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.
Institutional-grade equity research skills for AI agents. 31 Claude-type skills across 5 verticals (equity-research-core, business-intelligence, industry-analysis, models-and-pitches, quantitative-analysis) powered by agentii.ai's agent-use-ready SEC filing data plane — 10 years of filings, XBRL financials, earnings…
Med-adapted earnings preview: consensus estimates, historical surprises, guidance sensitivities, and the FDA-catalyst overlay (PDUFA/AdCom/trial readouts near the print) for biotech/pharma names.
Med peer benchmarking: select actual biotech/pharma peers via the med universe (drug/indication overlap where possible) and compare med-relevant metrics — pipeline depth, catalyst density, cash position, margins, valuation multiples.
Med-adapted recent-quarter review: last print financials, pipeline-milestone awareness, and FDA-event context — reads the quarter through the med lens (milestones moved, runway, regulatory updates) rather than generic financials alone.
Med-sector overview using the 049 taxonomy (med.medicinesbiotech, med.medicaldevices, med.healthcareservices, med.lifesciencestools) with med trends, catalysts, and FDA-decision context. Use to frame any biotech/pharma analysis before diving into a single name.
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 (Munger: invert, always invert), and wrongif falsifiability review. ≈50-finding cap sorted by severity; content-derived…
Append-only gap closure and the cadence engine for research theses. Evaluates artifact CURRENT state (never git history, never task checkboxes) against current pins and wrongif falsifiers, then appends a Convergence section to tasks.md re-proposing the gaps. A clean run leaves tasks.md byte-identical. Deterministic…
The Auto 档 scenario — a soft-plan orchestrator for a complete fundamental equity research thesis: understand → financials → valuation → synthesize. The body is a soft plan (stages), not a rigid DAG; correctness is enforced by each referenced skill's own requires: preconditions, never by this plan's rigidity (Q2).
Author the research plan — fundamentals first, trade ideas last; Constitution Check evaluated twice; Deviation Register with mandatory Expiry; emits the four side artifacts (brief/entities/reproduce/contracts). Technical (marketdatastage: early) theses MUST emit the entities.md bars schema before implement (Q42).
Create a research thesis — theses/{nnn}-{slug}/ via mkdir-as-CAS, pillar-prioritized spec.md, initialized thesis.md, and the thesis-quality checklist. Refuses creation while the workspace constitution is unratified (spec 046 Q83 A+).
Decompose the plan into research tasks — one task per ticker × skill × mode, grouped by pillar, [P]-marked by the different-files-and-no-incomplete-deps rule, with source-refs. mode: all expands to N tasks at generation, never exists as one task (Q79).
★not rated 203 todayA63 tokens
Apache-2.0
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: