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 wrong_if falsifiers, then appends a Convergence section to tasks.md re-proposing the gaps. A clean run leaves tasks.md byte-identical. Deterministic gaps (stale, invalidated) are uncapped; judgment-class gaps are capped per spec 046 Q40.
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See how to installReview the instructions the agent will receive before you install.
Append-only gap closure — the cadence engine of the research orchestration system (spec 046 Q26).
agentii.implement batch (the system detects its own staleness).skills/agentii/synthesize/SKILL.md (pack → author
content.html → assemble). An html_stale finding below means that workflow
must re-run.wrong_if
falsifiers in thesis.md. It never reads git history and never trusts [x]
checkboxes (Q26 A+: the ledger may lie; the correction is deterministic and has
a bounded expiry — the next converge).## Phase N: Convergence
section at the end of tasks.md, with src: refs and content-derived finding
IDs. Existing lines, including previous Convergence sections, are untouched.| Type | Class | Cap |
|---|---|---|
stale (pins older than current) | deterministic | uncapped |
invalidated (wrong_if metric+threshold triggered) | deterministic | uncapped |
missing / partial / contradicts / unrequested | judgment | Q40 cap (≈50) |
# Resolve the kit root first — contracts/kit-root.md. The kit's scripts do NOT ship
# with the skills, so never assume the CWD is the checkout.
KIT=""
for c in "${AGENTII_KIT_ROOT:-}" \
"$(cat "$HOME/.claude/skills/agentii/.kit-root" 2>/dev/null)" \
"${CLAUDE_PLUGIN_ROOT:-}"; do
[ -n "$c" ] && [ -f "$c/scripts/agentii_cmd.py" ] && { KIT="$c"; break; }
done
if [ -z "$KIT" ]; then d="$PWD"; while [ "$d" != "/" ]; do
[ -f "$d/scripts/agentii_cmd.py" ] && { KIT="$d"; break; }; d="$(dirname "$d")"; done; fi
[ -n "$KIT" ] || { echo "agentii kit not found — see contracts/kit-root.md" >&2; exit 1; }
python3 "$KIT/scripts/converge.py" --thesis theses/001-ai-semiconductors \
--pins '{"assumption_pin": 1, "corpus_version": "2026-08", "as_of": "2026-09-08", "constitution_pin": "0.1.0", "skill_pin": "recent-quarter:abc"}'
spec.md or plan.md.hash(entity+metric+period+gap_type)) — an
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3-statement financial model, integrated IS BS CF, income statement projection, balance sheet forecast, cash flow statement, cross-statement balancing, financial model build, operating model, three statement model, integrated financial statements
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Institutional-grade equity research skills for AI agents. 80 Claude-type skills across 14 verticals (equity-research-core, models-and-pitches, bio-pharm, scenarios, quantitative-analysis, idea-generation, options-derivatives, business-intelligence, industry-analysis, macro-strategy, portfolio-strategy, technical-analysis, risk-and-psychology, trading-as-business) powered by agentii.ai's agent-use-ready SEC filing data plane — SEC filings and 15K+ earnings call transcripts, 15.99M XBRL facts, and company profiles for 1,146+ US-public-equity tickers. Features the three-layer retrieval protocol (Document Discovery → Page Map → Deep Read, with deep-outline escalation) — measured, not asserted: 97.5% saved against a sequential read, and the page map itself is 10.0% of one (spec 062 T030, 2026-09-23) — server-side parallel multi-period search via search_cross_period, a full Excel/PPT generation pipeline with 3-tier office backend support, and the spec-046 governance layer (constitution, thesis and single-skill modes, mechanical gates, and a template-owned disclaimer on generated reports).
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Audit spreadsheet, formula error detection, hardcoded cell finder, cross-sheet reference audit, workbook auditor, Excel model audit, financial model QA, spreadsheet review, cell dependency trace, formula integrity check
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Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis, revenue model identification, market sizing TAM SAM SOM, competitive positioning, business unit performance, management team & leadership analysis, what does the company sell, how does the company go to market, business model type platform service product, channel mix direct vs indirect, revenue concentration risk, CEO CFO executive backgrounds and changes
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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 wrong_if falsifiability review. ≈50-finding cap sorted by severity; content-derived finding IDs; incremental scoping with three backstops; lifecycle hooks at pillar-complete / thesis-complete / pre-reduction.
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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 sequence, wedges, double tops and bottoms, triangles, head and shoulders, climaxes, measured moves, support and resistance
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