Claude Skill

earnings-preview-med

Med-adapted earnings preview: consensus estimates, historical surprises, guidance sensitivities, and the FDA-catalyst overlay (PDUFA/AdCom/trial readouts near the print) for biotech/pharma names.

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Part of agentii-ai/agentii-investment-intelligence — 46 skills

Install

skills CLI npx skills add https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/bio-pharm/skills/agentii/earnings-preview-med
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install agentii-ai-agentii-investment-intelligence@llmmart
Git git clone https://github.com/agentii-ai/agentii-investment-intelligence.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole agentii-ai/agentii-investment-intelligence collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Methodology inspired by publicly taught earnings-preview frameworks; all text is an original paraphrase.

Defaults

Parameter Default Value Rationale
surprise_window 8 quarters Standard surprise history window
include_catalysts true Med prints move on catalysts as much as EPS
guidance_sensitivity true Guidance is the swing factor for pharma

Preflight

Run canonical pre-flight per contracts/preflight.md. Propagate X-Agentii-Trace per contracts/x-agentii-trace-header.md.

Triggers

  • "Preview [biotech ticker]'s upcoming earnings."
  • "What should I expect at [ticker]'s next print?"
  • "How has [ticker] surprised historically?"
  • "Which catalysts land near [ticker]'s earnings date?"
  • "Build an earnings preview with consensus estimates."
  • "What's the guidance risk for [ticker] this quarter?"
  • "Summarize the last few quarters for [ticker]."
  • "Earnings + FDA calendar overlap for [ticker]."
  • "What are the swing factors for [ticker]'s print?"
  • "Historical reaction to [ticker]'s earnings surprises."
  • "What changed in my estimates, thesis, and positioning ahead of [ticker]'s print?"

Production Grounding

  • Med prints have TWO drivers: financials (revenue/EPS/guidance) and catalysts (PDUFA/AdCom/readouts). The catalyst overlay is mandatory — a clean quarter can be undone by a CRL days earlier.
  • Every preview closes with model-vs-consensus deltas (our modeled numbers vs consensus from search_earnings_calendar, signed with the driver named) and the three what's-changed vectors (estimates / thesis / positioning) — estimates move first, thesis and positioning follow only when the facts justify them.
  • For pre-revenue biotechs, the print is mostly about cash runway + pipeline updates; consensus EPS is secondary.
  • Grounding frameworks: references/knowledge-frameworks.md (道/法 review knowledge).

Data Source Priority

  1. search_earnings_calendar — estimates, actuals, surprise history, next date.
  2. search_xbrl_facts — revenue/EPS/margin trends.
  3. search_documents/read_source_* — prior-quarter commentary and guidance.
  4. Knowledge layer: search_investment_cases for historical print reactions.

Methodology

Retrieval Scope

unstructured_document_search

Retrieval Strategy

  1. Resolve the earnings event: search_earnings_calendar for dates/estimates/surprises (consensus values).
  2. Pull fundamentals trend: search_xbrl_facts key line items (our modeled numbers).
  3. Compute model-vs-consensus deltas on each key line item; state assumptions; annotate coverage_gap where no consensus value exists.
  4. Slot-refresh the three what's-changed vectors: estimates / thesis / positioning.
  5. Catalyst overlay: nearest PDUFA/AdCom/readout vs print date.
  6. Ground with historical cases (print reactions) via knowledge tools.

Temporal Scope

See frontmatter temporal_scope block.

Tool Allowlist

See frontmatter allowed_tools.

Protocol

  1. Event & estimates
  2. Fundamental trend
  3. Model-vs-consensus deltas
  4. What's-changed vectors (estimates / thesis / positioning)
  5. Catalyst overlay
  6. Swing-factor synthesis

Modes

  • Standard (default): estimates + surprises + guidance.
  • Pre-revenue: runway + pipeline + readout framing.
  • Catalyst-overlap: print framed around nearby FDA events.

Tool Fallbacks

Failure Fallback
search_earnings_calendar empty Use filings (search_documents) for dates; annotate coverage_gap
No catalyst data Flag "catalyst overlay unavailable"
Knowledge tools empty Proceed with structured data only

Output File

{ticker}/{YYYY-MM-DD_HHMM}_earnings-preview-med_{affix}.md

Output Structure

  1. Executive Summary — setup for the print in 2-3 sentences
  2. Consensus & Surprise History — estimates table + surprise record
  3. Model vs Consensus — our modeled numbers vs consensus (search_earnings_calendar) with signed deltas and named drivers
  4. What's Changed — the three vectors: estimates / thesis / positioning (estimates move first, ratings last)
  5. Guidance & Swing Factors — guidance risk analysis
  6. Catalyst Overlay — FDA events near the print
  7. Historical Context — cases with /v/ citations
  8. Coverage Gaps — degraded flags

Error Handling

Error Fallback
Estimates missing Present fundamentals trend only; flag
Date uncertain Use calendar's best estimate + annotate

Memory Load

See contracts/memory-load.md.

Snapshot

See contracts/snapshot-synthesis.md.

Final Summary (TUI)

Include ### Key Citations block with 0-10 clickable /v/ URLs.

References

  • contracts/citation-and-memory.md
  • contracts/output-frontmatter-schema.md
  • contracts/memory-load.md
  • contracts/snapshot-synthesis.md
  • contracts/preflight.md
  • references/knowledge-frameworks.md
Files (agentii-investment-intelligence)
  • references
    • knowledge-frameworks.md 2.2 KB
      # Med Knowledge Frameworks (shared)
      
      Full regulatory grounding lives in the fda-catalyst-analysis skill's reference:
      `../../fda-catalyst-analysis/references/knowledge-frameworks.md` (FDA/EMA process,
      AdCom mechanics, six scrutiny axes, catalyst sizing, med metrics).
      
      ## 道/法 layered review knowledge (runtime retrieval)
      
      Retrieve at runtime via `search_investment_strategies(sectors=med, layer_tags=L2)`
      and cite with /v/ URLs:
      - 道 (L1): Substantial Evidence Standard · Totality of Evidence & Benefit-Risk
        Balance · Safety Signal Characterization · Patient-Centric Risk-Benefit
        Context · Clinical Meaningfulness of Endpoints
      - 法/器 (L2): Comparator Selection Adequacy · Missing Data Sensitivity ·
        Subgroup Consistency · Surrogate Endpoint Validation · RWE Credibility ·
        REMS Effectiveness · Trial Design Integrity · Vote Tally Interpretation
        Matrix · Red Flag Screening Checklist
      
      ## Structured AdCom calendar
      
      `search_adcom_meetings` (committee/product/ticker/date/vote filters,
      122 meetings, 113 with votes) + `get_adcom_meeting` (briefing-doc inventory).
      
      ## What's-changed vectors & model-vs-consensus deltas (earnings preview)
      
      - **Three what's-changed vectors**: every preview closes by slot-refreshing
        three vectors — estimates (what numbers moved and why), thesis (what the
        quarter does to the investment case), positioning (where investor attention
        sits and the per-name bull/bear pivot conditions). Slot-refresh order:
        estimates move first; thesis and positioning follow only when the facts
        justify them.
      - **Model-vs-consensus deltas**: each key line item states our modeled number
        against the consensus value pulled from `search_earnings_calendar`, with the
        delta signed and the driver named. Where no consensus value is retrievable,
        the delta degrades to a `coverage_gap` with the required-input list — never
        a fabricated comparison.
      - **Uncertainty discipline**: scenario-flexing stays at market level, POS at
        asset level (peak × POS, changes logged with reasons); explicit abstention
        where a swing factor is unquantifiable.
      - **Buy-side lens**: client-question framing ("one common question we have
        received"); per-name bull/bear pivot conditions stated, not implied.
      
    • modes.md 1.2 KB
      # earnings-preview-med — Analyst Mode Definitions
      
      Derived from the skill's own methodology structure (scripts/mode_backfill.py, spec 046 M1).
      
      ### Mode: defaults
      
      **Objective**: Defaults analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: preflight
      
      **Objective**: Preflight analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: triggers
      
      **Objective**: Triggers analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: production-grounding
      
      **Objective**: Production Grounding analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: data-source-priority
      
      **Objective**: Data Source Priority analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: drug
      
      **Objective**: Drug modality analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: biologic
      
      **Objective**: Biologic modality analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: device
      
      **Objective**: Device modality analysis per the skill's methodology (see SKILL.md sections).
      
      ### Mode: vaccine
      
      **Objective**: Vaccine modality analysis per the skill's methodology (see SKILL.md sections).
      
  • SKILL.md 5.7 KB
    ---
    name: earnings-preview-med
    description: "Med-adapted earnings preview: consensus estimates, historical surprises, guidance sensitivities, and the FDA-catalyst overlay (PDUFA/AdCom/trial readouts near the print) for biotech/pharma names."
    sectors: [med.medicines_biotech, med.medical_devices]
    multi_ticker_semantics: single_target
    temporal_scope:
      default_quarters: 4
      max_quarters: 8
      description: "Preview window default 4 quarters; up to 8 for guidance trajectories."
    allowed_tools:
      - search_earnings_calendar
      - search_xbrl_facts
      - get_company_profile
      - search_documents
      - read_source_outline
      - read_source_pages
      - search_investment_cases
      - get_investment_case
      - search_investment_strategies
      - get_investment_strategy
      - search_by_analogue
      - search_knowledge_entries
      - get_knowledge_entry
    retrieval_scope: unstructured_document_search
    min_tool_diversity: 3
    parameter_free: false
    ---
    
    > Methodology inspired by publicly taught earnings-preview frameworks; all text is an original paraphrase.
    
    ## Defaults
    
    | Parameter | Default Value | Rationale |
    |-----------|---------------|-----------|
    | surprise_window | 8 quarters | Standard surprise history window |
    | include_catalysts | true | Med prints move on catalysts as much as EPS |
    | guidance_sensitivity | true | Guidance is the swing factor for pharma |
    
    ## Preflight
    
    Run canonical pre-flight per `contracts/preflight.md`. Propagate X-Agentii-Trace per `contracts/x-agentii-trace-header.md`.
    
    ## Triggers
    
    - "Preview [biotech ticker]'s upcoming earnings."
    - "What should I expect at [ticker]'s next print?"
    - "How has [ticker] surprised historically?"
    - "Which catalysts land near [ticker]'s earnings date?"
    - "Build an earnings preview with consensus estimates."
    - "What's the guidance risk for [ticker] this quarter?"
    - "Summarize the last few quarters for [ticker]."
    - "Earnings + FDA calendar overlap for [ticker]."
    - "What are the swing factors for [ticker]'s print?"
    - "Historical reaction to [ticker]'s earnings surprises."
    - "What changed in my estimates, thesis, and positioning ahead of [ticker]'s print?"
    
    ## Production Grounding
    
    - Med prints have TWO drivers: financials (revenue/EPS/guidance) and catalysts (PDUFA/AdCom/readouts). The catalyst overlay is mandatory — a clean quarter can be undone by a CRL days earlier.
    - Every preview closes with model-vs-consensus deltas (our modeled numbers vs consensus from `search_earnings_calendar`, signed with the driver named) and the three what's-changed vectors (estimates / thesis / positioning) — estimates move first, thesis and positioning follow only when the facts justify them.
    - For pre-revenue biotechs, the print is mostly about cash runway + pipeline updates; consensus EPS is secondary.
    - Grounding frameworks: `references/knowledge-frameworks.md` (道/法 review knowledge).
    
    ## Data Source Priority
    
    1. `search_earnings_calendar` — estimates, actuals, surprise history, next date.
    2. `search_xbrl_facts` — revenue/EPS/margin trends.
    3. `search_documents`/`read_source_*` — prior-quarter commentary and guidance.
    4. Knowledge layer: `search_investment_cases` for historical print reactions.
    
    ## Methodology
    
    ### Retrieval Scope
    unstructured_document_search
    
    ### Retrieval Strategy
    1. Resolve the earnings event: `search_earnings_calendar` for dates/estimates/surprises (consensus values).
    2. Pull fundamentals trend: `search_xbrl_facts` key line items (our modeled numbers).
    3. Compute model-vs-consensus deltas on each key line item; state assumptions; annotate coverage_gap where no consensus value exists.
    4. Slot-refresh the three what's-changed vectors: estimates / thesis / positioning.
    5. Catalyst overlay: nearest PDUFA/AdCom/readout vs print date.
    6. Ground with historical cases (print reactions) via knowledge tools.
    
    ### Temporal Scope
    See frontmatter temporal_scope block.
    
    ### Tool Allowlist
    See frontmatter allowed_tools.
    
    ### Protocol
    1. Event & estimates
    2. Fundamental trend
    3. Model-vs-consensus deltas
    4. What's-changed vectors (estimates / thesis / positioning)
    5. Catalyst overlay
    6. Swing-factor synthesis
    
    ## Modes
    
    - **Standard** (default): estimates + surprises + guidance.
    - **Pre-revenue**: runway + pipeline + readout framing.
    - **Catalyst-overlap**: print framed around nearby FDA events.
    
    ## Tool Fallbacks
    
    | Failure | Fallback |
    |---------|----------|
    | search_earnings_calendar empty | Use filings (`search_documents`) for dates; annotate coverage_gap |
    | No catalyst data | Flag "catalyst overlay unavailable" |
    | Knowledge tools empty | Proceed with structured data only |
    
    ## Output File
    
    `{ticker}/{YYYY-MM-DD_HHMM}_earnings-preview-med_{affix}.md`
    
    ## Output Structure
    
    1. **Executive Summary** — setup for the print in 2-3 sentences
    2. **Consensus & Surprise History** — estimates table + surprise record
    3. **Model vs Consensus** — our modeled numbers vs consensus (`search_earnings_calendar`) with signed deltas and named drivers
    4. **What's Changed** — the three vectors: estimates / thesis / positioning (estimates move first, ratings last)
    5. **Guidance & Swing Factors** — guidance risk analysis
    6. **Catalyst Overlay** — FDA events near the print
    7. **Historical Context** — cases with /v/ citations
    8. **Coverage Gaps** — degraded flags
    
    ## Error Handling
    
    | Error | Fallback |
    |-------|----------|
    | Estimates missing | Present fundamentals trend only; flag |
    | Date uncertain | Use calendar's best estimate + annotate |
    
    ## Memory Load
    
    See `contracts/memory-load.md`.
    
    ## Snapshot
    
    See `contracts/snapshot-synthesis.md`.
    
    ## Final Summary (TUI)
    
    Include ### Key Citations block with 0-10 clickable /v/ URLs.
    
    ## References
    
    - `contracts/citation-and-memory.md`
    - `contracts/output-frontmatter-schema.md`
    - `contracts/memory-load.md`
    - `contracts/snapshot-synthesis.md`
    - `contracts/preflight.md`
    - `references/knowledge-frameworks.md`
    

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