| name | rebind-manifest |
| description | Pipeline stage 2 of report-regeneration (detect -> strip -> rebind): turn an RSG + the OLD template + the new dataset into a schema-valid Binding Manifest and a taint dictionary. Enforces the earned-frozen rule (a data-shaped literal / old-taint / new-dataset value demotes a candidate-frozen node to needs-review), forces raster/embedded-cache nodes to regenerate, and proposes each node's data_query. Reach for this when building or amending a Binding Manifest. |
Skill: rebind-manifest (report-regeneration stage 2)
The surgeon planning the transplant. Given a Report Structure Graph (RSG), the OLD
template, and the new dataset, this stage builds a versioned, human-reviewable Binding
Manifest plus the taint dictionary that the V4 egress leg scans against. It addresses +
classifies + proposes queries — it never renders.
The honest guarantee (verbatim — never soften it): the plugin GUARANTEES only (a) no
old-client-data leak and (b) every low-confidence classification is surfaced for human
review. It does NOT guarantee a human-free-correct report. needs-review is guarantee (b)
made mechanical.
Run it
python3 build_manifest.py \
--rsg <rsg.json> --template <old-template.html> --new-data <data.json> \
--out <manifest.json> [--taint-out <taint-dict.json>] \
[--manifest-version 0.1.0] [--confidence-threshold 0.7] [--format json|text] [--pretty]
Exit codes: 0 valid manifest; 2 usage / path-guard / parse error / input RSG failed
rsg.schema.json (fail-closed); 3 manifest built but failed binding-manifest.schema.json.
--new-data shape: {"source_ref": "...", "source_period": "...", "values": [...] | {...}}.
values is the new value domain the earned-frozen rule tests against; if omitted, every scalar
leaf (minus reserved metadata keys) is the domain.
What it does (mirrors knowledge/core-architecture-spec.md §3/§4/§6)
- Taint dictionary from the OLD template — distinct rendered value literals (via the
pinned, non-inference data-shaped-literal detector) + identity strings (author / company /
title / source-filename), including a declared prior-artifact taint block
(
old_company: "..." comment convention) when present.
- Earned-
frozen rule. frozen is never the default. A candidate-frozen node is
demoted to needs-review if an independent re-run of the detector over its rendered
text fires (or the RSG already flagged it), OR the text carries an old-taint value, OR it
carries a new-dataset value. A data-shaped literal force-demotes regardless of classifier
confidence. (The RSG is already schema-forbidden from carrying frozen + data_shaped_literal:true,
so the demotion authority here is the independent detector, not the RSG flag.)
- Raster / embedded-cache force. Any node that renders as a raster or carries an embedded
binary/data cache is forced to
regenerate — a transplanted blob cannot be proven data-free.
- Propose one binding per NON-static node:
node_id, anchor, class, confidence,
provenance {source, source_period, method, pbi_route}, data_query. A frozen binding
carries no data_query; every non-frozen class must carry one.
- Validate the manifest against
binding-manifest.schema.json (stdlib-only validator).
Conservative-by-design note
The detector is deliberately non-inference: it fires on "100%" in a marketing tagline exactly
as on a KPI's "100%". Over-flagging a candidate-frozen node to needs-review is the safe
direction (guarantee (b)); under-flagging a data-bound node classed frozen is what a leak
looks like.
Constraints
Stdlib only (argparse / html.parser / re / json / pathlib), Python 3.9.6, no pip, no
network, no subprocess. Path-guarded (rejects .. traversal). Code is written to the schemas in
../../knowledge/.
Tests
python3 -m unittest tests.test_manifest (run from this skill directory) — demotion, taint dict
(inline + real corpus), raster→regenerate, and schema-validity.
