2026-10-11 16:38 UTC

provLedger's creator claims its installable Claude plugin surfaces recorded decisions and computed downstream dependencies before edits, potentially preventing data-science agents from repeating rejected experiments or overlooking affected outputs without imposing an execution veto.

state: seedheat: lowuncertainty: mediumconvergesscott: mediumagent-memory data-science-agents provenance agent-harnessesyizhao95

What is this?

The supplied case describes provLedger as a project database for data-science agents, attributed to creator yizhao95, with a claimed installable Claude plugin that surfaces recorded decisions and computed downstream dependencies before edits. Its evidence titles describe a worked-example walkthrough and installation command; the hypothesis frames the checks as advisory rather than an execution veto, intended to help agents avoid repeating rejected experiments or missing affected outputs. None of the supplied web snippets directly identifies provLedger or its creator, so they do not corroborate its installation, behavior, or effectiveness.

Why it matters to Scott

provLedger’s claimed pre-edit decision recall converges with Scott’s MCP IP Wiki advisory recall and provenance-bearing Claude-history search; computed downstream dependencies add a concrete mechanism worth testing alongside those retrieval systems, rather than just another memory store. This is creator testimony without corroborated effectiveness or compatibility with Scott’s tooling, and its advisory checks should not be mistaken for execution controls; the radar tracks related memory and dependency tools, but not this development.
dev:project.mcp-ip-wikidev:project.searchradar:continuity-claude-code-decision-memoryradar:gravity-control-center-decisionsradar:aimake-content-addressed-ai-pipelines
queries asked of Scott's wikis
  • agent memory rejected experiments decision history
  • provenance dependency graphs downstream impact before edits
  • agent harness advisory checks versus execution gates
  • data science agents experiment tracking reproducibility
  • agent-maintained wikis pre-action context retrieval

Measured heat

now 0 pts/hpeak 0 pts/hcomments 0/hpeers p14momentum: steady2 platformsage 550h
points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

09-18 18:35 (minted)⭐ origin echo-reconstructedPresents a worked-example walkthrough of pre-edit history and dependency checks, supplies a Claude plugin installation command, and explicit
yizhao95 on blog (echo) · attributed from hn.story.49758164 · published time unknown
—
09-18 18:19first on hacker news · published · lag ?I built a project database for data science agents
yzhao950213
—
09-18 18:19amplified on hacker news 👑hn.story.49758164
yzhao950213
peak 2 · 0 comments · 98% of case engagement
09-18 18:20our radar first saw it · lag ?discovery anchor: hn.story.49758164—
pace: p9 vs 1032 stories at the 336h mark (now 550h old) — behind addom-local-coding-harness (0.5x)

Evidence (2) — ⭐ canonical anchor

sourceobjectauthorscorecomments
🟧 hnI built a project database for data science agents
Retrieved article excerpt

Open article · Retrieved 2026-09-18T18:22:47.717655+00:00

# One change, checked against everything already decided

A walkthrough of provLedger: a task goes to the coding agent, the check runs before anything is edited, and the reason it fires is already on the record.

EN
中文

●~/churn-model — claude

terminal

01The task

~/churn-model on main

>

● Planning · 4 steps · churn-t118

Read pkg/training/split\_dataset.py · 62 lines

Read pkg/training/train\_churn.py · 148 lines

provledger · declaring 3 targets, checking each against its own history

provledger · computing what reads them — 5 consumers, 3 steps deep

#### ⚠ 2 findings before anything is edited

1This experiment has been run before
*80/20 was tried on 2026-08-14 and rejected · split\_dataset*

2weekly\_report reads this split, three steps downstream
*computed from the graph, not from the diff*

↳ nothing is blocked · recorded, and put in front of you

Answer them, or say go ahead — either way it is on the record.

>

🏠 Home
🎯 Outcomes
📋 Task · read only

CHURN-MODEL

## Retrain the churn model on an 80/20 split

churn-t118
published 14:22
4 steps
3 things touched

### Findings

2 blocking

⚠

This experiment has been run before

80/20 was tried on 2026-08-14 and rejected: the holdout leaked week-52 promotions, so the lift was the promotion and not the model.

pkg.training.split\_dataset
3 hits
open the record →

⚠

weekly\_report depends on this split

Computed downstream: split\_dataset → train\_churn → weekly\_report → the churn figure in the Monday deck.

3 steps · 5 consumers
open the graph →

1 unanswered

### Decisions relied on

- reason:96Stratify on churn, not on tenure — the tenure buckets are not balanced after 2026-06.
- reason:104Seed is fixed at 20260614 so a rerun is comparable.
- reason:118Holdout must not contain a promotion week.

1read the current split and its history

2answer the findings before editing

3change the split and retrain

4compare against the recorded expectation

🏠 Home
🎯 Outcomes
🧬 Node ledger · read only

CHURN-MODEL

## pkg.training.split\_dataset

derived
upstream 2 · downstream 5
14 records · 6 analysis runs

### Change history

2026-09-17

Proposed: move the split to 80/20 and retrain.

churn-t118open

stated

2026-08-14

Rejected: 80/20 leaked week-52 promotions into the holdout. Keep 70/30 until the promotion calendar is a column.

churn-t094rejected alternativesource level verbal

2 hits
stated

“We tried eighty-twenty in August and the holdout had week fifty-two in it — the lift was the promotion, not the model. Leave it at seventy-thirty until the promotion calendar is its own column.”

tier
:   stated — the user's own words, with the span

source level
:   verbal · the words themselves

recorded in
:   churn-t094, 2026-08-14 11:07

surfaced
:   3 times · adopted by 1 plan

provledger why pkg.training.split\_dataset

2026-06-02

Stratify on churn, not on tenure — the tenure buckets stopped being balanced.

churn-t061reason

5 hitsstated

2026-05-19

Signature changed: returns (train, test, meta) instead of (train, test).

run 71measured from the source

derived

2026-04-03

No reason on record for the original 70/30 choice.

run 44gap, kept as a gap

unstated

### Constraints in force

Do not move to 80/20 until the promotion calendar is a column of its own. — from churn-t094

Seed stays 20260614 so two runs can be compared. — from churn-t104

🏠 Home
🎯 Outcomes
🕸 Project state graph · read only

CHURN-MODEL

## run 87 · 2026-09-17 · 612 nodes · 188 with records

Data flow — what is read, what processes it, what comes out. Only what has a story is drawn.

FocusStory
Data flowFull

read
processed
produced










data/orders.parquet
18 columns

data/customers.parquet
11 columns

feeds/promotions
external

pkg.training.split\_dataset
14 records · 2 constraints

pkg.training.train\_churn
9 records

pkg.features.promo\_flag
declared

pkg.rollup.weekly\_report
Monday deck

metric: churn\_rate
tracked since 2026-03

### What this change would reach

**3 steps downstream**
5 consumers
1 metric on the end of it

Computed from the graph on this run and compared with the run before it — not reported by the agent.

❚❚ Pause
↺ Restart0:00 / 1:12

Interface wording is the product's own; the ledger shown here is a worked example, not a live database. The dashboard is read-only and opens the database read-only, so it can never block or change what it is showing — the check records and surfaces, it never vetoes. Try it with `claude plugin marketplace add yizhao95/prov_ledger`.

[↗ github.com/yizhao95/prov\_ledger](https://github.com/yizhao95/prov_ledger)
yzhao95021320
🟧 echo.blog ⭐Presents a worked-example walkthrough of pre-edit history and dependency checks, supplies a Claude plugin installation command, and explicityizhao95——

Interpretation history

Decision trace