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* Legislative-effectiveness aggregator.
*
* Pure helpers that turn the per-source EP API payloads consumed by
* `analyze_legislative_effectiveness` into deterministic effectiveness metrics
* keyed by a subject MEP. Kept side-effect-free so the tool handler can fan
* out network calls under `Promise.allSettled`, then defer aggregation to a
* single synchronous step that is easy to unit-test.
*
* **Inputs:** raw `Procedure`, `AdoptedText`, `LegislativeDocument`, and
* `ParliamentaryQuestion` arrays (already filtered to a date window upstream).
*
* **Outputs:** {@link LegislativeMetrics} — counts of reports authored,
* opinions delivered, amendments tabled/adopted, questions asked, and the
* derived legislative success rate.
*
* ISMS Policy: SC-002 (Input Validation), AC-003 (Least Privilege).
*
* @module utils/effectivenessAggregator
*/
import type { Procedure, AdoptedText } from '../types/ep/activities.js';
import type { LegislativeDocument } from '../types/ep/document.js';
import type { ParliamentaryQuestion } from '../types/ep/question.js';
/**
* Effectiveness metrics computed from real EP data.
*
* Each field is a count derived from a single EP API source; the
* `legislativeSuccessRate` is the only derived ratio.
*/
export interface LegislativeMetrics {
/** Procedures where the subject appears as rapporteur. */
reportsAuthored: number;
/** Procedures where the subject acts as shadow- or opinion-rapporteur. */
opinionsDelivered: number;
/** Plenary-session document items authored by the subject. */
amendmentsTabled: number;
/** Amendment-typed document items authored by the subject that reached an ADOPTED status. */
amendmentsAdopted: number;
/** Parliamentary questions filed by the subject. */
questionsAsked: number;
/**
* Percentage of subject-attributed procedures that resulted in an
* adopted text (0-100, two-decimal precision).
*/
legislativeSuccessRate: number;
}
/**
* Deterministic ordering payload returned alongside the counts so callers
* (tests, downstream tools) can audit which records contributed.
*
* Lists are sorted by stable identifier ascending so two runs over the same
* input produce identical output regardless of fetch order.
*/
export interface AggregatedAttributions {
/** Procedure IDs counted as reports authored, ascending. */
reportProcedureIds: string[];
/** Procedure IDs counted as opinions delivered, ascending. */
opinionProcedureIds: string[];
/** Document IDs counted as amendments tabled, ascending. */
amendmentDocumentIds: string[];
/** Document IDs counted as adopted amendments, ascending. */
amendmentAdoptedDocumentIds: string[];
/** Parliamentary question IDs counted, ascending. */
questionIds: string[];
}
/**
* Combined aggregator result.
*/
export interface AggregationResult {
metrics: LegislativeMetrics;
attributions: AggregatedAttributions;
/** Number of distinct procedures attributed to the subject. */
attributedProcedureCount: number;
/** Number of attributed procedures with a matching adopted text. */
proceduresWithAdoptedText: number;
}
// ---------------------------------------------------------------------------
// Identifier normalisation
// ---------------------------------------------------------------------------
/**
* Strip the `person/` prefix and surrounding whitespace from a MEP identifier.
*
* The EP API returns MEP ids in several forms (`person/124936`, `124936`,
* `MEP-124936`). We normalise to the bare numeric token plus the original
* string so substring matches against author fields succeed regardless of the
* representation chosen by a given endpoint.
*
* @internal
*/
export function normaliseMepIdTokens(id: string): string[] {
const raw = id.trim();
if (raw === '') return [];
const tokens = new Set<string>([raw.toLowerCase()]);
const slashIdx = raw.lastIndexOf('/');
if (slashIdx >= 0 && slashIdx < raw.length - 1) {
tokens.add(raw.slice(slashIdx + 1).toLowerCase());
}
const dashIdx = raw.lastIndexOf('-');
if (dashIdx >= 0 && dashIdx < raw.length - 1) {
tokens.add(raw.slice(dashIdx + 1).toLowerCase());
}
return [...tokens].filter((t) => t.length > 0);
}
/**
* Tolerant author/MEP match.
*
* Returns `true` when any normalised token from `mepId` matches the candidate
* exactly, or when the candidate contains a normalised token as a substring
* (case-insensitive). Empty / undefined candidates never match.
*
* @internal
*/
export function matchesMep(candidate: string | undefined | null, mepTokens: string[]): boolean {
if (candidate === undefined || candidate === null || candidate === '') return false;
if (mepTokens.length === 0) return false;
const c = candidate.toLowerCase();
for (const token of mepTokens) {
Iif (token === '') continue;
if (c === token) return true;
// Require the token to be at least 2 chars to avoid spurious substring
// matches against very short identifiers like "1".
if (token.length >= 2 && c.includes(token)) return true;
}
return false;
}
/**
* Build the set of identifier tokens that we treat as "authored by" the
* subject. For an MEP this is the MEP id plus name tokens (so rapporteur
* name-based matching works); for a committee it is the union of the
* committee's member IDs.
*/
export function buildSubjectTokens(
subjectId: string,
committeeMemberIds?: readonly string[],
subjectName?: string,
): string[] {
const result = new Set<string>();
for (const token of normaliseMepIdTokens(subjectId)) result.add(token);
if (subjectName !== undefined && subjectName.trim() !== '') {
// Add the full name and individual name parts as match tokens.
// The rapporteur field in procedures contains human-readable names
// like "Jane Andersson" so we need name-based matching.
const fullName = subjectName.trim().toLowerCase();
result.add(fullName);
// Add individual name parts (≥3 chars) for substring matching
for (const part of fullName.split(/\s+/)) {
if (part.length >= 3) result.add(part);
}
}
if (committeeMemberIds !== undefined) {
for (const memberId of committeeMemberIds) {
for (const token of normaliseMepIdTokens(memberId)) result.add(token);
}
}
return [...result];
}
// ---------------------------------------------------------------------------
// Source filters
// ---------------------------------------------------------------------------
/** Inclusive ISO-date window check; missing/invalid dates are treated as out-of-window. */
function inWindow(date: string | undefined | null, dateFrom: string, dateTo: string): boolean {
if (date === undefined || date === null || date === '') return false;
const d = date.length >= 10 ? date.slice(0, 10) : date;
return d >= dateFrom && d <= dateTo;
}
/**
* Round a number to 2 decimal places, returning `0` when the input is not
* finite. Used pervasively for percentage / ratio fields so the public
* envelope never emits `NaN` or `Infinity`.
*/
export function roundToTwoDecimals(value: number): number {
if (!Number.isFinite(value)) return 0;
return Math.round(value * 100) / 100;
}
/** Shadow / opinion rapporteur fingerprints. */
const SHADOW_OR_OPINION_KEYWORDS = ['shadow', 'opinion'];
/**
* Decide whether a procedure attributes the subject as the primary rapporteur
* vs. a shadow- or opinion-rapporteur, vs. neither. Returns `null` when the
* procedure carries no recognisable subject attribution.
*
* Heuristics:
* - `rapporteur` substring match (case-insensitive) against the subject's
* normalised tokens promotes the procedure to "report authored".
* - Combined with a `shadow` / `opinion` token in the same field, the
* procedure is reclassified as "opinion delivered".
* - `responsibleCommittee` is **not** sufficient on its own — it only enters
* the committee aggregation path via member-MEP attribution.
*/
function classifyProcedureRole(
procedure: Procedure,
mepTokens: string[],
): 'report' | 'opinion' | null {
// Defensive: TypeScript types `rapporteur` as `string`, but runtime EP API
// payloads occasionally arrive with the field missing or null. Treat any
// falsy value as "no attribution" so the aggregator never crashes on a
// malformed item.
const rapporteur = procedure.rapporteur;
if (!rapporteur) return null;
const matched = matchesMep(rapporteur, mepTokens);
if (!matched) return null;
const lower = rapporteur.toLowerCase();
const hasOpinion = SHADOW_OR_OPINION_KEYWORDS.some((k) => lower.includes(k));
if (hasOpinion) return 'opinion';
// Default to "report" when the rapporteur field plainly names the MEP
// (with or without a `rapporteur` qualifier). The opinion/shadow check
// above already separated minority roles.
return 'report';
}
/**
* Decide whether a plenary-session document item should be counted as an
* amendment authored by the subject. We look at:
* - `authors` array (preferred MEP attribution)
* - document `type` (e.g., `AMENDMENT`, `REPORT_AMENDMENTS`)
* - document `status` for the adoption flag (`ADOPTED` substring)
*/
function isSubjectAmendment(doc: LegislativeDocument, mepTokens: string[]): boolean {
const type = doc.type.toUpperCase();
if (!type.includes('AMENDMENT')) return false;
const authors = Array.isArray(doc.authors) ? doc.authors : [];
return authors.some((author) => matchesMep(author, mepTokens));
}
function isDocumentAdopted(doc: LegislativeDocument): boolean {
return doc.status.toUpperCase().includes('ADOPTED');
}
// ---------------------------------------------------------------------------
// Aggregator
// ---------------------------------------------------------------------------
/**
* Inputs to {@link aggregateLegislativeEffectiveness}.
*/
export interface AggregatorInputs {
/** Subject identifier (MEP ID or committee abbreviation). */
subjectId: string;
/**
* Optional human-readable subject name (e.g. MEP full name). When provided,
* enables rapporteur name-based matching against the procedure's `rapporteur`
* field (which carries human-readable text like "Jane Andersson").
*/
subjectName?: string;
/**
* Optional list of committee member MEP IDs. When provided, the aggregator
* treats any rapporteur/author hit against a member as a hit for the
* committee subject.
*/
committeeMemberIds?: readonly string[];
/** Inclusive ISO-date window for filtering procedures, documents, and questions. */
dateFrom: string;
/** Inclusive ISO-date window upper bound. */
dateTo: string;
/** Procedures fetched from `/procedures`. */
procedures: readonly Procedure[];
/** Adopted texts fetched from `/adopted-texts`. */
adoptedTexts: readonly AdoptedText[];
/** Plenary-session document items fetched from `/plenary-session-documents-items`. */
plenaryDocumentItems: readonly LegislativeDocument[];
/** Parliamentary questions fetched from `/parliamentary-questions`. */
questions: readonly ParliamentaryQuestion[];
}
/**
* Compute deterministic effectiveness metrics from the provided EP payloads.
*
* The function is pure: it never mutates its arguments, never throws, and
* produces stable output for stable input. Empty inputs return zero metrics
* (not `NaN`) so the surrounding tool can safely surface partial-source
* outages.
*
* @param inputs - raw EP arrays plus subject metadata
* @returns aggregated metrics + per-record attributions, sorted ascending
*
* @example
* ```typescript
* const result = aggregateLegislativeEffectiveness({
* subjectId: 'person/124936',
* dateFrom: '2024-01-01',
* dateTo: '2024-12-31',
* procedures, adoptedTexts, plenaryDocumentItems, questions,
* });
* // result.metrics.reportsAuthored, result.metrics.legislativeSuccessRate, ...
* ```
*/
interface ProcedureClassification {
reportProcedures: Set<string>;
opinionProcedures: Set<string>;
}
function classifyProcedures(
procedures: readonly Procedure[],
tokens: string[],
dateFrom: string,
dateTo: string,
): ProcedureClassification {
const reportProcedures = new Set<string>();
const opinionProcedures = new Set<string>();
for (const proc of procedures) {
if (!inWindow(proc.dateLastActivity, dateFrom, dateTo)
&& !inWindow(proc.dateInitiated, dateFrom, dateTo)) {
continue;
}
const role = classifyProcedureRole(proc, tokens);
if (role === 'report') reportProcedures.add(proc.id);
else if (role === 'opinion') opinionProcedures.add(proc.id);
}
return { reportProcedures, opinionProcedures };
}
function buildAdoptedRefSet(
adoptedTexts: readonly AdoptedText[],
dateFrom: string,
dateTo: string,
): Set<string> {
const adoptedRefs = new Set<string>();
for (const text of adoptedTexts) {
Iif (!inWindow(text.dateAdopted, dateFrom, dateTo)) continue;
const ref = text.procedureReference.trim();
Eif (ref !== '') adoptedRefs.add(ref);
}
return adoptedRefs;
}
function countProceduresWithAdoption(
procedures: readonly Procedure[],
attributedIds: ReadonlySet<string>,
adoptedRefs: ReadonlySet<string>,
): number {
let count = 0;
for (const proc of procedures) {
if (!attributedIds.has(proc.id)) continue;
const ref = proc.reference.trim();
if ((ref !== '' && adoptedRefs.has(ref)) || adoptedRefs.has(proc.id)) {
count += 1;
}
}
return count;
}
function classifyAmendments(
items: readonly LegislativeDocument[],
tokens: string[],
dateFrom: string,
dateTo: string,
): { amendmentIds: Set<string>; amendmentAdoptedIds: Set<string> } {
const amendmentIds = new Set<string>();
const amendmentAdoptedIds = new Set<string>();
for (const doc of items) {
if (!inWindow(doc.date, dateFrom, dateTo)) continue;
if (!isSubjectAmendment(doc, tokens)) continue;
amendmentIds.add(doc.id);
if (isDocumentAdopted(doc)) amendmentAdoptedIds.add(doc.id);
}
return { amendmentIds, amendmentAdoptedIds };
}
function classifyQuestions(
questions: readonly ParliamentaryQuestion[],
tokens: string[],
dateFrom: string,
dateTo: string,
): Set<string> {
const ids = new Set<string>();
for (const q of questions) {
if (!inWindow(q.date, dateFrom, dateTo)) continue;
if (!matchesMep(q.author, tokens)) continue;
ids.add(q.id);
}
return ids;
}
function sortedAscending(items: ReadonlySet<string>): string[] {
return [...items].sort((a, b) => a.localeCompare(b));
}
export function aggregateLegislativeEffectiveness(inputs: AggregatorInputs): AggregationResult {
const tokens = buildSubjectTokens(inputs.subjectId, inputs.committeeMemberIds, inputs.subjectName);
const { reportProcedures, opinionProcedures } = classifyProcedures(
inputs.procedures, tokens, inputs.dateFrom, inputs.dateTo,
);
const adoptedRefs = buildAdoptedRefSet(inputs.adoptedTexts, inputs.dateFrom, inputs.dateTo);
const attributedIds = new Set<string>([...reportProcedures, ...opinionProcedures]);
const proceduresWithAdoptedText = countProceduresWithAdoption(
inputs.procedures, attributedIds, adoptedRefs,
);
const { amendmentIds, amendmentAdoptedIds } = classifyAmendments(
inputs.plenaryDocumentItems, tokens, inputs.dateFrom, inputs.dateTo,
);
const questionIds = classifyQuestions(inputs.questions, tokens, inputs.dateFrom, inputs.dateTo);
const reportProcedureIds = sortedAscending(reportProcedures);
const opinionProcedureIds = sortedAscending(opinionProcedures);
const amendmentDocumentIds = sortedAscending(amendmentIds);
const amendmentAdoptedDocumentIds = sortedAscending(amendmentAdoptedIds);
const sortedQuestionIds = sortedAscending(questionIds);
const attributedProcedureCount = attributedIds.size;
const legislativeSuccessRate = attributedProcedureCount > 0
? roundToTwoDecimals((proceduresWithAdoptedText / attributedProcedureCount) * 100)
: 0;
return {
metrics: {
reportsAuthored: reportProcedureIds.length,
opinionsDelivered: opinionProcedureIds.length,
amendmentsTabled: amendmentDocumentIds.length,
amendmentsAdopted: amendmentAdoptedDocumentIds.length,
questionsAsked: sortedQuestionIds.length,
legislativeSuccessRate,
},
attributions: {
reportProcedureIds,
opinionProcedureIds,
amendmentDocumentIds,
amendmentAdoptedDocumentIds,
questionIds: sortedQuestionIds,
},
attributedProcedureCount,
proceduresWithAdoptedText,
};
}
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