turnaround

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Turnaround analysis, stagnation detection, performance inflection, operational improvement, restructuring analysis, management change impact, cost cutting effectiveness, business transformation, recovery trajectory, operational metrics improvement

AI & Automation 206 stars 16 forks Updated 2 days ago Apache-2.0

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Quality Score: 94/100

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Description 5%
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Skill Content

<!-- analog: thesis-tracker --> ## 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 turnaround stagnation - run turnaround stagnation analysis - produce turnaround stagnation report - turnaround stagnation breakdown - turnaround stagnation deep dive - build a turnaround stagnation - assess turnaround stagnation - quantify turnaround stagnation - compare turnaround stagnation across peers - review turnaround stagnation for - generate turnaround stagnation on - turnaround stagnation for investment decision ## Defaults | Parameter | Default | Notes | |---|---|---| | lookback_quarters | 4 | Historical data window — matches `temporal_scope.default_quarters` | | include_peers | false | Whether to surface a peer comparison block | ## Methodology ### Retrieval Scope This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings and earnings call transcripts 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_fa...

Details

Author
agentii-ai
Repository
agentii-ai/agentii-investment-intelligence
Created
4 months ago
Last Updated
2 days ago
Language
Python
License
Apache-2.0

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