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

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Earnings Preview

skills CLI
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-preview --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview .claude/skills/earnings-preview && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
earnings-preview
GitHub stars
207
Token cost
~2.4k tokens
SKILL.md length
992 words
Files
9 (incl. references)
Skills in repo
79
Repo updated
First seen
Licence
Apache-2.0

At a glance

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

  • Works in 3 steps: Live Office session? If mcpoffice* tools… → Python library: Bash: python3 -c "import… → LibreOffice: Bash: which soffice for…
  • Tasks that involve Stock and market analysis
  • SKILL.md covers Preflight, Triggers, Defaults and Methodology, plus 9 more sections
  • Reaches agentii.ai; needs AGENTII_API_KEY

What it does

Earnings Preview is an agent skill from agentii-ai/agentii-investment-intelligence. 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

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/disclaimer.md`, `references/formula-sheet.md` and `references/institutional-defaults.md`).

It sits in Business, Finance & HR, covering Stock and market analysis, Slides and decks and Financial analysis. It works with Python, Bash, python-pptx and Microsoft PowerPoint. The repository describes itself as: 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… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Stock and market analysis
  • Tasks that involve Slides and decks
  • Tasks that involve Financial analysis

Example prompts

  • “Use the earnings-preview skill to earning preview deck, quarterly earnings presentation, earnings summary slides, consensus vs actual presentation…”
  • “/earnings-preview”

Requirements

  • Python 3
  • A credential in AGENTII_API_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Live Office session? If mcpoffice* tools are present (Cowork), drive the live
  2. Python library: Bash: python3 -c "import pptx" — if exit ≠ 0, fall back to .md
  3. LibreOffice: Bash: which soffice for structural validation and PDF export.

What it can do on your machine

Read from SKILL.md and the folder at commit 86980e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • agentii.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AGENTII_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Earnings Preview loads about 2.4k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 992 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from agentii-ai/agentii-investment-intelligence at commit 86980e1, republished under its Apache-2.0 licence (© agentii-ai). 992 words, ~2,397 tokens.

Download SKILL.mdSave it as .claude/skills/earnings-preview/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
earnings-preview
description
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
multi_ticker_semantics
single_target
temporal_scope.default_quarters
4
temporal_scope.max_quarters
8
temporal_scope.description
Typical lookback: 4 quarters, max: 8
retrieval_scope
unstructured_document_search
min_tool_diversity
5

Preflight

Run canonical pre-flight per contracts/preflight.md. 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 (install the python-pptx package) 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 — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).

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) plus earnings call transcript document search (search_documents(form_type="earnings_call_transcript") → read_source_outline → read_source_pages) for forward-looking catalyst and guidance context. 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

Inputs → Build → Validate → Output → Next

  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.

Disclaimer (Q139/T137) — REQUIRED, template-owned

This output is presentation-shaped and MUST carry the canonical disclaimer from scenarios/templates/disclaimer.md — verbatim, not restated. The clause set is the contract; the wording is the workspace's rendering (Q126). Placeholders are filled, never shipped. The full requirement, the clause-set rule, and the per-slide footer rule for price targets are in references/disclaimer.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).

Show full SKILL.md (409 more words)Show less

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."

© agentii-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview of agentii-ai/agentii-investment-intelligence.

  • SKILL.md
  • references/disclaimer.md
  • references/formula-sheet.md
  • references/institutional-defaults.md
  • references/methodology.md
  • references/modes.md
  • references/output-structure.md
  • references/tool-fallbacks.md
  • references/validation-checklist.md

Open the folder on GitHubat commit 86980e1

Compare with similar skills

Earnings Preview next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Earnings Preview this skillagentii-ai/agentii-investment-intelligence207—~2.4kAutomated safety check: PassApache-2.0
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PowerPoint PPTX ToolkitXiaomiMiMo/MiMo-Code14k—~6.8kAutomated safety check: NotesApache-2.0
Python PPTX Generatorsickn33/agentic-awesome-skills47k2 repos~1.1kAutomated safety check: PassMIT
Yfinance Datahimself65/finance-skills3.4k—~1.3kAutomated safety check: PassMIT
Fin Yfinance Datacriptogus/agent-evolve-network288—~806Automated safety check: PassMIT

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Questions about Earnings Preview

What does Earnings Preview do?

Earnings preview deck, quarterly earnings presentation, earnings summary slides, consensus vs actual presentation, earnings preview report, pre-earnings analysis, earnings expectations deck…. Earnings Preview is an agent skill from agentii-ai/agentii-investment-intelligence.

When should I use Earnings Preview?

Earnings Preview fits situations like: tasks that involve Stock and market analysis; tasks that involve Slides and decks; tasks that involve Financial analysis.

How do I install Earnings Preview in Claude Code?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview in agentii-ai/agentii-investment-intelligence) into .claude/skills/earnings-preview in your project. Claude Code loads it when a task matches its description.

How do I install Earnings Preview in Codex?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a codex`. Or copy the skill folder (plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview in agentii-ai/agentii-investment-intelligence) into .agents/skills/earnings-preview in your project. Codex loads it when a task matches its description.

Can I use Earnings Preview in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/earnings-preview, .gemini/skills/earnings-preview, .github/skills/earnings-preview and .opencode/skills/earnings-preview in your project.

What does Earnings Preview need to run?

Going by SKILL.md and its folder, Earnings Preview needs credentials named AGENTII_API_KEY. Our summary lists: Python 3; A credential in AGENTII_API_KEY.

Does Earnings Preview access the network?

SKILL.md names 1 domain. In commands or code: agentii.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Earnings Preview safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Earnings Preview use?

Earnings Preview is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Earnings Preview use?

About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Earnings Preview?

Skills that share tags, products or a category with Earnings Preview: McKinsey-Style PPT Design (likaku/Mck-ppt-design-skill, 297 stars), PowerPoint PPTX Toolkit (XiaomiMiMo/MiMo-Code, 14k stars), Python PPTX Generator (sickn33/agentic-awesome-skills, 47k stars) and Yfinance Data (himself65/finance-skills, 3.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Earnings Preview?

agentii-ai (a GitHub user) maintains it in agentii-ai/agentii-investment-intelligence, which has 207 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on September 29, 2026.

Source: agentii-ai/agentii-investment-intelligence on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.