captable_build git:20260908.1bafa29A

Immutable. This exact content never changes and is served at /api/v1/blob/25237deb63d30667.

---
name: captable_build
description: Extract, reconcile and validate startup ownership and convertible-loan data into four managed JSON insights.
---

# captable_build

## Inputs and outputs

One startup dataset slug with successfully synchronized parsed documents.
The canonical API returns `list[InsightFile]` containing the consolidated result.
Four logical JSON insights live under `insights/captable-build/`: `classification`,
`loan-extraction`, `table-extraction`, and `consolidated`. Filenames and model
suffixes are supplied by `InsightFile`, using `subdir=True` and `extension="json"`.
There are no dated snapshots, latest pointers, HTML files, separate assessments,
aggregation caches or build Markdown reports. Source dates stay inside the JSON.

## Workflow and dependencies

Classify source documents, extract CLA terms, and extract cap-table/register/pool
versions. Reconcile the source versions, assess terms and aggregate loans in code,
then save the consolidated JSON. Assessment and aggregation have no separate files;
PDF signature markers are read again when consolidation must be recomputed.
The configurable term schema is `config/captable_build/cla_terms.md`.

Every stage uses shared reusable selection: manual first, then ranked generated
insights with matching indexed startup revision and effective configuration.
Extraction keys include selected classification content. Consolidation includes
all three selected inputs, assessment settings, tool version and evaluation date
for maturity findings. Editing a manual input invalidates generated dependents.
A manual consolidated JSON wins before dependencies run. `--fresh` bypasses
only generated reuse, without deleting files or overriding manual inputs.

## Side effects and failure behavior

Generation writes only the managed JSON insights and shared freshness metadata.
Missing/empty parsed sources or failed extractions raise; incomplete outputs are
not saved as reusable insights. Failures remain in logs and retry on a later run.
Manual JSON must have the same structure as its generated counterpart. Existing
legacy files are left untouched and are not selected as alternative inputs.
This skill never imports, synchronizes or discovers people implicitly. Bulk
refresh performs its own shared pre-ingestion and registers this for startups.

## Usage

```bash
conda run -n sictic-env python -m skills.harness /captable_build example
conda run -n sictic-env python -m skills.captable_build build --startup example
```

`--dataset`/`-d` remain aliases; `--fresh` regenerates generated artifacts.
The direct CLI retains `classify`, `extract`, `table`, `assess`, and `aggregate`
for inspection. They use the same stage implementations; cheap assessments and
aggregation only return structured data. The `build` Python adapter returns the
consolidated dictionary from the same canonical workflow. No `snapshot` command.
The direct build CLI also retains `--model` for explicit test-model overrides.

## References

- [Implementation](captable_build.py)
- [Insight objects](../../lib/captable/insights.py)
- [Term schema](../../config/captable_build/cla_terms.md)
- [Domain checks](../../docs/captable-checks.md)