RE

render-review-rows

Automates the assembly of data review reports.

Install

mkdir -p .claude/skills/render-review-rows && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13555" && unzip -o skill.zip -d .claude/skills/render-review-rows && rm skill.zip

Installs to .claude/skills/render-review-rows

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

1. The filing is the single source of truth. Every fact traces to `source_accession_number` + verbatim `source_text`. 2. Fail closed on source ambiguity. Fail open on extraction incompleteness. 3. Facts before judgments. Proposals are raw events. Classification is Skill 8, not Sk
280 chars · catalog descriptionno explicit “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Intermediate

Key capabilities

  • Denormalize extraction and enrichment artifacts into a 47-column CSV.
  • Rebuild `master_rows.csv` after manual overrides.
  • Rebuild the global `Data/views/master.csv` after deal changes.
  • Populate 47 columns per a column specification.
  • Derive `bid_note` from `event_type` using a mapping table.

How it works

This skill reads various JSONL and JSON input artifacts, processes them according to a column specification, and outputs a denormalized 47-column CSV file, along with review status and an overrides file.

Inputs & outputs

You give it
Extraction and enrichment artifacts from Skills 1-8, such as `deal.json`, `actors.jsonl`, `events.jsonl`, `judgments.jsonl`.
You get back
A `master_rows.csv` file with 47 columns, `review_status.json`, `overrides.csv`, and a global `Data/views/master.csv`.

When to use render-review-rows

  • Rebuilding master review files
  • Aggregating deal extraction data
  • Generating compliance reports

About this skill

render-review-rows

Design Principles

  1. The filing is the single source of truth. Every fact traces to source_accession_number + verbatim source_text.
  2. Fail closed on source ambiguity. Fail open on extraction incompleteness.
  3. Facts before judgments. Proposals are raw events. Classification is Skill 8, not Skill 5.
  4. Alex's collection instructions are the extraction spec. Used for methodology and taxonomy. Never as a factual source.
  5. master.csv is the review artifact, not the estimation artifact.

Overview

Denormalize all extraction and enrichment artifacts into a 47-column review CSV. Pure mechanical assembly -- no judgment, no classification, no interpretation. If the input artifacts exist, this skill always succeeds.

When To Use

  • After Skills 1-8 have completed (orchestrated or independent).
  • To rebuild master_rows.csv after manual overrides or re-extraction.
  • To rebuild the global Data/views/master.csv after any deal changes.

Input Artifacts

All paths relative to Data/deals/<slug>/:

ArtifactSource Skill
extraction/deal.json5. extract-events
extraction/actors.jsonl4. build-party-register
extraction/actors_extended.jsonl5. extract-events (if new actors minted)
extraction/events.jsonl5. extract-events
extraction/event_actor_links.jsonl5. extract-events
enrichment/process_cycles.jsonl7. segment-processes
enrichment/judgments.jsonl8. classify-bids-and-boundary
extraction/audit_flags.json6. audit-and-reconcile (optional)

Output Artifacts

ArtifactDescription
master_rows.csv47-column review CSV (one row per event-actor link)
review/review_status.jsonReview status and flags for this deal
review/overrides.csvHeader-only CSV for reviewer corrections
Data/views/master.csvGlobal rebuild: all Data/deals/*/master_rows.csv concatenated

Tools

ToolPurpose
File readRead all input artifacts from disk
File writeWrite master_rows.csv, review_status.json, overrides.csv
File searchFind all Data/deals/*/master_rows.csv for global rebuild

Procedure

1. Read deal.json -> extract Group A (deal header) fields.
2. Read actors.jsonl + actors_extended.jsonl (if exists) -> build actor lookup.
3. Read events.jsonl -> build event list.
4. Read event_actor_links.jsonl -> build link list.
5. Read process_cycles.jsonl -> build cycle/round lookup.
6. Read judgments.jsonl -> build classification lookup.
7. Read audit_flags.json (if exists) -> build review flag inputs.

8. For each event:
   a. Look up event-actor links for this event.
   b. If links exist: emit one row per link (event + actor columns).
   c. If no links: emit one row with blank actor columns.
   d. Populate all 47 columns per the column spec.
   e. Derive bid_note from event_type using the mapping table.
   f. Derive review flags (approximate_date, missing_nda, etc.).

9. Sort rows: deal_slug -> event_date -> event_type priority -> actor_alias.
10. Write master_rows.csv with header + sorted rows.
11. Write review/review_status.json with status, flags, extraction date.
12. Write review/overrides.csv (header only).
13. Rebuild global Data/views/master.csv:
    - Find all Data/deals/*/master_rows.csv files.
    - Validate headers are consistent across all deals.
    - Concatenate all rows sorted by deal_slug.
    - Write to Data/views/master.csv.

Gate

master_rows.csv exists in Data/deals/<slug>/.

Failure Policy

Always succeeds if input artifacts exist. This is pure denormalization -- no judgment calls, no ambiguity. If an input artifact is missing, skip its columns (leave blank) and note in review_status.json.

Required Reading

  1. references/column-spec.md -- 47-column specification, sorting rules, bid_note mapping, review flag derivation, global master.csv rebuild

When not to use it

  • When Skills 1-8 have not completed.
  • When judgment, classification, or interpretation is required.
  • When an input artifact is missing and its columns should not be skipped.

Limitations

  • This skill always succeeds if input artifacts exist, even if they are incomplete.
  • It does not perform any judgment, classification, or interpretation.
  • It relies on `source_accession_number` + `source_text` for factual tracing.

How it compares

This skill performs a purely mechanical assembly of data without judgment or classification, ensuring a consistent and interpretation-free aggregation of processed information.

Compared to similar skills

render-review-rows side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
render-review-rows (this skill)05moNo flagsIntermediate
literature-review5592moReviewAdvanced
openalex-database487moReviewIntermediate
market-research-reports387moReviewAdvanced

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