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Search earnings transcripts

search_earnings_transcripts

Search earnings-call intelligence from live calls, decomposed into atomic, quote-anchored claims and Q&A pressure points — never a raw transcript dump.

Retrieval for "claims" and "pressure_points" is lexical, not semantic. A nonempty query uses an OR-of-tokens full-text candidate set; strict websearch_to_tsquery matches receive a fixed ranking boost, so strict matches rank ahead of loose partial-term matches. Lower-ranked rows may match only some query terms. If that filtered full-text search returns no rows, a trigram fallback handles typos and sub-word variants. Quoted phrases use websearch syntax, but synonyms are not inferred: try the company's own vocabulary ("capex" and "capital expenditure", segment names, abbreviations). An empty or partial result is not proof that management did not discuss a topic; coverage and vocabulary both matter.

Target and filter semantics:

  • "claims" (default) searches or browses normalized management/analyst claim rows. ticker, quarter_filter, claim_family, section, detail, and limit apply. claim_family matches primary or secondary families; section is "prepared_remarks" or "qa". Base rows include direction/value/unit where checkable, assertion_status, canonical_statement, verbatim_quote, speaker, speaker_role, section, transcript_id, source_block_index, qa_turn_id, and a source_link object.

  • "pressure_points" searches or browses what analysts pressed for and whether management confirmed, declined, deflected, or partially answered. ticker, quarter_filter, claim_family (the linked family), detail, and limit apply. section is ignored because every pressure point is from Q&A. Base rows include specific_ask, response_quality, refused_number, linked_family, linked_claim_id, verbatim_quote, transcript_id, source_block_index, qa_turn_id, and a source_link object.

  • "disclosure_profile" is a direct company lookup, not text search. The ticker is the first ticker value, or query when ticker is empty. Profiles are curated separately from transcript coverage, so a covered company may not have one; availability is "available" or "unavailable" accordingly. quarter_filter, claim_family, section, detail, and limit do not narrow it.

  • "coverage" is corpus inventory, not text search. ticker and limit apply; query, quarter_filter, claim_family, section, and detail do not narrow it. Rows report calls_covered, earliest_period, latest_period, latest_call_date (the call date of latest_period), claims, and pressure_points.

An empty query is a capped browse, not a completeness guarantee. Rows are ordered by newest fiscal period/call and then source-block (spoken) order within one call. Every response is limited to at most 50 rows, and a browse that reaches its limit may omit additional rows even if no truncation flag is present. For a latest-call note: (1) call "coverage" with one ticker, (2) read latest_period, (3) call "claims" with that ticker, quarter_filter=latest_period, query="", detail=true, and a deliberate limit, then (4) call "pressure_points" with the same ticker and quarter. Treat both browses as capped evidence, not a complete transcript. Narrow large result sets with ticker, quarter, target, claim_family, and (for claims) section. For media quotes, run_sql can read transcripts.appearance_claims.verbatim_quote; other transcript tables remain restricted.

Evidence rules: canonical_statement is normalized and must not be quoted as verbatim. Quote only verbatim_quote, with its speaker, role, ticker, and fiscal period. A […] inside verbatim_quote marks omitted transcript sentences between non-adjacent evidence spans: preserve it exactly when quoting, and never present text on either side of it as one continuous statement. When a quote is used, render source_link.source_label as the Markdown link text for source_link.source_url beside the claim. The label names the company, fiscal period, and earnings call transcript; never replace it with an ingestion vendor. Do not make a second call just to find a citation, do not invent a replacement when source_url is null, and do not call a document-level link exact context. source_locator still identifies the stored transcript block or Q&A turn. assertion_status is load-bearing: analyst_hypothesized is the analyst's framing, while mgmt_declined_to_confirm is a refusal, not a management assertion. Spoken call claims are a different source class from filed XBRL actuals (run_sql on the sec schema) and formally issued targets (the sec_guidance dataset); label them separately.

Examples:

  • Latest call: search_earnings_transcripts(query="", search_target="coverage", ticker="MU"), then repeat with search_target="claims", quarter_filter=<latest_period>, detail=true, limit=50, and finally with search_target="pressure_points" for the same ticker and quarter.

  • Cross-company theme: search_earnings_transcripts(query="capital expenditure capacity", search_target="claims", ticker="MU,NVDA", detail=true); inspect each returned row for topical support, do not assume every term matched, and retry vocabulary as needed.

  • Disclosure habits: search_earnings_transcripts(query="", search_target="disclosure_profile", ticker="MU").

claim_family codes: driver_attribution, forward_conviction, prior_view_revision, strategic_agreement, pricing_mechanics, demand_magnitude, capacity_milestone, competitive_positioning, cohort_behavior, cost_margin_bridge, capital_allocation, stated_risk_constraint, qa_dynamics, regulatory_policy, pipeline_backlog, commodity_hedging, ma_deal, labor_org. Topic paths (topic_path column) are rooted at: demand, supply_capacity, pricing, cost_margin, capital, competition, customer, product_roadmap, risk, governance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum 1-50 rows (default 15). This is a hard cap, not proof the result is complete; narrow by ticker, quarter, target, family, and claims section.
queryNoFor claims/pressure_points: lexical websearch text; strict matches rank above loose partial-term matches, with trigram fallback only when FTS returns no rows. Empty text browses capped rows. For disclosure_profile, it can supply the ticker when ticker is empty. Ignored by coverage.
detailNoFor claims, add structured_fields, secondary_families, period, time_horizon, conviction_qualifier, denominator, and falsifiable; for pressure_points, add tone_note. Ignored by disclosure_profile and coverage. The extractor's quantified flag is not published: it only records that the extractor wrote something into value, which the caller can already see in value itself.
tickerNoTicker, or a comma-separated list of tickers, for claims, pressure_points, and coverage; case-insensitive. Company names belong in company_name; pass only one of the two. A name passed here is still read as a name when it fits a stored company, and the response says so. Companies listed in India carry the NSE suffix ('RELIANCE.NS', 'INFY.NS') and companies listed in Switzerland carry '.SW' ('NESN.SW', 'ROP.SW'); a plain NSE or Swiss symbol is also accepted, but a symbol that is a US ticker ('INFY', 'ROP') selects the US listing. The response lists possible matches for a value that is not in the transcript corpus. disclosure_profile uses only the first ticker.
sectionNoprepared_remarks or qa; applies only to claims. Ignored for pressure_points because those rows are all Q&A, and ignored by lookup/inventory targets.
claim_familyNoClaim-family code. Matches primary/secondary families on claims and the linked family on pressure_points; ignored by disclosure_profile and coverage.
company_nameNoCompany name, or a comma-separated list of names, for claims, pressure_points, and coverage; case-insensitive ('nvidia', 'HP Inc', 'Ford Motor'). Each name resolves to the stored ticker(s) that match it best; the response reports the resolution and lists possible matches for a name that resolved to nothing. Pass either company_name or ticker, not both. disclosure_profile uses only the first resolved ticker.
search_targetNoclaims or pressure_points perform lexical retrieval/browse; disclosure_profile is a direct company lookup; coverage is corpus inventory.claims
company_filterNoDeprecated alias of ticker, kept for clients installed before the parameter was renamed. Pass ticker instead.
quarter_filterNoExact fiscal period such as FY2026Q3; applies to claims and pressure_points. Ignored by disclosure_profile and coverage. Pin this after coverage for a single-call browse.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint=false, idempotentHint=false, openWorldHint=false) disclose little operationally, but the description carries rich behavior: lexical-not-semantic retrieval, OR-of-tokens candidate sets, websearch_to_tsquery boost, trigram fallback, 50-row hard cap, newest-period/source-block ordering, and a full evidence/citation rulebook. This is substantially more than the annotations convey. (Minor tension: the description describes purely read-style retrieval while readOnlyHint=false, but it never asserts read-only-ness, so this is not a formal contradiction.)

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then retrieval mechanics, target semantics, evidence rules, and examples — a sensible progressive structure for a genuinely complex 10-parameter, 4-target tool. It is dense and somewhat repetitive (the 50-row cap and 'capped browse' caveat are restated), but nearly every sentence carries operational weight.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return fields need not be enumerated, yet the description still maps each target's base-row fields and the evidence/citation rules an agent needs to render results correctly. Given the tool's complexity, this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all ten parameters; baseline is 3. The description adds value beyond the schema by enumerating the 19 `claim_family` codes and the root `topic_path` values (absent from the schema) and by giving a per-target applicability matrix (which of ticker/quarter_filter/claim_family/section/limit narrow each target).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Search earnings-call intelligence'), specifies the unit of retrieval ('atomic, quote-anchored claims and Q&A pressure points'), and explicitly distinguishes itself from a raw transcript dump and from the `run_sql`/`sec`/`sec_guidance` alternatives. An agent can identify the tool's scope without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use routing across the four `search_target` modes, names sibling alternatives (`run_sql` for media quotes and XBRL actuals, the `sec_guidance` dataset for targets), gives a step-by-step latest-call recipe, and states exclusions ('do not make a second call just to find a citation'). Alternatives and negative conditions are both spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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