Investigation Review Hub Gap Analysis

Investigation Review Hub — Gap Analysis & Remediation Dashboard

These tasks ask for one JSON object (no prose) that conforms to a task-specific input/payloads/answer_template.json. The template defines the exact top-level keys, section lists, item fields, enum choices, ordering rules, and numeric precision. The answer is scored by exact field/value match, so precision matters more than narrative quality.

Source of record

The Investigation Review Hub is a read-only SQL hub. The base URL, the access header and key, and the list of allowed endpoints are in the task's environment_access.md (and usually restated in the payload context file) — read them from the task, do not assume or hardcode them. Workflow:

1. Fetch the hub's schema endpoint to learn the tables and columns.
2. Use the read-only SQL query endpoint (with the task's access header/key) to SELECT each table filtered by the task's matter_id.

The hub tables (consistent across matters):

Never inspect local environment source files, database files, seeds, manifests, or setup scripts — only the running hub endpoints and the task-local payload files.

Critical: separate SIGNAL from NOISE

Every matter is seeded with realistic distractor records. Including them as findings or counting them in metrics produces wrong answers. Filter ruthlessly.

Signal records (include)

• Explicitly-named IDs with a descriptive suffix, e.g. SRC-SENT-ALDEN-PHONE, PRIV-NORTH-LOG-GAP, QC-GRAY-MISCODED-PRIV, RET-ALLOY-BOX-POST, DOC-ALLOY-BID-EMAIL-1. The ID pattern is {TYPE}-{MATTERCODE}-{DESCRIPTOR}.

Noise records (exclude)

• Generic sequential IDs like SRC-SENTINELGJ-001, PRIV-GRAYCLIFFS-002, RET-HARBORSTON-003. The ID pattern is {TYPE}-{MATTERCODE}-NNN.
• Hedging notes confirm noise: "routine", "no production-impacting issue has been escalated yet", "Review team marked this item for follow-up but not immediate remediation", "Privilege sample has ordinary review variance", "Entry included to create similar labels across matters", "Finding is similar to escalated records in another matter", "Review manager requested re-sampling before escalation", "Potential issue was remediated by archive collection", "Source map entry has minor metadata normalization issues", "Collection status differs between custodian tracker and vendor load report", "Requires matter-level filtering because similar issue labels appear across matters".

Cross-check (definitive)

The remediation_actions table lists the signal record set explicitly:

• Non-noise actions (e.g. ACT-SENTINELGJ-001, ACT-ALLOYWORKS-017) target exactly the signal records via target_ref. These are your finding/risk record IDs and the basis for the action plan.
• Noise actions have NOISE in the action_id and description "Routine action included as realistic operational noise." Exclude them entirely.

The set of signal records = the set of target_ref values from non-noise remediation_actions. This is the single most reliable signal detector — use it.

Building the answer

1. Carry hub-exact fields straight through

Record IDs, category_code/affected_categories, integer counts (doc_count, withheld_count, logged_count, volume_count), dates (event_date, hold_date), policy_section, retention_period_months, record_type, source_type, custodian_name, third_party flag → map directly. These are the fields most likely to match exactly — get them verbatim.

• unlogged_count = withheld_count − logged_count.
• affected_categories/category_impacts: split the comma string, sort ascending.
• source_refs/record_refs: the finding's own anchoring ID plus any source_ref the hub links (e.g. a QC finding's source_ref document IDs). Sort ascending.

2. Map hub status/issue vocabulary to the template enums

The hub uses its own vocabulary; map to the exact enum strings in the template. Common mappings (verify against the specific template's enum list):

• Retention status: system_loss→active_system_loss, retained→preserved_available, available→available_archive, post_hold_partial_recovery→post_hold_loss, should_exist_missing/policy_destroyed_pre_hold/post_hold_loss/auto_purged→same.
• Privilege issue: incomplete_log→privilege log gap, over_designated→privilege miscoding/downgrade, third_party_waiver→third-party waiver, miscoded_privilege→privilege miscoding.
• QC issue: miscoded_nonresponsive/zero_claim_contradiction→responsiveness miscode, miscoded_privilege→privilege miscoding.
• Source status: lost→lost/destroyed, not_collected→not_collected, available→available_archive, partial_collection→partial.

3. Interpreted fields (no direct hub value — derive consistently)

• cutoff_date = the matter hold_date (the retention-compliance cutoff). Do not leave it null when a hold_date exists. (Confirmed: setting it to null breaks records.)
• risk_level = preservation risk, not the remediation severity: policy_destroyed_pre_hold→low (policy-compliant, no preservation risk), post_hold_loss→high/critical, should_exist_missing→medium, system_loss/auto_purged→medium, archive_available→medium.
• severity (when separate from risk_level): take from the hub severity field of the remediation action / QC finding.
• priority: copy the hub priority (P0/P1/P2/P3) verbatim.
• priority_rank: P1 before P2; within a tier, follow the hub action_id order. Rank 1 = highest.
• production_impact: lost/destroyed source→source_lost; not-collected source→source_missing; miscoded/non-produced doc→not_produced/recode_needed/ underproduced; withheld-unlogged→withheld_unlogged; privilege waiver→privilege_exposure; available archive→source_available.
• third_party (string or null): the recipient name from the note (e.g. "Derek Winslow", "trial consultant") when third_party=1; else null.

4. Owner mapping

Hub owner strings rarely match the enum exactly. Map by closest meaning and reuse the same mapping across actions for the same matter:

5. Action-type mapping (hub action_type → template action_type enum)

• supplemental_collection on a lost/destroyed source → forensic_recovery or disclose_preservation_issue.
• supplemental_collection on a not-collected personal source → collect_personal_device / collect_source.
• supplemental_collection on an archive → collect_archive / search_archive.
• privilege_rework on incomplete log → supplement_privilege_log; on over-designation → privilege_recode_and_log / recode_and_produce; on waiver → waiver_assessment_and_disclosure.
• qc_remediation → qc_remediation (when the enum has it) else recode_and_produce else quality_control_review.
• retention_exception_review → disclose_preservation_issue (post-hold loss), locate_missing_record (should-exist-missing), restore_from_backup (system loss), no_action_policy_loss (policy-destroyed-pre-hold).

6. Metrics

• Count signal records only unless a metric description explicitly broadens scope.
• "selected incomplete-log blockers" / "selected" qualifier → only the material/signal privilege entries that are incomplete-log blockers (withheld_count > logged_count). If a matter has no signal incomplete-log entry, the privilege withheld/logged/unlogged metrics are 0.
• Box/file counts: sum volume_count over signal events with the matching volume_unit.
• *_count category metrics: size of the union of affected_categories across signal records.
• production_ready / rolling_production_ready: false if any critical/high signal gap exists, else true.
• The metrics block tends to be scored as a unit — one wrong metric value can fail the whole block, so every metric must be correct simultaneously. Recompute each carefully and double-check ambiguous ones. Example: destroyed_lab_archive_box_count is "boxes for the destroyed records source named in the task, or 0 when not measured in boxes" — read the description literally; if the matter's destroyed source is not a lab archive it may be 0 even when other boxes were destroyed.

7. Section-specific guidance

• Findings / top_risks: one record per signal gap/defect, finding_id/risk_id = the anchoring hub record ID. Available archives usually belong in retained_or_available_sources, not in risks — but if archive_available is a valid issue_type, an available archive may also appear as a remediable risk. Check whether the matter's available-archive source should be counted in top_risk_count.
• Category statuses / coverage: one entry per category with a material non-complete status (categories touched by ≥1 signal record). open_issue_count = number of signal records touching that category.
• Action plan / priority_actions: one per non-noise remediation_action. target_refs = the action's target_ref (plus linked records); due_days from the hub.
• retained_or_available_sources: sources with status = available/archive — the remediation paths. limits_loss_for_categories = categories the archive actually covers.

8. Ordering

Apply every ordering_rules entry from the template: sort lists by the specified key ascending (finding_id, category_code, source_id, priority_rank/rank, target_id). Sort every category-code list ascending within items.

Validation before finalizing (do this every time)

The answer is scored by exact field/value match against a gold answer. Two consequences:

1. Prefer the hub's literal value for direct fields (e.g. volume_unit="report" or "files", record_type, source_type) even when that value is not in the template's enum — the gold is built from the same hub data and likely uses the same literal. Do not "correct" a hub value into a different enum member unless the field is interpreted (no hub value) or the hub value is clearly a status to be mapped.
2. Enums guide interpreted fields only — for status/issue/action/owner fields with no direct hub value, use an enum member (that is what the gold maps to).

Run reference/validate.py to confirm: all required top-level keys present; every list item has all item_required_keys; every metrics required_keys present; integers are integers; nullable fields are null or the right type. The validator warns on values not in the template's enum — treat each as a deliberate decision (keep the hub literal, or map to an enum member), not an automatic error.

Reference files

• reference/hub_tables.md — full table/column reference and query patterns.
• reference/signal_vs_noise.md — detailed signal/noise detection with the noise-note catalog.
• reference/enum_mappings.md — consolidated hub→enum mapping tables.
• reference/validate.py — a validator script that checks an answer against a template's enums, required keys, and types.

Approach summary

1. Read prompt + answer_template.json + payload context → note matter_id, required keys, enums, ordering rules.
2. Query the hub for all 9 tables filtered by matter_id.
3. Determine the signal record set from non-noise remediation_actions.target_ref.
4. Build each section from signal records: carry hub-exact fields, map enums, derive interpreted fields (cutoff_date=hold_date, risk_level=preservation risk).
5. Compute metrics from signal records only (respect "selected" qualifiers).
6. Order per template rules.
7. Validate enums/keys/types programmatically.
8. Emit one JSON object, no prose.