agentsclimarketplace

Secular trends

Skill agentii-ai/agentii-investment-intelligence/plugins/agent-plugins/agentii-equity-agent/skills/agentii/secular-trends

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.

Install
npx -y skills add agentii-ai/agentii-investment-intelligence --skill secular-trends

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Secular technology trends, technology adoption cycle, disruption risk, AI impact analysis, digital transformation, industry 4.0 trends, technology moat, innovation trajectory, R&D effectiveness, tech competitive positioning

SKILL.md

6.7 KB, as published. Nobody here has run it

<!-- analog: idea-generation -->

Preflight

Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace style.md override, memory load, and coverage check. See contracts/preflight.md.

Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md.

Triggers

  • analyze dim secular tech trends
  • run dim secular tech trends analysis
  • produce dim secular tech trends report
  • dim secular tech trends breakdown
  • dim secular tech trends deep dive
  • build a dim secular tech trends
  • assess dim secular tech trends
  • quantify dim secular tech trends
  • compare dim secular tech trends across peers
  • review dim secular tech trends for
  • generate dim secular tech trends on
  • dim secular tech trends for investment decision

Defaults

ParameterDefaultNotes
lookback_years3Historical data window
include_peersfalseWhether to surface a peer comparison block
<!-- BEGIN port-dimension-prompts methodology + modes -->

Methodology

Retrieval Scope

This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings spanning multiple fiscal periods). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.

Retrieval Strategy

Follow the retrieval strategy decision tree in contracts/retrieval.md. This skill uses:

  • Branch (a) for structured financial metrics via search_xbrl_facts with list_xbrl_concepts pre-condition for unfamiliar concepts.
  • Branch (c) for single-period document queries via direct read_source_outlineread_source_pages.
  • Branch (d) for simple lookups via get_company_profile / search_earnings_calendar.

**Layer 1 secondary_label allowlist **: prefer ?secondary_label=other_events_8_01 to surface trend-related 8-Ks (technology disruption, regulatory shifts, demographic events) before Layer 2.

Temporal Scope

Default: 12 fiscal quarters (max 20). Secular tech trends: 12 quarters (3 fiscal years) for long-range technology adoption cycles

Tool Allowlist

See frontmatter allowed_tools.

Protocol

This skill delivers analyst-grade output via 8 addressable mode(s); invoke with --mode=<slug> / --modes=<slug1>,<slug2> / --mode=all (see Mode syntax. The default invocation (no flag) runs the essentials_modes subset declared in this skill's frontmatter.

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}_secular-trends_tech-trends.md .

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 — inline /v/ citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index.
  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; 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.

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 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.

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."
Sector mismatchPeer sector != target sectorFilter out mismatched peers"Removed {n} peer(s) due to sector mismatch."
Insufficient historyTicker <3 years on public marketsDowngrade to limited-history profile"Limited historical data; analysis adjusted accordingly."
MCP unreachablePreflight probe failsHalt with actionable error"agentii data plane unreachable; check connection."

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.