research-report-interpretation

name	research-report-interpretation
description	Interpret sell-side, institutional, expert, or investor research by extracting claims, assumptions, valuation drivers, verification needs, and thesis impact.

Research Report Interpretation Skill

这个 skill 用于解读券商、卖方、机构、专家或投资者研究报告。它的目标不是复述研报，而是把一份报告拆成可验证 claim、隐含假设、预期变量、估值驱动和对 Mira thesis 的增量影响。

研报在 Mira 中默认是 sellside_and_expert_research，通常是 L3 secondary / signal。它可以帮助识别框架、预期差、变量优先级、估值方法和叙事变化，但不能替代公司披露、监管文件、官方数据、市场数据或可复算模型。

Use When

• 用户提供或指定一份券商研报、机构研报、rating change、target price update、initiation note、industry note、专家研究、投资者信或研究 PDF。
• 用户问“这篇研报怎么看 / 靠谱吗 / 有什么新东西 / 对 thesis 有什么影响”。
• 需要从研报中提取可复用方法、变量框架或预期差线索，但当前任务仍围绕某个研究对象，而不是纯方法论研究。
• 需要把研报结论与已有 Mira thesis、company filing、earnings package、consensus proxy 或市场定价做差异检查。

如果用户问的是“这个研究方法本身是否值得纳入 Mira”，优先进入 loops/methodology-research-loop.md。如果研报解读触发 thesis 状态变化，再 handoff 到 loops/thesis-update-loop.md 或 loops/event-delta-loop.md。

Required Inputs

• research_object: ticker、company、industry、macro asset 或 methodology object。
• market_scope
• time_boundary
• report_title
• provider_or_submitter
• author_or_team，如可得
• report_date 或明确的 source_gap
• report_type: initiation、update、rating_change、target_price_update、industry_note、thematic_note、expert_research、investor_letter、other
• access_route: public_on_demand、user_material、authorized_provider 或 transient_only
• license_scope
• storage_scope
• redistribution_allowed
• user_goal: summarize、challenge、extract_claims、compare_to_thesis、update_thesis、reverse_engineer_method
• completeness_status: full_report、excerpt、screenshot、summary_only、metadata_only

Required Source Types

• Report source or user material intake record.
• restricted_source_note when the report is paid, confidential, licensed, user-provided, expert-network, or otherwise restricted.
• At least one independent L1 / L2 / L5 source when a report claim is used for a durable conclusion.
• Existing Mira thesis package, evidence log or expectation map when the user asks for thesis impact.
• Consensus or estimate source, or explicit source_gap, when the interpretation depends on market expectation baseline.

Ingestion And Permission Gate

Before using a newly supplied report, run data/ingestion-layer.md.

Default treatment:

• Public report URL: ingestion_route=public_on_demand; cite metadata and short summaries only.
• User upload, screenshot, clipped PDF or exported note: ingestion_route=user_material; keep private unless user explicitly approves promotion.
• Licensed vendor or paid research: ingestion_route=authorized_provider or user_material; tracked artifacts may contain metadata, short compliant effect notes and claim categories, not raw report content.
• Unknown permission: storage_scope=transient_only or private; public_case_use=blocked.

Do not commit full paid reports, substantial excerpts, expert-network transcripts, or vendor raw data. Do not quote long passages. Extract claim-level summaries instead.

Analysis Flow

1. Report Metadata And Source Posture

Record:

• report identity, date, provider, author/team and source URL/path
• permission and storage boundary
• whether the report is complete or only a fragment
• whether it is company-specific, industry-wide, macro, thematic or method-focused
• stale boundary: report date, event covered, next earnings, next data release or target price/rating update

If report_date, permission, completeness or object identity is missing, keep the output at working_view and mark the gap.

2. Thesis Of The Report

Separate:

• headline conclusion
• core variable the author believes matters most
• time horizon of the view
• catalyst or revision path
• base case, bull case and bear case
• rating / target price / valuation output
• evidence the report itself cites
• what the report asks the market to change its mind about

Never treat rating, target price or author conviction as evidence by itself.

3. Claim Extraction

Extract claim-level records into report-claim-map.csv.

Each row should identify:

• claim_type: fact, reported_metric, guidance, target, forecast, assumption, interpretation, opinion, market_pricing, sentiment or derived_calculation
• source_speaker: sellside, buyside, expert, company, market, media or mira
• variable: revenue, margin, pricing, volume, capex, cash flow, multiple, risk premium, market share, demand, supply, regulation or other
• time_horizon: current, next_quarter, FY1, FY2, long_term or unknown
• evidence_cited_by_report
• independent_verification_status
• treatment: use_normally, attribute, monitor, needs_cross_check, source_gap, exclude

Facts and reported metrics require independent verification before they can support a durable Mira conclusion. Forecasts, assumptions, interpretations and opinions remain attributed to the report.

4. Expectation And Variant-Perception Bridge

Ask:

• Is the report describing consensus, challenging consensus, or updating consensus?
• Which variable is the expectation baseline: revenue, EPS, margin, FCF, capex, TAM, unit volume, ASP, multiple or risk premium?
• Does the report cite consensus provider/data, or is it using author estimates?
• Is the claimed edge from better facts, better interpretation, different time horizon, or different risk weighting?
• What would prove the author right or wrong?

If no reliable consensus proxy exists, write source_gap; do not replace consensus with a single analyst view, media tone or price action.

5. Valuation And Model Decomposition

If the report includes target price, rating, valuation multiple, DCF, SOTP or scenario math, decompose:

• forecast driver: revenue, margin, EPS, FCF, capex, share count, net cash/debt
• valuation anchor: P/E, EV/Sales, EV/EBITDA, EV/FCF, DCF, SOTP, NAV, replacement cost or other
• terminal assumptions and discount rate if available
• multiple change versus estimate change
• sensitivity: which input moves the conclusion most
• hidden assumption: margin normalization, utilization, terminal growth, TAM share, customer concentration, dilution or cost of capital

If Mira relies on these numbers for a conclusion, run skills/data-analysis-quality-gate/SKILL.md and record formulas or calculation_gap.

6. Evidence Cross-Check

Cross-check the report's material claims against:

• issuer primary disclosure or filing
• current or recent earnings package
• transcript / management Q&A where relevant
• market price, valuation and estimate data
• peer disclosure or industry data
• previous Mira evidence log or expectation map

Classify each material claim:

• confirmed: independently supported by higher-weight evidence
• plausible_unverified: directionally plausible but not yet confirmed
• contested: contradicted or weakened by other evidence
• opinion_only: useful framing, not evidence
• source_gap: cannot be checked with available sources

7. Bias, Incentive And Framing Check

Check for:

• rating or target-price anchoring
• model-driven precision without source detail
• selective peer set or date window
• company-access bias
• event-chasing after price movement
• bull-case assumptions embedded in base case
• TAM-to-revenue leap
• channel-check anecdote presented as broad demand fact
• valuation multiple change without explicit risk-premium or growth rationale

Bias check does not reject the report automatically. It determines treatment and confidence.

8. Mira Thesis Impact

If an existing thesis or expectation map exists, classify the report impact:

• no_new_evidence: repeats known consensus or prior Mira view
• new_variable: introduces a variable Mira was not tracking
• evidence_upgrade: improves evidence quality for an existing variable
• evidence_downgrade: weakens or contradicts a current variable
• expectation_delta: changes consensus, author estimates or valuation-implied expectation
• method_delta: useful framework should enter methodology review
• actionability_gap: interesting but not enough for research action without more data

Then state whether to update:

• evidence-log.csv
• expectation-map.csv
• thesis-ledger.md
• event-delta.md
• methodology-card.md

When a research report contributes a reusable method for gold, precious metals or macro-sensitive commodities, do not promote the method directly. Classify it as method_delta, identify the existing Mira method it extends, and record whether it should become a labeled lens. For example, a gold residual / MSE framework should map to memory/methodologies/gold-residual-regime-lens.md unless independent data reconstruction supports a stronger methodology review.

Output Package

Default output package:

• report-readout.md
• report-claim-map.csv
• evidence-log.csv

Optional supporting artifacts:

• restricted-source-note.md
• calculation-ledger.csv
• thesis-system updates when impact is material
• methodology card when the main value is a reusable method

quick_map can output only a routing card, source posture, report thesis, key claim table, Mira impact and refresh triggers. standard should produce the package. deep_dive should add cross-checks, valuation decomposition and thesis-system updates where relevant.

Required Sections In report-readout.md

• setup
• source and permission boundary
• report thesis
• claim map summary
• expectation / variant-perception bridge
• valuation and model decomposition
• independent cross-check
• bias and framing check
• Mira thesis impact
• facts / inferences / judgments
• refresh triggers
• follow-up prompts

Scoring

Use scores only to force structure, not to replace judgment.

dimension	score range	meaning
source_posture	1-5	report identity, date, permission and completeness quality
claim_separation	1-5	facts, forecasts, assumptions and opinions are separable
evidence_traceability	1-5	report shows upstream evidence that can be checked
independent_verifiability	1-5	Mira can cross-check material claims
expectation_delta_quality	1-5	report improves consensus / expectation understanding
valuation_transparency	1-5	target price or model assumptions are decomposable
bias_risk	1-5	higher means more framing / incentive / selection risk
mira_incremental_value	1-5	value added versus existing Mira state

Red Flags

• report date or author/source unknown
• full conclusion rests on target price or rating language
• facts, forecasts and opinions are mixed without separation
• target price changes mainly from multiple expansion with no risk-premium explanation
• TAM narrative is treated as company revenue without share, timing and margin bridge
• channel checks lack sample, geography, timing or counter-evidence
• consensus is asserted but provider, date and metric definition are missing
• report relies on company access or management framing without external check
• model precision exceeds source quality
• report is stale relative to earnings, guidance, filing or material event

Stop Rules

• If permission is unclear, do not retain raw report content in tracked artifacts.
• If the report is restricted, output only compliant metadata, short effect notes and claim-level summaries.
• If the report is fragmentary, do not infer omitted model assumptions as known.
• If independent verification is unavailable, keep conclusions at working_view, monitor or source_gap.
• If valuation math is central and cannot be reproduced, mark calculation_gap and avoid strong target-price conclusions.
• If the report only adds opinion and no new evidence, do not update the durable thesis; record no_new_evidence or method_delta only.
• If a report's main value is a reusable model or factor lens, keep report facts attributed to the report and route the method through methodology review before treating it as a Mira framework.