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Latest snapshot2026-09-12USmethodology registry-public-v1
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113,018 tools
- remove_video_storageremoveVideoDBVideoDB
ConnectorrequiredContent & Design - render_timelinerenderVideoDBVideoDBConnectorrequiredContent & Design
- search_collectionsearchVideoDBVideoDBConnectorrequiredContent & Design
- search_rtstreamsearchVideoDBVideoDBConnectorrequiredContent & Design
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- search_videos_by_titlesearchVideoDBVideoDBConnectorrequiredContent & Design
- semantic_searchsemanticVideoDBVideoDBConnectorrequiredContent & Design
- set_rtstream_alert_statussetVideoDBVideoDBConnectorrequiredContent & Design
- set_rtstream_index_statussetVideoDBVideoDBConnectorrequiredContent & Design
- set_rtstream_scene_index_statussetVideoDBVideoDBConnectorrequiredContent & Design
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- set_rtstream_understanding_statussetVideoDBVideoDBConnectorrequiredContent & Design
- transcode_mediatranscodeVideoDBVideoDBConnectorrequiredContent & Design
- translate_transcripttranslateVideoDBVideoDBConnectorrequiredContent & Design
- understand_rtstreamunderstandVideoDBVideoDBConnectorrequiredContent & Design
- understand_videounderstandVideoDBVideoDBConnectorrequiredContent & Design
- update_collectionupdateVideoDBVideoDBConnectorrequiredContent & Design
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- upload_mediauploadVideoDBVideoDBConnectorrequiredContent & Design
- explain_indicatorexplainWhisperGraphWhisper SecurityConnectorrequiredSecurity
- explain_schemaexplainWhisperGraphWhisper SecurityConnectorrequiredSecurity
- identifyidentifyWhisperGraphWhisper SecurityConnectorrequiredSecurity
- list_workflowslistWhisperGraphWhisper SecurityConnectorrequiredSecurity
- queryqueryWhisperGraphWhisper SecurityConnectorrequiredSecurity
- read_docsreadWhisperGraphWhisper SecurityConnectorrequiredSecurity
- run_workflowrunWhisperGraphWhisper SecurityConnectorrequiredSecurity
- Fixed Income: Actual vs Projectedfixed · Compare actual vs projected prepayment data for MBS via YieldBook. BACKWARD-LOOKING historical analysis only.
USE WHEN: User asks for historical prepayment analysis, actual CPR/CDR history, actual vs projected comparison, or model accuracy assessment on MBS.
DO NOT USE FOR: Forward-looking prepayment projections (use fixed_income_risk_analytics with retrievePPMProjection), standard cashflows (use fixed_income_cashflow_analytics).
DIALS: If the user supplies prepay dials (globalSettings.prepayDials), you MUST also pass dialHeadStart (months) or the dials have no effect on the result — ask the user for the headstart if not given.LSEGLSEG
PluginoptionalFinance - Fixed Income: Bond Referencefixed · Retrieve bond reference (static/metadata) data via YieldBook Bond Indic API. Returns contractual and reference information about bonds without requiring calculations.
DO NOT USE FOR: Cashflow schedules, payment projections, amortization, or prepayment analysis — use fixed_income_cashflow_analytics instead. Do NOT use for scenario analysis, rate shocks, pricing, risk metrics, or any analytical calculation — use the appropriate analytics tool directly (fixed_income_scenario_analytics for scenarios/shocks, fixed_income_risk_analytics for pricing). Do NOT call this tool as a preliminary lookup step before running an analytics tool.LSEGLSEGPluginoptionalFinance
- Fixed Income: Cashflow Analyticsfixed · Calculate bond cashflow schedules via YieldBook Cashflow API. Returns payment dates, principal, interest, and prepayment projections.
USE WHEN: User asks for cashflows, cashflow schedules, amortization, payment projections, or prepayment analysis on bonds.
DO NOT USE FOR: Bond pricing/risk metrics (use fixed_income_risk_analytics), rate scenarios (use fixed_income_scenario_analytics), historical actual-vs-projected prepay (use fixed_income_actual_vs_projected).
MBS/TBA/CMO PREPAY DEFAULTS: For MBS, TBA, or CMO bonds (identifiers starting with FNMA, GNMA, FHLMC, FN, GN, G2, FHL, or containing -TBA/-GEN), ALWAYS include prepay: {"type": "Model", "rate": 100} per bond unless user specifies different prepay assumptions. Omitting prepay on these bonds causes "PrepayRate not specified" error.
FLOATER/FORWARDS: When user asks to "use forwards", apply floaterSettings: {useForwardIndex: true} to ALL bonds.
KEYWORDS: Cashflow section keyword is "dataPaymentList" — returned in columnar format {columns, rows}.LSEGLSEGPluginoptionalFinance
- Fixed Income: Curvesfixed · Retrieve interest rate curves via YieldBook Curves API. Returns par rates, spot rates, forward rates, and discount factors.
USE WHEN: User wants YieldBook-specific curve data (GVT, SWAP, SWAP_RFR, GVT_MUNI curves) as inputs for YieldBook calculations.
DO NOT USE FOR: General LSEG IR curves (use interest_rate_curve), credit curves (use credit_curve), FX forward curves (use fx_forward_curve).
SPECIFIC TENORS: set "terms" in years (2Y → [2]) and leave "expandCurve" false, which otherwise returns ~120 points.
TIME SERIES: send ONE call holding one curve entry per date, each with a unique curveId — never one call per date.
OUTPUT FORMAT: The "points" array in curve responses is returned in columnar format as {columns, rows} for token efficiency.LSEGLSEGPluginoptionalFinance
- Fixed Income: Historical Datafixed · Retrieve historical price/yield/OAS snapshots and time-series for TBA bonds via YieldBook.
USE WHEN: User asks for previous-close snapshot, historical prices, or a date-range time series of stored/recorded yield or OAS values on a bond (i.e. looking up what the yield/OAS was on a past date, not computing it now).
DO NOT USE FOR: Current pricing or risk analytics — computing price, yield, OAS, duration, convexity, DV01, or spreads as of today or with live/close curves (use fixed_income_risk_analytics); CMO bonds (FNMA origination-year.series form) are not supported.LSEGLSEGPluginoptionalFinance
- Fixed Income: Risk Analyticsfixed · Calculate current pricing and risk analytics (price, yield, OAS, duration, convexity, DV01, spreads, accrued interest) via YieldBook PY API for Government, Corporate, MBS/CMBS, ABS, Municipal, Callable/Putable, FRN, TIPS, Bond Future, and Swap instruments.
USE WHEN:
- If the user says run a PY / do a PY / run py on a bond, use THIS tool.
- If the user asks for projected speeds, forward-looking speeds, or prepayment projections on a bond or MBS without explicitly asking for actual-vs-projected history, use THIS tool.
DO NOT USE FOR: Cashflows/payment schedules (use fixed_income_cashflow_analytics), yield curves (use fixed_income_curves), rate shock/scenario analysis (use fixed_income_scenario_analytics), historical actual-vs-projected prepayment (use fixed_income_actual_vs_projected), single-bond QPS pricing (use bond_price), looking up what yield/OAS/price was on a past date or retrieving a time-series of stored historical values (use fixed_income_hist_data).
DATE OPTIONS (mutually exclusive):
- usePreviousClose=true: Use previous market close (default, most stable)
- useLiveData=true: Use live intraday market data
- pricingDate: Use specific historical dateLSEGLSEGPluginoptionalFinance
- Fixed Income: Scenario Analyticsfixed · Analyze bond performance under rate scenarios via YieldBook Scenario API. Supports parallel shifts, non-parallel curve twists, credit spread scenarios, and horizon analysis.
USE WHEN: User asks for rate scenario analysis, rate shocks, parallel/non-parallel curve shifts, bear/bull steepeners/flatteners, or horizon analysis on specific bonds. This is the ONLY tool for scenario analysis and rate shock analysis — call it directly without any prior bond reference lookup.
DO NOT USE FOR: Current price/yield without scenarios (use fixed_income_risk_analytics), yield curves (use fixed_income_curves), historical prepay analysis (use fixed_income_actual_vs_projected).
Only create the EXACT scenarios requested — do NOT add extra scenarios unless explicitly asked.
SCENARIO FORMAT: Each scenario MUST have scenarioID + scenarioTitle + either parallelShift (bp number) OR curveShifts [{year, value}] — use ONE, not both.LSEGLSEGPluginoptionalFinance
- Historical Pricing Summarieshistorical · To retrieve time series pricing Interday summaries data or Intraday summaries data(i.e. bar data). Optimize queries to minimize token usage: limit row count when possible.LSEGLSEGPluginoptionalFinance
- IXM: Compare Index Return Time Seriesixm · Compares historical index return time series data for multiple FTSE fixed income indexes (2-4 indices). Also supports comparing a saved custom project iteration against its base index when iterationId is provided — base indices are resolved automatically from the iteration settings. Returns performance comparison data at specified frequencies (daily/monthly) with optional currency conversion and hedging. IMPORTANT: This tool supports a maximum of 4 indices. If the user requests more than 4 indices, inform them that comparing more than 4 indices at a time is not supported and ask them to reduce the selection. Do NOT fall back to calling ixm_index_return_time_series multiple times as a workaround.LSEGLSEGPluginoptionalFinance
- IXM: Customise Indexixm · Creates a customized index variant with dedicated exclusions (countries, currencies, markets, ratings) or additional classifier buckets resolved from human-readable names, and returns comparison data (original vs. customized) in a chart-ready format. Accepts 1-10 unique base index IDs in baseIndexIds, which IXM combines into a single starting universe using its default weighting, plus one or more exclusion arrays. At least one exclusion family is required. The response always includes every requested base index; if any base index series is unavailable the whole request fails. Returns the same response shape as ixm_compare_index_return_time_series for rendering in the existing IXM chart widget.LSEGLSEGPluginoptionalFinance
- IXM: Index Return Time Series Dataixm · Retrieves historical index return time series data for a single FTSE fixed income index. Use this tool directly when the user specifies a known index (e.g. WGBI, EGBI, ABBI) — do NOT call ixm_list_indexes first. Currency conversion is handled via the baseCurrency parameter. Returns performance data at specified frequencies (daily/monthly) with optional currency conversion and hedging. Also supports customised index iterations via the iterationId parameter. IMPORTANT: When the user wants to compare multiple indices, always use ixm_compare_index_return_time_series instead. Do NOT call this tool multiple times as a workaround for comparison requests.LSEGLSEGPluginoptionalFinance
- IXM: Index Risk Time Seriesixm · Retrieves historical risk characteristics time series for FTSE fixed income indexes (e.g., Yield to Maturity, OAS, Effective Duration). Returns time series data for a specified risk metric.LSEGLSEGPluginoptionalFinance
- IXM: Index Sector Riskixm · Retrieve sector risk analysis data for a specific bond index, showing risk metrics (duration, convexity, spread duration) broken down by weighted average life sectors. Returns a structured grid with sector names and corresponding risk values. Requires a base index ID (e.g., S-IX-WGBI) and pricing date.LSEGLSEGPluginoptionalFinance
- IXM: Index Turnover Time Seriesixm · Retrieves historical turnover time series for FTSE fixed income indexes. Returns time series data for a specified turnover metric.LSEGLSEGPluginoptionalFinance
- IXM: List Customised Indexesixm · Lists saved customised-index iterations for the authenticated user, paginated. Returns iteration name, project name, base indices, asset class, base currency, and last modified date. Results are paged: by default only the first page (up to 30 rows) is returned. Use the optional page and pageSize inputs together with the response paging metadata (totalPages, hasNextPage) to retrieve all iterations. Use this tool when the user wants to browse or find a previously saved custom index.LSEGLSEGPluginoptionalFinance
- IXM: List Indexesixm · Use this tool ONLY to browse or discover available FTSE fixed income and equity indexes when the user does not already know which index to use. Do NOT call this tool if the user has already specified an index ID (e.g. WGBI, EGBI, ABBI, G7). Filters by asset class, region, quality, and weighting. Returns index tickers, descriptions, and classifications.LSEGLSEGPluginoptionalFinance
- IXM: Save Customised Indexixm · Saves a previously previewed customised index iteration. Called directly by the chart widget — not intended for LLM invocation.LSEGLSEGPluginoptionalFinance
- Lipper: Get Fund Infoget · PURPOSE
Provides fund factsheet information (key fund characteristics) by resolving a single fund - identified by Fund Name, PermID code or Lipper ID code - into its Lipper factsheet summary including official fund name, Lipper Global Classification, asset type, currencies, domicile, fund management company, launch date, legal structure, and investment objective. For ambiguous names it returns the data for the closest match (active, primary share class by default) along with a list of other candidate matches.
INPUT
- fundIdentifier: Fund Name, Fund Lipper ID, Fund PermID for Share Class or Portfolio (Parent, Sub-Fund) that will be used to identify the fund.
- fields: list of requested fields. Unless specified default_key_facts are: ShareClassId, ShareClassPermId, ParentId, ParentName, ShareClassName, AssetStatusName, AssetTypeName, AssetUniverseName, CurrencyOfRecordName, BaseCurrencyName, DomicileName, FundManagementCompanyName, LaunchDate, Objective, LegalStructureName, LipperGlobalClassificationName
OUTPUT
All or any specific fields out of the following: Share Class ID, Share Class Perm ID, Share Class Name, Asset Status, Asset Type, Asset Universe, Currency Of Record, Base Currency, Domicile, Fund Management Company, Launch Date, Fund Objective, Legal Structure, Lipper Global Classification.
USE WHEN
- User asks for "key data," "key facts," "factsheet," "fund info," "fund details," or "basic info" for a named fund, ETF, or investment trust, pension fund or insurance fund ("Show me the key data for Fidelity Asia Fund", "Find Blackrock Index Fund").
- User asks for one or more specific reference fields about a named or identified fund: classification, currency, domicile, manager, launch date, legal structure, or investment objective/strategy - including single-field, conversational phrasing ("When was X launched?", "What currency and domicile is X in?").
DO NOT USE WHEN
- User needs data that is not explicitly listed as OUTPUT (example of fund data that is out of scope: fund holdings, fund performance, returns, fund benchmark, ratings, NAV, or AUM).
- User refers to a security that is not a fund asset – e.g. Equity, Bond, Index, Company data.
- The identifier given is not supported (ISIN, SEDOL, CUSIP, RIC, or ticker (e.g. "IE00B4L5Y983," "QQQ") - this tool does NOT accept these and will fail. Resolve to a Lipper identifier first (see PREREQUISITES), or route ticker-only queries to an equity/security lookup tool instead.
- Query is about the issuing company/equity itself, not the fund , vehicle - use a general entity/equity search tool.,
ROUTING NOTES
- If the user supplies an ISIN, CUSIP, SEDOL, or RIC, first resolve it to a supported input type (Fund Name, Fund Lipper ID, Fund PermID for Share Class or Portfolio (Parent, Sub-Fund)).
- If the user needs data for multiple funds, break it into singular queries separately for each fund.LSEGLSEGPluginoptionalFinance
- Macroeconomics: Datamacroeconomics · Execute Datastream DSWS GetData queries for macroeconomic series and return normalized tabular results.
SEARCH-FIRST POLICY (IMPORTANT):
- This tool retrieves values only after the series mnemonic, field, or expression is known.
- If the mnemonic, datatype/field, or expression code is uncertain, call macroeconomics_instrument_discovery first. For Reuters poll concepts, call macroeconomics_metadata_discovery target="polls" first and select the statistic mnemonic that matches the request.
- Do NOT brute-force multiple guessed mnemonics/fields/expressions with repeated calls.
- If results are empty, mismatched, or NA-heavy, use macroeconomics_instrument_discovery to re-resolve and retry once with resolved values.
Request must include at least one entry in the requests array. Each entry is either a standard instruments + fields request or an expression-only request.
SERIES IDENTIFIER RULES:
- Economic mnemonics are fixed-width and dot-padded. Pass them exactly as returned, e.g. USGDP...D, CHGDP.Y%R. Do not strip, pad, or re-case them.
- MEASURE MISMATCH: if a series returns the wrong MEASURE - a LEVEL when a % change was wanted, or nominal vs real, or SA vs NSA - do NOT hand-edit the transformation or adjustment code. Re-resolve via macroeconomics_instrument_discovery and confirm by the series NAME. Use macroeconomics_metadata_discovery target="economic-patterns" to look up the standard pattern for a concept and the full transformation/adjustment-code legend.
- A value that looks like a mnemonic is passed through as-is; anything else is resolved via navigator/search, which is less reliable than a resolved mnemonic.
FIELD/DATATYPE RULES:
- X is the default datatype for Timeseries requests and works for economic series. X does NOT work for Snapshot requests.
- ES (economic series value) is the field for Snapshot requests on economic series.
- INVALID fields that always return NA or error: BID, ASK, DS, VALUE, CLOSE. Equity/FX fields such as P, MV, PE and ER do not apply to macroeconomic series.
- When in doubt about which field to use, call macroeconomics_metadata_discovery with target="datatypes".
EXPRESSION RULES:
- Use the expression field when you already have the final Datastream expression string, e.g. "PCH#(USGDP...D,-1Y)" or "300E(USGDP...D,12M)".
- Do not combine expression with instruments or fields. The expression string contains the executable calculation.
- Dynamic expressions call functions directly, e.g. "PCH#(USGDP...D,-1Y)" to derive a growth rate from a level series.
- Pre-built expressions use a discovered expression mnemonic with arguments, e.g. "300E(USGDP...D,12M)" after finding 300E via macroeconomics_metadata_discovery target="expressions"/"functions".
- Prefer a PUBLISHED growth series over computing one where both exist - resolve the "% change" series with macroeconomics_instrument_discovery first, and only calculate when no published series matches.
- Expression parameter metadata is limited. Instrument arguments are Datastream mnemonics; period/window arguments commonly use values such as 12M, -1M, -20D, -1Y; numeric arguments are plain numbers. DSWS validates final expression semantics.
- PERIOD UNITS MUST MATCH THE SERIES FREQUENCY. On a quarterly series a period given in months returns NO ROWS AND NO ERROR: MED#(USGDP...D,6M) is empty, MED#(USGDP...D,2Q) works. Use Q for quarterly series, M for monthly, Y for annual.
- Functions nest in Timeseries requests only, e.g. MED#(PCH#(USGDP...D,-1Y),2Q). A nested call in a SNAPSHOT expression is rejected by DSWS with "INVALID CODE" - use a single-level function there, e.g. PCH#(USGDP...D,-1Y), or run the nested form as a Timeseries and take the last row.
- The TIME date parameter anchors to the latest reported observation rather than a calendar date, which suits irregularly published macro series: VAL#(USGDP...D,TIME) is the latest US GDP value and works in both kinds. The displaced form VAL#(USGDP...D,TIME-3Q) (three quarters earlier) works in TIMESERIES ONLY - in a Snapshot it is rejected with "INVALID CODE"; use an ordinary displacement there instead, e.g. VAL#(USGDP...D,-1Y).
TWO KINDS AND HOW TO USE THEM:
1. Snapshot - a single point-in-time value per series. Payload: instruments + fields + kind="Snapshot". MUST use ES. Returns the latest available observation, so it works for monthly/quarterly/annual series without needing a date window.
2. Timeseries - values across a date range. Payload: instruments + fields + kind="Timeseries" with optional start/end/frequency. Use X. Match frequency to the series: forcing one the series is not published at returns sparse or NA-heavy rows.
EXAMPLE REQUEST PAYLOAD:
{
"requests": [
{ "instruments": "USGDP...D", "fields": "X", "start": "-3Y", "end": "0D", "frequency": "Quarterly", "kind": "Timeseries" },
{ "instruments": "USGDP...D", "fields": "ES", "kind": "Snapshot" },
{ "expression": "PCH#(USGDP...D,-1Y)", "start": "-5Y", "end": "0D", "frequency": "Quarterly", "kind": "Timeseries" }
]
}LSEGLSEGPluginoptionalFinance
- Macroeconomics: Instrument Discoverymacroeconomics · Discover macroeconomic series and the facets needed to narrow them, before retrieving values. Every request is scoped to Economics automatically - there is no category parameter.
Send one or more entries in "requests"; each carries its own "action" and is executed independently. BATCH aggressively - a synonym sweep across phrasings, or the same concept across several markets, belongs in ONE call rather than several round trips.
QUERY RULES (action="search"):
- Pass a keyword or short phrase, NOT a full question. Good: "Population", "Money Supply M3", "Producer Price Index". Bad: "What is the Population in Malaysia?".
- To scope by country prefer the eco_market facet - a HARD filter that surfaces every series in that market, including ones whose name never mentions the country. Putting the country in the query text is a WEAKER fallback: it matches only the series NAME, so it can MISS in-market series and ADMIT other markets.
- To resolve a known mnemonic, pass it as the "query" (e.g. "USGDP...D"); the mnemonic is a searchable field.
FACET FILTERS (action="search", "filters"):
- "filters" is an object of facet symbol -> exact value. KEYS must begin with "eco_" (unified economic facets) or "nav_" (Navigator facets). Other prefixes are rejected.
- Economics search draws on TWO sources: Navigator and a curated economic index. eco_* is the unified vocabulary covering both; a single eco_* key is applied across both automatically - you never pick sources yourself. Use nav_* only for Navigator dimensions with NO eco_ equivalent. Both families can be combined in the SAME "filters" object.
- Discover symbols with action="listFilters", then values with action="listFilterValues". Values must be EXACT strings from listFilterValues (e.g. "China (Mainland)", not "China"). nav_highrank / nav_medrank use "Y"/"N", not "Yes"/"No".
- Facets are a HARD narrowing mechanism. For dimensions absent from the series NAME (market, frequency, adjustment) a facet surfaces series a query term would miss - so facets improve recall, not just precision.
- Directly usable values: eco_frequency (Monthly|Quarterly|Annual; rare qualified variants "Weekly - Friday"|"Weekday (5 day)" - plain "Weekly"/"Weekday" are NOT valid), eco_seasonally_adjusted / eco_key_indicator / eco_headline (y|n), eco_forecast (Historical|Forecast), eco_activity (Active|Discontinued), eco_sector (National Accounts|External Sector|Money & Finance|Consumer Sector|Industry Sector|Labour Market|Government Sector|Prices|Surveys & Forecast|Commodities).
- Discover via listFilterValues: eco_market, eco_category_code, eco_currency, eco_unit, eco_source, eco_economic_type, eco_conversion_method, eco_scale. eco_source_contains is free text on the publisher (e.g. "central bank") and returns no value list - just pass a substring.
- Facets are AND-ed; unknown values are ignored and never fail the search.
- WHEN TO ADD FACETS: start with the query (+ eco_market). If the target still ranks low after a synonym sweep, add facets you are confident about - typically eco_frequency, eco_seasonally_adjusted, eco_sector (GDP->National Accounts, CPI->Prices, unemployment->Labour Market) - ONE at a time, confirming by the result NAME. A wrong or over-narrow facet can drop the correct series.
- NOT EVERY SERIES IS FACETABLE: some are surfaced only by keyword + eco_market. If a series never appears despite correct facets, stop adding facets and rely on the keyword/eco_market path, or retrieve it directly by mnemonic.
CHOOSING BETWEEN NEAR-IDENTICAL RESULTS (metadata.headline / metadata.keyIndicator):
- Each result carries metadata.headline and metadata.keyIndicator ("Y"/"N"). keyIndicator is BROAD - most economic series are "Y", so it barely discriminates. headline is NARROW: across variants of the SAME concept exactly one is "Y", marking the variant the SOURCE treats as standard - for volume aggregates the CONSTANT-price (real) seasonally adjusted series, not the current-price (nominal) one.
- RANK DOES NOT SURFACE IT: the headline variant routinely scores BELOW its siblings (Colombia imports - CBIMNGS.B current prices, headline "N", outranks CBIMNGS.D constant prices, headline "Y"; likewise USGDP...D and BDGDP...D). Taking the top hit therefore returns the NOMINAL series by default.
- RULE: when two or more results share a concept and differ mainly in price basis or adjustment (compare metadata.adjustmentFactorDesc - "Current prices" vs "Constant prices", SA vs NSA), LEAD with the headline="Y" series and NAME the alternatives you rejected. Never silently pick one.
- eco_key_indicator="y" / eco_headline="y" are HARD filters for the standard variant, but do NOT apply them blindly: transformed series - growth rate, "% change", "YoY", "MoM", targets/forecasts - are usually NOT flagged, so the filter EXCLUDES exactly what a rate-of-change request asked for. For those, search without it (or add the transformation term to the query) and pick by NAME.
- Growth-rate series are often published at a different frequency than the level, so avoid over-constraining eco_frequency.
READING MNEMONICS POSITIONALLY (heuristic - verify with the returned name):
- Mnemonics are fixed-width and dot-padded, e.g. USGDP...D: [market prefix][concept][transformation char][adjustment char]. First 2 chars = country (US, CH, JP); middle = concept (GDP, CP = consumer prices, UN = unemployment).
- The transformation code before the final char changes WHAT is measured: USGDP...D = "US GDP (AR) CONA" (the LEVEL) vs USGDP..SD = "US REAL GDP % CHANGE AT ANNUAL RATES" (the GROWTH RATE). Same concept, different measure - NOT interchangeable.
- The FINAL char is the ADJUSTMENT code and IS interchangeable across variants of the same series (real vs nominal, SA vs NSA). Match intent by the transformation code first, then pick the adjustment code, and always confirm with the result NAME rather than the code alone.
- YoY variants differ: a "% change y/y" series can be DISCRETE/quarterly (CHGDP.Y%R = "GDP QUARTERLY YOY % CHANGE") or CUMULATIVE/year-to-date (CHGDP%..C = "GDP Growth Rate, Cumulative, y/y"), which give different numbers for the same period. For a plain "GDP growth" ask prefer the discrete variant unless the user says cumulative/YTD, and confirm via the expandedName ("QUARTERLY" vs "YEAR TO DATE"). Use macroeconomics_metadata_discovery target="economic-patterns" to look up the standard pattern for a concept and the full transformation/adjustment-code legend.
SEARCH STRATEGY (action="search"):
- For a rate/change/growth request, put the transformation in the query ("GDP % change", "GDP annual rate", "CPI change"). A bare concept query ("GDP") tends to return LEVEL series and may not surface the % change series at all.
- Sweep transformation synonyms IN ONE BATCH; one phrasing is not enough. Search matches the series NAME, and naming differs by country, so the SAME concept needs DIFFERENT wording per market: China's series is named "Growth Rate" so "GDP growth" finds it at rank 1, but the US series is "REAL GDP % CHANGE AT ANNUAL RATES" so "GDP growth" returns NOTHING there - only "GDP % change" or "GDP annual rate". Send ["<concept> growth", "<concept> % change", "<concept> annual rate", "<concept> YoY"] per market as parallel requests and merge the candidates.
- Select by NAME and metadata.headline, not by rank or a single query. Over-fetch (maxResults 30-90) across the sweep and pick the result whose NAME matches the requested measure (level vs % change, YoY vs MoM, SA vs NSA).
- One country per request. For multi-country comparisons send one request per country, each with its own eco_market, in the same batch.
- Some specialized series (source-mean / "&" / NADJ variants) are unreachable by keyword search at any depth. If the expected series never appears, fall back to a close reachable equivalent confirmed via the NAME, or retrieve it directly by mnemonic.
- Search only resolves the input series. Calculations over them (regression, forecast, correlation, moving average) are a separate step: build the expression with macroeconomics_metadata_discovery target="expressions"/"functions" and run it with the data tool.
TYPICAL FLOW:
1. (optional) action="listFilters" to see available facets.
2. (optional) action="listFilterValues" with an eco_*/nav_* filterName to see valid values.
3. action="search" with a keyword (+ optional filters) to get the mnemonic - batch the synonym sweep here.
4. Pass the mnemonic to the data tool (use action="listDatatypes" first if you need the field code).
5. If the data tool returns empty rows, NA-heavy output, or mismatched instruments, return here to re-resolve - do NOT brute-force guessed mnemonics.
EXAMPLE - batched synonym sweep across two markets:
{ "requests": [
{ "action": "search", "query": "GDP % change", "maxResults": 30, "filters": { "eco_market": "United States" } },
{ "action": "search", "query": "GDP annual rate", "maxResults": 30, "filters": { "eco_market": "United States" } },
{ "action": "search", "query": "GDP growth", "maxResults": 30, "filters": { "eco_market": "China (Mainland)" } }
] }
EXAMPLE - discover facet values, then list datatypes:
{ "requests": [
{ "action": "listFilterValues", "filterName": "eco_market", "query": "United" },
{ "action": "listDatatypes", "identifier": "MYGDP...D", "count": 20 }
] }LSEGLSEGPluginoptionalFinance
- Macroeconomics: Metadata Discoverymacroeconomics · Discover the reference metadata needed to build macroeconomic data requests - economic field/datatype codes, expressions, functions, mnemonic patterns, and Reuters poll concepts.
Send one or more entries in "requests"; each carries its own "target" and a REQUIRED "query" (this is a catalog keyword search, not a full listing). Batch related lookups into ONE call. Datatype searches are scoped to Economics automatically - there is no category parameter. To list the datatypes available for one specific series instead, use macroeconomics_instrument_discovery action="listDatatypes".
TARGETS:
- "datatypes": economic field/datatype codes. The catalog is filtered to the ~156 economics datatypes, so results are macro-specific: X (universal timeseries default), ES (snapshot economic series), BDATE (base date), DISC (discontinued series), and the point-in-time release dates DREL1..DREL20.
- "expressions": pre-built expressions by name, code/mnemonic, formula terms, or parameter names (e.g. "z-score", "moving average", "300E"). A discovered mnemonic can be executed as e.g. "300E(USGDP...D,12M)".
- "functions": functions by name or code, used to build dynamic expressions such as "PCH#(USGDP...D,-1Y)".
- "economic-patterns": the standard economic mnemonic pattern for a concept. The catalog holds 74 curated concepts across 8 sectors (Money & Finance, Industry Sector, External Sector, Labour Market, National Accounts, Prices, Consumer Sector, Government Sector). QUERY WITH THE FULL CONCEPT NAME, NOT AN ABBREVIATION: "Consumer Price Index" matches, "CPI" returns nothing; "Unemployment Rate" matches, "jobless" does not. Returns concept -> X-synonym pattern rows (e.g. Gross Domestic Product -> GDP...X with valid adjustment codes D,B,C,A; Consumer Price Index -> CONPRCX; Unemployment Rate -> UN%TOTX) plus the adjustment-code legend (final mnemonic character: D=constant prices SA, B=current prices SA, etc.). Use it to INTERPRET/VALIDATE a resolved mnemonic (level vs % change, real vs nominal, SA vs NSA) or as a FALLBACK to construct the canonical mnemonic when keyword search fails - always confirm against the actual returned series, never fabricate blindly. If a concept returns no rows, retry with the full official name or a sector term before concluding it is absent.
- "polls": Reuters economic poll concepts, returning statistic-specific mnemonics. NOTE: polls are a SEPARATE universe from the Economics category - they are not category-scoped, so poll mnemonics will not appear in ordinary economic series search.
MACRO-RELEVANT CALCULATIONS (targets "functions" / "expressions"):
- Expressions and functions are domain-neutral and are NOT filtered to Economics, so results may include instruments outside the macro universe. The ones that matter for macroeconomic work are mostly transformations of a level series into a rate:
* PCH# - percentage change over a window, e.g. PCH#(USGDP...D,-1Y) for year-over-year growth from a level series.
* ACH# - actual (absolute) change over a window, when the level difference is wanted rather than a percentage.
* GRFL# / GRLS# - annualised growth rate, from first-and-last values or a least-squares trend line.
* MAV# - moving average, for smoothing volatile monthly indicators.
* LAG# - shift a series to align releases with different publication lags.
* CFY# / CFQ# / CFM# - calendar annual / quarterly / monthly value, to re-period a series.
* 300E - pre-built expression usable as 300E(<mnemonic>,<window>).
- Verify any code with target="functions" before using it; the list above is a starting point, not the full catalog.
- Prefer a published growth series over computing one where both exist: search for the "% change" series with macroeconomics_instrument_discovery first, and only fall back to a calculation when no published series matches.
TIPS:
- Expression/function parameter metadata is limited: instrument arguments are Datastream mnemonics (e.g. USGDP...D); period/window arguments commonly use values like 12M, -1M, -20D, -1Y. DSWS validates final expression semantics.
- Resolve field/expression/function codes here BEFORE requesting data; if a data request returns NA or errors for a field or expression, re-resolve here rather than guessing.
EXAMPLE - resolve a datatype and a poll concept in one call:
{ "requests": [
{ "target": "datatypes", "query": "release date", "limit": 20 },
{ "target": "polls", "query": "Argentina CPI monthly", "country": "Argentina", "frequency": "Monthly", "limit": 10 }
] }
EXAMPLE - interpret a mnemonic, then find a growth function:
{ "requests": [
{ "target": "economic-patterns", "query": "Consumer Price Index", "limit": 10 },
{ "target": "functions", "query": "percentage change", "limit": 10 }
] }LSEGLSEGPluginoptionalFinance
- MktData: Credit Curvecredit · Two-phase Credit Curve tool: (1) Call with country + issuerType to list curves. For Corporate, also provide at least one filter: name, sector, rating, or currency. Returns columnar {columns, rows}. (2) Call with name to calculate curve points (id is optional).LSEGLSEGPluginoptionalFinance
- MktData: Equity Volatility Surfaceequity · Generates equity volatility surfaces and smiles (single, or compared across two dates) for the definitions providedLSEGLSEGPluginoptionalFinance
What is Tool Explorer?
Tool Explorer indexes the callable tool names and descriptions attached to public registry profiles. It is useful for seeing what agents can actually invoke, not just which profile exists.
How do category and verb filters work?
Category filters use the live registry category rollup. Verb filters use the public tool insights rollup, so the page stays backed by the same read models as the tracker charts.
Why do auth requirements matter?
Auth requirements show whether a tool is likely usable without account connection, requires authentication, is private, or is unknown in the current snapshot.