McKinsey-Style PPT Design
likaku/Mck-ppt-design-skill
Builds consultant-style PowerPoint decks from scratch with the MckEngine python-pptx wrapper, through a five-stage flow with scripted quality gates.
Earnings preview deck, quarterly earnings presentation, earnings summary slides, consensus vs actual presentation, earnings preview report, pre-earnings analysis, earnings expectations deck…
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-preview --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "earnings-preview" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview into .claude/skills/earnings-preview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "earnings-preview", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-previewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-preview --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview .agents/skills/earnings-preview && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "earnings-preview" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview into .agents/skills/earnings-preview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "earnings-preview", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-preview --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview .cursor/skills/earnings-preview && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "earnings-preview" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview into .cursor/skills/earnings-preview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "earnings-preview", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/agentii-ai/agentii-investment-intelligence.git --path plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-preview --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview .gemini/skills/earnings-preview && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "earnings-preview" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview into .gemini/skills/earnings-preview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "earnings-preview", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-previewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview .github/skills/earnings-preview && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "earnings-preview" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview into .github/skills/earnings-preview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "earnings-preview", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentii-ai/agentii-investment-intelligence --skill earnings-preview -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence earnings-preview --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview .opencode/skills/earnings-preview && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "earnings-preview" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview into .opencode/skills/earnings-preview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "earnings-preview", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
earnings-previewEarnings 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. 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.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 86980e1. It shows what the files ask for, not the result of running them.
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.
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.
Hosts in commands or code, which the agent is likely to contact:
agentii.aiFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
AGENTII_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
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.
.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.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:
mcp__office__* tools are present (Cowork), drive the live
document instead of headless Python.Bash: python3 -c "import pptx" — if exit ≠ 0, fall back to .md
slide spec with data_availability: degraded + python_pptx_missing: true.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).
| Parameter | Default | Notes |
|---|---|---|
| slide_count | 4-6 | Title, Company Overview, Consensus Estimates, Historical Surprises, Catalysts, Outlook |
| lookback_quarters | 4 | Trailing 4 quarters for trend analysis |
| peer_count | 3-5 | From search_companies sector peers |
| source_footers | required | Every slide has standard agentii citation footer |
| template | institutional-default | Dark header bar, agentii blue accent, 12pt body |
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.
See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.
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.
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).
Step-by-step execution detail is in references/methodology.md.
Inputs → Build → Validate → Output → Next
search_earnings_calendar, search_xbrl_facts, search_companies, get_company_profile).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.## Validation Gates below.## Output File.agentii.md; hand off to a downstream pitch/review skill if requested.Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.md.
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.
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).
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:
[FACT] / [DEDUCTED] / [VIEW] per contracts/snapshot-synthesis.md./v/ citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index.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.
contracts/memory-load.md.key_metrics, conclusions, facts_count, deducted_count, views_count, citation_count) per contracts/output-frontmatter-schema.md.[FACT]/[DEDUCTED]/[VIEW] — see contracts/snapshot-synthesis.md.sessions/{YYYY-MM-DD}/ and update sessions/INDEX.md per contracts/session-format.md.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.
| Failure Mode | Detection | Action | User-Facing Message |
|---|---|---|---|
| Missing earnings data | search_earnings_calendar returns empty | Use 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 returned | Proceed with coverage gaps section | "Presentation based on partial data; see Coverage Gaps." |
| Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." |
| Insufficient history | <4 quarters of data available | Downgrade to limited-history presentation (3 slides min) | "Limited historical data available; presentation adjusted." |
| MCP unreachable | agentii Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection and AGENTII_API_KEY." |
| Office backend unreachable | All 3 office backends fail Preflight | Halt 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 unavailable | get_entity_knowledge returns 503 | Fall 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
SKILL.md and 8 other files (references) in plugins/vertical-plugins/models-and-pitches/skills/agentii/earnings-preview of agentii-ai/agentii-investment-intelligence.
Open the folder on GitHubat commit 86980e1
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Earnings Preview this skillagentii-ai/agentii-investment-intelligence | 207 | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| McKinsey-Style PPT Designlikaku/Mck-ppt-design-skill | 297 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| PowerPoint PPTX ToolkitXiaomiMiMo/MiMo-Code | 14k | — | ~6.8k | Automated safety check: Notes | Apache-2.0 | |
| Python PPTX Generatorsickn33/agentic-awesome-skills | 47k | 2 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Yfinance Datahimself65/finance-skills | 3.4k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Fin Yfinance Datacriptogus/agent-evolve-network | 288 | — | ~806 | Automated safety check: Pass | MIT |
likaku/Mck-ppt-design-skill
Builds consultant-style PowerPoint decks from scratch with the MckEngine python-pptx wrapper, through a five-stage flow with scripted quality gates.
XiaomiMiMo/MiMo-Code
Creates, edits and reads PowerPoint .pptx files with python-pptx or PptxGenJS, with scripts for XML edits, text dumps, PDF and image rendering, and thumbnails.
sickn33/agentic-awesome-skills
Generate complete Python scripts that build polished PowerPoint decks with python-pptx and real slide content.
himself65/finance-skills
Fetch financial and market data with the yfinance Python library (Yahoo Finance).
criptogus/agent-evolve-network
Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more.
Geeksfino/finskills
Free Python scripts that fetch US stock data, SEC filings, insider trades and macro indicators, and run financial score calculators and portfolio analytics.
agentii-ai/agentii-investment-intelligence
Adversarial verification of research theses — cross-run/cross-thesis contradiction via the entity index, pre-mortem (Klarman/Kahneman: assume the loss already happened, reverse the path), inversion…
agentii-ai/agentii-investment-intelligence
Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step…
agentii-ai/agentii-investment-intelligence
The research-domain clarification skill — find underspecified items in a thesis spec.md (prose wrongif, universe rows without rationale, missing budget/expiry/pins, ambiguous pillars), ask the human…
agentii-ai/agentii-investment-intelligence
Scaffold and amend the L1 Investment Constitution — [ALLCAPS] placeholder bootstrap, SemVer bump rules, Sync Impact Report, MINOR/MAJOR re-examination dispatch after the gate-5 budget confirm.
agentii-ai/agentii-investment-intelligence
Append-only gap closure and the cadence engine for research theses.
agentii-ai/agentii-investment-intelligence
Execute research tasks — checklist soft gate, phase dispatch with explicit thesisdir, budget enforcement (halt + approval card on overrun), skillpin recording (versionhash content-hashed per skill…
Categories
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.
Earnings Preview fits situations like: tasks that involve Stock and market analysis; tasks that involve Slides and decks; tasks that involve Financial analysis.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.