3ddfd3e2-8596-4969-a069-09577933fcbc"
```

84 turns / $15.33, the largest category and the least interesting work in
the corpus. `cargo` is not on the default path, so every Rust-touching
command carried `export PATH="$HOME/.cargo/bin:$PATH"`, and the shell does
not persist `cd`.

Fix at the root, not the leaf: `tools/dep-weight.py` already special-cases
the missing `cargo` with a helpful error, which is evidence the friction
was noticed and patched in the wrong place.

Deliver: every `make` target runs from a clean shell with no prefix, from
any directory. Document the one-line environment requirement in
`README.md` if one remains. Remove the leaf workaround in `dep-weight.py`
only if it becomes unreachable — a positive control that never fires is
still cheaper than a regression.

**Predicted:** environment-setup turns → **< 10** (from 84),
**$12–15** recovered. Highest confidence in the review.

**Delivered.** `tools/repo.py` resolves the repo root from `__file__` and
`cargo` from PATH-then-rustup-locations; every tool imports it, so `REPO`
is now stated once rather than four times. The Makefile derives `REPO`
from `MAKEFILE_LIST` and resolves `CARGO` the same way. `make env-test`
is the positive control — it runs every tool from `/` with
`PATH=/usr/bin:/bin`, and is wired into `make all`, so this cannot
silently regress and invalidate T05's measurement.

The leaf workaround in `dep-weight.py` was kept, not deleted: it is now
unreachable on a rustup machine, and `--self-test` asserts `cargo_bin()`
resolves unaided. Per the task text, a control that never fires is
cheaper than a regression.

`loop-lint` failed on `repo.py` immediately — a new tool with a positive
control but no `--self-test` entry point. Second time the gate has caught
its own pass's work within the hour.

## Task: `make task-done` — one command for a task close

```task
id: CB-WP-0004-T02
status: done
priority: high
state_hub_task_id: "8a1b59c7-6318-47ba-8cbc-83bb44dd221f"
```

Merges two categories: workplan status edits (21 turns, $4.06) and hub
task-status calls (25 turns, $7.46).

`make task-done T=CB-WP-0004-T02` must:

1. flip `status: todo` → `done` in the workplan file, **failing loudly on
   an unknown or already-done task** — the heredocs it replaces silently
   no-op'd on a typo;
2. read that task's **measured** cost and tokens from `cb-cost --by-task`;
3. push the hub event with the real numbers.

The third point is the one that matters beyond cost. Every
`update_task_status` in this project so far carried **hand-typed token
estimates**, in a repo whose central finding is that estimated token counts
are worthless. The hub currently holds fiction produced by the exact habit
CB-WP-0002 disproved.

**Predicted:** those 46 turns → **~6**, **$9–11** recovered, and the hub
stops holding estimates. Add `--self-test` per InnerLoop v1.1.

**Delivered.** `tools/task-done.py` + `make task-done T=<id>`. It refuses
on an unknown id, a typo'd id, an already-done task, a task with no
`state_hub_task_id`, and — the one that matters — **a task with no
measured spend**, rather than reporting an estimate. `cb-cost` gained
`by_task_detail` (cost, response count, model histogram, and token
components per task), and `task-done` imports cb-cost rather than parsing
its printed table, so the hub number is not a copy that can drift.

**The positive control found a real defect before the tool was used
once.** Attribution keyed on a bare `T\d\d` from the commit subject, so
`CB-WP-0002 T01`, `CB-WP-0003 T01` and `CB-WP-0004 T01` all landed in one
bucket. The self-test reported **$12.10** for "T01"; the qualified figure
is **$2.33** — a 5.2× overstatement that would have been pushed to the
hub as a measured number, reproducing the fiction this task exists to
end, in a new form. Fixed by `task_label()`: qualified subjects
(`CB-WP-0004 T01`) key on the full id, unqualified ones stay bare and are
never retro-assigned to a workplan. The pinned $93.15 benchmark is
unchanged, confirming historical attribution was not disturbed.

That is the **fourth** instance of trusted arithmetic (TA) — a number
believed because it was produced by a program rather than by hand.

## Task: `make status` — one-shot orientation

```task
id: CB-WP-0004-T03
status: done
priority: medium
state_hub_task_id: "5466a510-37a5-4491-b93e-509cd400cc23"
```

49 turns / $6.87 of `grep`/`ls`/`wc` answering "what is the state of this
repo". Replace with one command printing: active workplan and task counts,
gate results, open spend since the last commit (CB-01), provisional item
ages, and any `loop-lint` findings.

Also shrinks cold-start context, which `specs/SessionShape.md` §3 measures
at ~51k for a fresh session — the artifacts a new session reads to orient
are exactly what this prints.

**Predicted:** ~10 orientation turns → **1 per session**, **$4** recovered.
Confidence medium: some inspection is genuinely exploratory and will not
disappear, and the review says so.

**Delivered.** `tools/status.py` + `make status`, 22 lines of output:
commit and working-tree state, every workplan with its task counts, the
next todo task with its heading, spend since the last commit against
CB-01/CB-02, and the three fast gates.

Two deliberate constraints. It **does not build** — a status command that
takes two minutes gets replaced by `ls` within a day — and it **states
its own limit** in the output (`slow gates not run here`), so a green
`status` cannot be misread as a green `make all`. The self-test asserts
the output stays under 40 lines, because the failure mode for an
orientation tool is becoming another thing to skim.

Its positive control refuses the confidently-empty report: a parser that
found zero workplans and zero tasks would print a clean, wrong picture,
which is worse than the greps it replaces. That control also caught a
dot-all regex that returned twenty paragraphs of a previous task's prose
as the "task heading".

## Phase B — The one that also closes an error class

## Task: Fact registry and `make facts-check`

```task
id: CB-WP-0004-T04
status: done
priority: high
state_hub_task_id: "b5dfbf1e-619b-4e64-8463-49ff2ce38b48"
```

75 turns / $13.86 of heredocs opening a markdown file, string-replacing a
number, and writing it back — the mechanism behind **duplicated-fact
drift**, the fourth error class, which InnerLoop v1.2 states as prose and
cannot currently gate.

Two instances on record: a price sheet inlined into a spec went stale
within an hour of the real sheet changing, and the acceptance figure
$92.21 → $92.87 → $93.32 → $93.15 had to be chased across a survey, a
workplan, and an evidence file on every move.

Deliver a registry where a number appearing in more than one artifact is
declared once — **generated by the instrument that measures it wherever
possible**, not hand-maintained — plus `make facts-check` failing when a
committed artifact disagrees with it.

**The trap to avoid, stated up front:** a hand-maintained registry moves
the problem rather than solving it, and would itself become a copy that
drifts. If generation from instruments proves impractical, deliver only
the *check* (detect the same number stated differently in two artifacts)
and say so — a gate with no generator still closes the class.

**Predicted:** **$6–9** recovered, plus DFD's first executable gate.
Confidence medium; this is the hardest task here and the most valuable.

**Delivered — both halves, not just the check.** `facts.toml` holds 15
facts and is **generated** by `make facts-gen` from cb-cost, dep-weight
and rule-coverage; the file opens with `# GENERATED — do not edit` and
the self-test asserts that line is still there. The trap named in this
task — a hand-maintained registry that becomes another drifting copy —
is closed by `facts-check` re-running the instruments and failing if the
committed registry disagrees with them. A stale registry cannot certify
stale artifacts.

An artifact quoting a fact tags it: `**$93.15** <!-- fact:pinned_total -->`.
17 occurrences across 5 artifacts are now under the gate.

**Falsified before being believed.** Changing `specs/CostAccounting.md`
line 158 from $93.15 to $92.87 — the exact historical drift — produced
exit 1 and `specs/CostAccounting.md:158 claims fact:pinned_total but does
not state $93.15`. The gate was tested against the class it exists to
catch, on a real artifact, not only in its self-test.

**What it does not close, stated rather than implied.** 22 untagged
literal copies remain, across `specs/InnerLoop.md`, `specs/GameKernel.md`,
`research/CB-RES-0002` and the older workplans. They are **reported, not
failed**: tagging is opt-in, a number can legitimately recur, and a gate
that fires on coincidence gets routed around. Naming the uncovered
surface is more useful than claiming the class is closed.

InnerLoop's single-source-of-fact rule moves from prose to executable —
**v1.3**.

## Phase C — Prove it, or withdraw the claim

## Task: Control loop — measure recovery and test for relocation

```task
id: CB-WP-0004-T05
status: todo
priority: high
state_hub_task_id: "922346ac-1e99-4e94-9dc6-35c8fa0eddc5"
```

The task this workplan exists for. Run `make cost-mix` over the sessions
that executed T01–T04 and commit
`evidence/CB-EV-0003-mechanical-work.md` comparing against the committed
baseline:

| category | baseline turns | baseline $ | predicted | measured | verdict |
|---|---|---|---|---|---|
| environment setup | 84 | $15.33 | <10 turns | | |
| ad-hoc text patching | 75 | $13.86 | $6–9 saved | | |
| hub task status + workplan edit | 46 | $11.52 | ~6 turns | | |
| orientation / inspect | 49 | $6.87 | $4 saved | | |
| **mechanical total** | **290** | **$51.26** | **$33–41 saved** | | |

**Three tests, all of which must be reported:**

1. **Did the mechanical turns disappear?** Per-category, against
   prediction. An unmet prediction is reported unmet, not retargeted.
2. **Did they relocate?** Total pass cost and non-mechanical turn counts
   must be compared too. If mechanical turns fell and prose turns rose by
   as much, the saving is zero and this workplan failed — that is the
   result to publish.
3. **Did quality hold?** `make all` green, and the same class of findings
   still surfacing. A cheaper pass that catches fewer errors is worse, and
   the loop has no metric for this yet — record the judgment explicitly
   rather than implying the cost number settles it.

Normalize per unit of work, not per session: passes differ in size, so
report **mechanical share of pass cost** (baseline: 38%) alongside
absolute dollars.

**Measured — [CB-EV-0003](../evidence/CB-EV-0003-mechanical-work.md).**
`cb-cost` gained `--since`, so the baseline window (`--pin 578dcbe`, 662
responses, $135.60) and this pass (`--since 578dcbe`, 83 responses,
$7.82) are two disjoint windows over the same transcripts.

**Mechanical share fell 38.2% → 32.4%. Six points, against a predicted
25–30. The aggregate prediction is reported unmet.**

Two categories met their prediction and two did not:

- environment setup **11.5% → 0.6%** of pass (85 turns → 1) — met
- hub + workplan closes **8.5% → 0.0%** (46 turns → 0) — met
- text patching **10.4% → 9.6%** — not met
- orientation **5.1% → 21.2%** — not met, *worse*

**The confound is stated in the evidence before any defence:** this is
the pass that *built* the tools, and the two categories that missed are
precisely the two whose tools were under construction. Writing
`make status` requires inspecting what it summarizes. The clean test is
the next pass, which uses the tools without building them — that test is
carried forward, not waived.

**Relocation: not supported.** Output tokens per response *fell* 896 →
681. The rise in output's share of cost is a shrinking denominator
(cache-read fell as context shrank), not more prose. Cost per response
halved, and the evidence explicitly refuses to claim it: that is
compaction (mean context 232,982 → 117,822), not tooling.

**Quality held.** `make all` green with two new gates, and four findings
surfaced this pass — three of them caught by controls written this pass,
including a 5.2× attribution error that would have reached the hub as a
measured number.

## Task: Retrospective

```task
id: CB-WP-0004-T06
status: todo
priority: low
state_hub_task_id: "47892c23-ef09-4910-a9af-327494289e05"
```

The question to answer honestly: **does converting agent work to
deterministic tooling actually recover capacity, or does the work
reappear elsewhere?**

This is the first pass in the project to make a *quantitative prediction
before acting*. Whether the prediction held is more informative than the
saving itself — a loop that can forecast its own economics can plan; one
that cannot is guessing with numbers attached.

Record the prediction error per candidate, and whether the review's stated
confidence levels (high/medium/low) tracked reality. If they did not, the
next review should stop stating confidence, or state it differently.