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Recent Quarter

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agentii-ai
recent-quarter

Recent quarter performance analysis, quarterly earnings review, last quarter results, quarterly financial performance, analyze recent quarter, Q4 earnings, quarterly revenue breakdown, EPS this quarter, margin analysis recent quarter, sequential growth, quarterly performance review

Overview

Publisheragentii-ai
Repositoryagentii-investment-intelligence
Skill namerecent-quarter
Stars
207
Forks
16
Bundled files
5
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by agentii-ai on GitHub. Read the source before you install it.

Installation

Install the Recent Quarter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/marketplace-beachhead/plugins/equity-research-core/skills/agentii/recent-quarter
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git /tmp/agentii-investment-intelligence
mkdir -p .claude/skills
cp -r /tmp/agentii-investment-intelligence/marketplace-beachhead/plugins/equity-research-core/skills/agentii/recent-quarter .claude/skills/recent-quarter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Recent Quarter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Recent Quarter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Recent Quarter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Recent Quarter Performance

Preflight

Run canonical pre-flight per contracts/preflight.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

  • analyze recent quarter performance for {ticker}
  • quarterly earnings review for {ticker}
  • last quarter results {ticker}
  • quarterly financial performance {ticker}
  • analyze {ticker} recent quarter
  • {ticker} Q4 earnings
  • {ticker} quarterly revenue breakdown
  • EPS this quarter {ticker}
  • margin analysis recent quarter {ticker}
  • sequential growth {ticker}

Defaults

ParameterDefaultNotes
lookback_quarters1Single most-recent quarter
include_sequentialtrueShow QoQ growth rates

Methodology

1. Retrieval Scope

This skill performs structured data retrieval (XBRL facts + earnings calendar) plus earnings call transcript document search (search_documents(form_type="earnings_call_transcript") → read_source_pages) to cross-reference management's call commentary against the reported quarter. Business-model structural analysis is handled by /agentii:business-model . This skill is TEMPORAL/QUANTITATIVE .

2. Retrieval Strategy

  1. ** Pre-flight (mandatory)**: get_company_fiscal_calendar/{ticker} then get_ticker_coverage/{ticker}. Route based on coverage.
  2. XBRL retrieval: search_xbrl_facts(ticker, concept=["Revenues","GrossProfit","OperatingIncomeLoss","NetIncomeLoss","EarningsPerShareDiluted"], fiscal_year=[latest]) — returns is_primary: true rows by default.
  3. Earnings calendar: search_earnings_calendar(ticker, fiscal_year=[latest, latest-1]) — returns EPS actual/estimate/surprise. Use get_company_fiscal_calendar for fiscal period orientation, NOT search_earnings_calendar .
  4. Consolidated P&L: get_company_financials/{ticker} returns IS/BS/CF highlights with XBRL data.

Read before you quote. A page's description is platform-generated — it is never the issuer's words and must never be quoted as the filing's. When a description identifies a relevant page, read_source_pages that page and quote its page_content. The description is a pointer, not a source: a citation written from one is the fabricated quote this skill's output standard exists to prevent (contracts/retrieval.md § Three-Layer Document Protocol).

3. Temporal Scope

Default: 1 fiscal quarter (max 4). This skill is a temporal snapshot of the most recent quarter's financial performance.

4. Tool Allowlist

See frontmatter allowed_tools. search_xbrl_facts is the primary data source for consolidated P&L metrics; search_earnings_calendar provides EPS actuals, estimates, and surprise data; get_company_fiscal_calendar resolves fiscal period orientation; search_documents(form_type="earnings_call_transcript") + read_source_pages cross-reference management commentary. Deep structural analysis belongs to /agentii:business-model .

5. Protocol

  1. Pre-retrieval: call get_company_fiscal_calendar/{ticker} to resolve fiscal period format, then get_ticker_coverage/{ticker} .
  2. XBRL retrieval: search_xbrl_facts(ticker, concept=["Revenues","GrossProfit","OperatingIncomeLoss","NetIncomeLoss","EarningsPerShareDiluted"], fiscal_year=[latest]) — returns is_primary: true rows by default.
  3. Earnings calendar: search_earnings_calendar(ticker, fiscal_year=[latest, latest-1]) for EPS actuals, estimates, and surprise percentages.
  4. Financial highlights: get_company_financials/{ticker} for IS/BS/CF summary data.
  5. Output: produce P&L progression table with QoQ and YoY growth rates, margin trend chart data, and earnings-vs-consensus comparison.

Modes (5 — temporal / quantitative)

This skill is temporal/quantitative ONLY. Structural analysis (business model classification, product-line decomposition, channel analysis) belongs to /agentii:business-model . Modes below focus on quarterly P&L data, growth rates, margins, and earnings vs. consensus.

Analyst Modes

This skill exposes addressable analysis modes (--mode=<slug> / --modes=<s1>,<s2> / --mode=all; see Mode syntax). The full mode definitions and their output templates live in references/modes.md. The default invocation runs the essentials subset.

Tool Fallbacks

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

Output File

Write the final deliverable to {ticker}/{YYYY-MM-DD_HHMM}_recent-quarter_{affix}.md . Example affixes: consolidated-p-and-l, margin-trends, earnings-vs-consensus.

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 — coverage gaps are required; inline /v/ citations are the citation surface (immediately after each fact). A bottom roll-up index is optional, and where kept it must not repeat a link the prose already carries.
  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; citations belong inline, a bottom roll-up index is optional and never a repeat of a link already given; 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 the summary shape in contracts/citation-and-memory.md — Citation Placement Policy item 3: title · key conclusions · key metrics · Executive Summary · Key Citations (the 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 without opening the file.

Error Handling

Failure ModeDetectionActionUser-Facing Message
Missing dataData API returns empty result setWiden date range and retry once"No data available for {ticker} in requested window."
Partial dataData API returns <80% expected recordsProceed with coverage gaps section"Analysis based on partial data; see Coverage Gaps section."
MCP unreachablePreflight probe failsHalt with actionable error"agentii data plane unreachable; check connection."

Ownership & insider signals: search_institutional_holdings (top-10 holders + whale portfolios, direction=accumulating|reducing|new|exited) and search_insider_trades (Form-4 transactions with SEC URLs) are available as signal inputs.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Recent Quarter AI skill do?

Recent quarter performance analysis, quarterly earnings review, last quarter results, quarterly financial performance, analyze recent quarter, Q4 earnings, quarterly revenue breakdown, EPS this quarter, margin analysis recent quarter, sequential growth, quarterly performance review

Why use Recent Quarter on TypingMind?

Because you install it once and use it with any model. Recent Quarter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Recent Quarter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/marketplace-beachhead/plugins/equity-research-core/skills/agentii/recent-quarter. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Recent Quarter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Recent Quarter?

As many as you like. As long as a model supports skills, you can use Recent Quarter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Recent Quarter AI skill free?

Yes. It is published on GitHub by agentii-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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