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Earnings preview

Skill agentii-ai/agentii-investment-intelligence/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview

Claude-type skills for institutional equity research — 25 AI agent skills with SEC filings, XBRL financials, earnings calendars, DCF/comps/LBO models, and PPT generation. Powered by agentii.ai data plane. Works with Claude Code, OpenCode, Codex, OpenClaw, Goose.

Install
npx -y skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview

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Earnings preview deck, quarterly earnings presentation, earnings summary slides, consensus vs actual presentation, earnings preview report, pre-earnings analysis, earnings expectations deck, quarterly preview, upcoming earnings summary, earnings announcement preview

SKILL.md

8.6 KB, as published. Nobody here has run it

Preflight

Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace style.md override, memory load, and coverage check. See contracts/preflight.md.

Office dependency probe (FR-043) — this skill produces .pptx via Bash + python-pptx:

  1. Live Office session? If mcp__office__* tools are present (Cowork), drive the live document instead of headless Python.
  2. Python library: Bash: python3 -c "import pptx" — if exit ≠ 0, fall back to .md slide spec with data_availability: degraded + python_pptx_missing: true.
  3. LibreOffice: Bash: which soffice for structural validation and PDF export.

If the Python library is absent, report the exact remediation: pip install python-pptx and produce the .md degraded fallback per contracts/office-tooling.md.

Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md.

Triggers

  • generate earnings preview deck
  • build earnings preview presentation
  • create quarterly earnings slides
  • earnings preview pptx
  • earnings summary presentation
  • consensus estimates presentation
  • earnings surprise summary deck
  • quarterly results presentation
  • earnings catalyst calendar slides
  • pre-earnings analyst deck

Defaults

ParameterDefaultNotes
slide_count4-6Title, Company Overview, Consensus Estimates, Historical Surprises, Catalysts, Outlook
lookback_quarters4Trailing 4 quarters for trend analysis
peer_count3-5From search_companies sector peers
source_footersrequiredEvery slide has standard agentii citation footer
templateinstitutional-defaultDark header bar, agentii blue accent, 12pt body

Methodology

Retrieval Scope

This skill performs structured data retrieval (earnings calendar, XBRL facts, company profile) with simple lookups — no unstructured document search. retrieval_scope: structured_only applies. See references/formula-sheet.md for presentation structure guidelines.

Retrieval Strategy

See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.

Temporal Scope

Default: 4 fiscal quarters (max 8). Trailing 4 quarters captures current estimates and YoY comparisons. Maximum 8 quarters for analysts who want 2-year trend context on the estimates slide.

Tool Allowlist

See frontmatter allowed_tools. This skill produces a polished .md slide-deck specification; .pptx rendering is available via the companion financial-analysis:pptx-author skill (separate install; see contracts/office-tooling.md).

Protocol

Step-by-step execution detail is in references/methodology.md.

Deliverable Chain

InputsBuildValidateOutputNext

  1. Inputs: resolved ticker + earnings calendar, consensus estimates, and trailing XBRL facts (search_earnings_calendar, search_xbrl_facts, search_companies, get_company_profile).
  2. Build: write a self-contained Python script using python-pptx that creates the 4–6 slide .pptx deck per ## Output Structure. Execute via Bash: python3 script.py. Verify the .pptx file exists. If python-pptx is absent, fall back to .md slide spec per contracts/office-tooling.md.
  3. Validate: run the ## Validation Gates below.
  4. Output: write the artifact path per ## Output File.
  5. Next: append to agentii.md; hand off to a downstream pitch/review skill if requested.

Validation Gates

  1. slide count: between 4 and 6. If failed: If outside range: refuse delivery.
  2. estimates slide: includes consensus, high, and low estimates. If failed: If missing: flag in Coverage Gaps.
  3. source footers: every slide has source_footer with standard agentii citation. If failed: If any missing: refuse delivery.
  4. peer comparison: has >= 3 peers. If failed: If < 3: flag in Coverage Gaps.

Tool Fallbacks

Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.md.

Output File

Primary deliverable: {ticker}/{YYYY-MM-DD_HHMM}_earnings-preview_{affix}.pptx — real PowerPoint binary via Bash + python-pptx per contracts/office-tooling.md. Degraded fallback: {ticker}/{YYYY-MM-DD_HHMM}_earnings-preview_{affix}.md when python-pptx is absent (FR-044).

Output Structure

The deliverable is a structured markdown report written to the path in ## Output File. Full section-by-section template (headings, tables, and field definitions) lives in references/output-structure.md. Required elements:

  1. Executive Summary — headline conclusions (≤200 words).
  2. Core analysis sections — per this skill's methodology and analyst modes.
  3. Data classification — tag findings [FACT] / [DEDUCTED] / [VIEW] per contracts/snapshot-synthesis.md.
  4. Coverage Gaps & Citations — inline /v/ citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index.
  5. Output frontmatter — emit the FR-090 structured block per contracts/output-frontmatter-schema.md.

Citations & memory: follow contracts/citation-and-memory.md — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link; a bottom Citations section provides a non-duplicative roll-up index; the closing TUI reply includes a compact Key Citations list (headline 5–10 facts) of clickable /v/ URLs; and append the run to agentii.md per contracts/agentii-md-schema.md.

Memory & Snapshot

  • Memory load (pre-flight): load prior workspace context for the ticker before retrieval — see contracts/memory-load.md.
  • Structured output frontmatter: emit the FR-090 block (key_metrics, conclusions, facts_count, deducted_count, views_count, citation_count) per contracts/output-frontmatter-schema.md.
  • Snapshot synthesis: after writing the deliverable, update the two-tier snapshot and classify findings as [FACT]/[DEDUCTED]/[VIEW] — see contracts/snapshot-synthesis.md.
  • Session archival: record the run under sessions/{YYYY-MM-DD}/ and update sessions/INDEX.md per contracts/session-format.md.

Final Summary (TUI)

End the closing chat reply with a compact Key Citations list (headline 5–10 facts), each a clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link, so the user can cmd+click straight to the exact SEC page. See contracts/citation-and-memory.md.

Error Handling

Failure ModeDetectionActionUser-Facing Message
Missing earnings datasearch_earnings_calendar returns emptyUse search_xbrl_facts for historical actuals only; flag estimates as unavailable"Consensus estimates not available for {ticker}; presentation based on historical actuals only."
Partial data<80% expected fields returnedProceed with coverage gaps section"Presentation based on partial data; see Coverage Gaps."
Sector mismatchPeer sector != target sectorFilter out mismatched peers"Removed {n} peer(s) due to sector mismatch."
Insufficient history<4 quarters of data availableDowngrade to limited-history presentation (3 slides min)"Limited historical data available; presentation adjusted."
MCP unreachableagentii Preflight probe failsHalt with actionable error"agentii data plane unreachable; check connection and AGENTII_API_KEY."
Office backend unreachableAll 3 office backends fail PreflightHalt with AGENTII_OFFICE_UNREACHABLE"No office backend available. Options: (a) set AGENTII_API_KEY for agentii-office, (b) pip install python-pptx, (c) install OfficeCLI."
Knowledge Store unavailableget_entity_knowledge returns 503Fall back to get_company_profile + search_companies; flag with knowledge_store_degraded: true"Knowledge Store not yet available; peer analysis based on filing-derived entity context."

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