Earnings Analysis
Wind-Alice/AliceMarket
Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage.
Qualitative stock analysis, management operating plan MOP assessment, key performance indicator KPI identification, catalyst identification and classification, earnings call transcript analysis…
$ npx skills add agentii-ai/agentii-investment-intelligence --skill qualitative-filtering -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence qualitative-filtering --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/idea-generation/skills/agentii/qualitative-filtering .claude/skills/qualitative-filtering && 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 "qualitative-filtering" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering into .claude/skills/qualitative-filtering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qualitative-filtering", 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/idea-generation/skills/agentii/qualitative-filteringType 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 qualitative-filtering -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence qualitative-filtering --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/idea-generation/skills/agentii/qualitative-filtering .agents/skills/qualitative-filtering && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "qualitative-filtering" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering into .agents/skills/qualitative-filtering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qualitative-filtering", 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 qualitative-filtering -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence qualitative-filtering --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/idea-generation/skills/agentii/qualitative-filtering .cursor/skills/qualitative-filtering && 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 "qualitative-filtering" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering into .cursor/skills/qualitative-filtering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qualitative-filtering", 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/idea-generation/skills/agentii/qualitative-filtering--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 qualitative-filtering -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentii-ai/agentii-investment-intelligence qualitative-filtering --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/idea-generation/skills/agentii/qualitative-filtering .gemini/skills/qualitative-filtering && 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 "qualitative-filtering" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering into .gemini/skills/qualitative-filtering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qualitative-filtering", 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 qualitative-filteringInstalls 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 qualitative-filtering -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/idea-generation/skills/agentii/qualitative-filtering .github/skills/qualitative-filtering && 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 "qualitative-filtering" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering into .github/skills/qualitative-filtering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qualitative-filtering", 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 qualitative-filtering -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 qualitative-filtering --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/idea-generation/skills/agentii/qualitative-filtering .opencode/skills/qualitative-filtering && 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 "qualitative-filtering" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering into .opencode/skills/qualitative-filtering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qualitative-filtering", 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.
qualitative-filteringQualitative stock analysis, management operating plan MOP assessment, key performance indicator KPI identification, catalyst identification and classification, earnings call transcript analysis…
Qualitative Filtering is an agent skill from agentii-ai/agentii-investment-intelligence. Qualitative stock analysis, management operating plan MOP assessment, key performance indicator KPI identification, catalyst identification and classification, earnings call transcript analysis, qualitative evidence gathering for investment thesis
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/modes.md` and `references/qual-methodology.md`).
It sits in Business, Finance & HR, covering Meeting notes and agendas, OKRs and executive reporting and Stock and market analysis. 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.
4 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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Qualitative Filtering loads about 2.5k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 999 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). 999 words, ~2,464 tokens.
.claude/skills/qualitative-filtering/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Methodology fused from professional trading and investment frameworks; all text is an original paraphrase.
| Parameter | Default Value | Rationale |
|---|---|---|
| catalyst_window_days | 20-60 | Trading horizon for active positions |
| kpi_trend_min_quarters | 8 | Minimum quarters of KPI history for trend analysis |
| mgmt_track_record_years | 3 | Management credibility requires 3+ years of guidance vs actuals |
| catalyst_min_impact | 5% | Minimum expected price impact to justify catalyst-driven trade |
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).
references/qual-methodology.md (bundled MOP-KPI-Catalyst framework)search_documents(ticker={T}, form_type="earnings_call_transcript") → read_source_outline → read_source_pages (citation prefix ect<N>; pages carry section_type in session_title and guidance/forward_looking/analyst_questions in labels)search_investment_strategies + search_investment_cases + search_by_analogueunstructured_document_search (earnings call transcripts + SEC disclosures)
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.
Three-layer protocol from contracts/retrieval.md: the qualitative framework is bundled in references/qual-methodology.md. Earnings transcripts via search_documents(form_type="earnings_call_transcript") → read_source_pages (Layer 1→3). Strategy frameworks and historical analogues via MCP knowledge tools. Detailed methodology and catalyst classification in references/qual-methodology.md.
See frontmatter temporal_scope block.
See frontmatter allowed_tools.
This skill implements qualitative investment analysis through a three-stage framework: MOP → KPI → Results. Companies do not publish an "MOP" — the analyst infers it by identifying KPIs first, then reverse-engineering the strategic plan. The analyst verifies the chain is intact and credible. A broken chain is the highest-quality short signal.
Detailed methodology: management assessment framework (Alpha/Beta/Delta), board quality checklist, mosaic theory triangulation, catalyst taxonomy, sector-specific KPI templates, and the 20+ pattern red flag catalog are in references/qual-methodology.md.
Critical distinction: Good company ≠ good stock. For the 20-60 day horizon, catalysts are required.
KPI Identification: Identify industry-specific KPIs per the reference templates (SaaS, retail, manufacturing, financial services, healthcare). Determine leading vs. lagging. Assess consistency (changing KPIs = red flag), auditability, relevance. Map trends over 8+ quarters. KPI divergence from sector norms often explains quantitative outlier signals.
MOP Analysis (5-dimension scorecard, each 0-10, composite < 25 = high risk): Extract from earnings calls, presentations, MD&A. Infer the MOP: forward-looking statements → recurring themes → strategic narrative → test consistency/credibility. Score on: Track Record (30%, 3yr+ guidance vs. actuals), Consistency (20%), Realism (20%), Alignment (15%, insider ownership + compensation structure), Disclosure Quality (15%). Red flags: transformational M&A without plan, repeated guidance misses, high SBC with low hurdles, C-suite turnover within 18 months.
Management Team (Alpha/Beta/Delta): Alpha (CEO) — track record, capital allocation, communication style. Primary Betas (CFO, CPO, CTO, Corp Dev, CMO) — depth and tenure. Red flags: cluster departures, CFO departure near guidance, cluster insider selling.
Board Assessment: Independence ≥ 75%, expertise present, financial expert on audit committee. "Political incest" check: management/board overlap. Red flags: classified board, supermajority voting, tenure > 15yr, CEO as Chair, related-party transactions.
Industry Analysis: Five Forces and SWOT as thinking prompts, not rigid boxes. Read competitor 10-Ks to cross-check management narrative. Do not trust management pronouncements on competition — verify independently. "Explain to 10-year-old" test: describe in 1-2 sentences. "3-5 factors" rule: identify drivers that matter; more than 5 = spread too thin. For formal peer-set construction and relative benchmarking, defer to the peer-bench skill rather than rebuilding it here.
Consensus Reconstruction (run after steps 1-5, never before — reading consensus early anchors the analysis to the expectation it is meant to test): Establish the published sell-side average and its dispersion, then triangulate the effective buy-side expectation, which typically moves ahead of the published figure. Weight recent revisions over the stale average. Output a range with a direction, never a point estimate. Wide dispersion = no consensus exists, so the disconnect framing does not apply; tight dispersion with stale revisions is the highest-value setup. If the buy-side bar cannot be triangulated, mark the disconnect unquantified and flag a coverage gap rather than substituting the published number. State the variant view as: market expects X, evidence indicates Y, because [KPI/MOP finding], closing when [catalyst] by [date].
Catalyst Identification: Identify all catalysts within 20-60 days. Classify: Earnings / Corporate Action / Regulatory / Management / Industry / Macro. Assess: specificity (dateable?), magnitude (≥ 15% high, 5-15% standard, < 5% insufficient), probability, binary vs. spectrum (binary → reduce size). Tumbleweed test: < 1 non-earnings press release/month = avoid. Catalyst stacking: multiple = higher conviction; zero = investment, not trade.
Red Flag Scan: Scan against catalog (see reference). 3+ flags = hard stop for longs. Key flags: non-recurring charges in 3+ of 4 quarters, SBC > 10% revenue, GAAP losses + non-GAAP profits, trade data contradicts management, competitor filings describe different dynamics.
MCP Integration: search_investment_strategies(kind=qualitative) → search_investment_cases(domain=catalyst_driven) → search_by_analogue(event_type, company_situation). Handoff: conviction score (1-10), quantified consensus disconnect (or unquantified), ranked catalyst calendar, KPI summary, MOP score, management/board flags, red flag count.
{ticker}/{YYYY-MM-DD_HHMM}_qualitative-filtering_{affix}.md
unquantified), and the variant view in one structured sentence| Error | Fallback |
|---|---|
search_documents(form_type="earnings_call_transcript") returns empty | Use SEC filings only; flag transcript gap |
| No catalyst within 60-day window | Flag as watchlist item; do not force a catalyst |
search_by_analogue returns empty | Note "no relevant analogues found"; do not fabricate |
See contracts/memory-load.md.
See contracts/snapshot-synthesis.md.
Include ### Key Citations block with 0-10 clickable /v/ URLs.
references/qual-methodology.mdcontracts/citation-and-memory.mdcontracts/output-frontmatter-schema.mdcontracts/memory-load.mdcontracts/snapshot-synthesis.mdcontracts/preflight.mdcontracts/retrieval.md© 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 2 other files (references) in plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering of agentii-ai/agentii-investment-intelligence.
Open the folder on GitHubat commit 86980e1
Qualitative Filtering 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 |
|---|---|---|---|---|---|---|
| Qualitative Filtering this skillagentii-ai/agentii-investment-intelligence | 207 | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Earnings AnalysisWind-Alice/AliceMarket | 130 | 3 repos | ~2.2k | Automated safety check: Pass | None | |
| Equity Research Corebyteseek/Mira | 275 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Earnings Recaphimself65/finance-skills | 3.4k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Xvary Stock Researchsickn33/agentic-awesome-skills | 47k | 2 repos | ~952 | Automated safety check: Pass | MIT | |
| Catalyst ConfirmationSuperior-Trade/superior-skills | 214 | — | ~667 | Automated safety check: Pass | MIT |
Wind-Alice/AliceMarket
Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage.
byteseek/Mira
Run Mira's core single-equity research workflow across fundamentals, financial quality, macro context, technical pricing, events, and thesis framing.
himself65/finance-skills
Analyze a company's most recent (or a specified past) earnings report from Yahoo Finance data (yfinance): actual vs estimated EPS, surprise size, revenue and margin trends, and the stock's price…
sickn33/agentic-awesome-skills
Thesis-driven equity analysis from public SEC EDGAR and market data; /analyze, /score, /compare workflows with bundled Python tools (Claude Code, Cursor, Codex).
Superior-Trade/superior-skills
A skill your agent uses when a Polymarket prediction-market thesis rests on an external event — CPI, Fed, elections, court rulings, ETF decisions — and needs market confirmation before committing.
ginlix-ai/LangAlpha
The evidence, judgement, intake and market-data rules every research deliverable follows.
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
Qualitative stock analysis, management operating plan MOP assessment, key performance indicator KPI identification, catalyst identification and classification, earnings call transcript analysis…. Qualitative Filtering is an agent skill from agentii-ai/agentii-investment-intelligence.
Qualitative Filtering fits situations like: tasks that involve Meeting notes and agendas; tasks that involve OKRs and executive reporting; tasks that involve Stock and market analysis.
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill qualitative-filtering -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering in agentii-ai/agentii-investment-intelligence) into .claude/skills/qualitative-filtering in your project. Claude Code loads it when a task matches its description.
Run `npx skills add agentii-ai/agentii-investment-intelligence --skill qualitative-filtering -a codex`. Or copy the skill folder (plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering in agentii-ai/agentii-investment-intelligence) into .agents/skills/qualitative-filtering 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 qualitative-filtering -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qualitative-filtering, .gemini/skills/qualitative-filtering, .github/skills/qualitative-filtering and .opencode/skills/qualitative-filtering in your project.
SKILL.md names no scripts, command-line tools or credentials: Qualitative Filtering is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. 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.
Qualitative Filtering 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 2.5k tokens (SKILL.md is roughly 9.9k 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 7.9k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Qualitative Filtering: Earnings Analysis (Wind-Alice/AliceMarket, 130 stars), Equity Research Core (byteseek/Mira, 275 stars), Earnings Recap (himself65/finance-skills, 3.4k stars) and Xvary Stock Research (sickn33/agentic-awesome-skills, 47k 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.