"Understanding Task Analysis, Splitting, and Execution Strategies" matching MCP tools:

• get_strategy_leaderboard

  OneQAZ Trading Intelligence

  Purpose: Top RL-learned research strategies — GLOBAL pool + per-symbol partition. Layer E evidence. The GLOBAL pool may include synthesized win_rate values, so per_symbol_leaderboard is the primary measured-edge surface for trust auditing. When to call: final trust-validation step. Prerequisites: none. Next steps: market://{market_id}/signals/summary for live signals. Caveats: `min_trades` filter enforces statistical validity. Strategies are paper-tested, not real-money executed. Args: market_id: Market identifier (crypto, kr_stock, us_stock) target_market: Alias for market_id (backward compat) top_n: Top N strategies to return (default 20) limit: Alias for top_n (client-compat) min_trades: Minimum trades count for inclusion (default 10) include_per_symbol: Include per-symbol PG partition results (default True) Disclaimer: Information only, not investment advice.

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• get_strategy

  Heista

  Read a creative strategy in full by its powersource_id. Returns the same brand-merged bundle shape as get_powersource(data) — buyer profile, 12 behavioral tensions, angles, narrative direction, tone of voice, selling points, CTAs, proof, brand story, homepage data, offering — projected through the public PowerSource API serializer. Use this when you already have a powersource_id (from list_strategies) and want the full strategy payload in one call, without the job_id round-trip that get_powersource needs. Archived strategies are excluded by default (parity with list_strategies). Pass include_archived=true to read archived strategies. Read-only, free, account-scoped.

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• malware_get_template

  website-search

  Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

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• woet_classifier

  cpp-cpm-engine

  Worked-vs-On-time Execution Timeline (WOET) per-activity day-by-day classification of as-built execution against baseline. For each pairable activity (matched by ``task_code``), classifies execution into 4 day-states: - PROGRESS: work performed during the baseline-planned window - GAIN: work performed BEFORE the baseline window opened - EXTENDED: work performed AFTER the baseline window closed - VOID: baseline-window day where activity was NOT active This is a CPP-disclosed enhancement layered on top of AACE 29R-03 §3.3 Windows Analysis — a per-day execution classifier (Progress/Gain/Extended/Void) NOT itself AACE-defined. It is not a substitute for fragnet-based AACE 29R-03 §3.7 (TIA) modeling. It gives the trier-of-fact a calendar picture of how the project executed versus how it was supposed to execute, which is otherwise buried in finish-date deltas. Use this tool when you want a per-activity execution-quality picture (on-time %, count of activities with VOID days, etc.). Args: baseline_xer_path: server-side path to baseline XER (target dates). actual_xer_path: server-side path to as-built XER (act dates). baseline_xer_content: full text of baseline XER (alternative). actual_xer_content: full text of as-built XER (alternative). Supply EXACTLY ONE of path/content per pair. today: optional ISO date (YYYY-MM-DD) reference for in-progress activities. Defaults to actual XER's last_recalc_date if available, else today's date. Returns: { "method": "WOET", "standard": "AACE 29R-03 §3.3 Windows Analysis — per-day execution classification overlay (CPP-disclosed enhancement, not AACE-defined)", "today": "YYYY-MM-DD", "project_totals": {progress, gain, extended, void}, "per_activity": [{code, name, baseline_start, ...}, ...], "on_time_pct": float (0-100) }

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• atlas_get_analysis

  CareerProof MCP

  Retrieve a completed analysis result by analysis ID. Returns scores, competency breakdown, and recommendations. analysis_id comes from atlas_start_gem_analysis response or atlas_list_analyses. Only works after analysis is completed -- check with careerproof_task_status first. Free.

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• list_strategies

  Heista

  List all PowerSource strategies (scans) for a brand. A brand has many strategies — one per scanned URL. Product-page strategies carry product_name and is_product_page=true; use these to label them in conversation or to pick the right one for a product-focused generation. Returns powersource_id (use as the brief/PowerSource id everywhere else), product_name, scanned_at, source_url, is_pinned. Free, read-only. Paginated via cursor.

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• free2aitools_rank

  Free2AITools

  Keyword-search AI entities using the task text as query input. Returns FNI-ranked catalog entries. Does not perform task-fit recommendation or compatibility analysis. Read-only, no side effects. May return a retryable transient 503 under cold-path or fallback budget limits; retry according to Retry-After. Use free2aitools_search for keyword-based discovery, or free2aitools_select_model to apply hardware/license metadata filters.

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• list_service_capabilities

  Molt2Meet

  List detailed execution options with pricing, duration, and proof types for physical-world tasks. Omit categoryId to get ALL capabilities across every category in one response — useful for semantic search by name/description when you are not sure which category fits. Pass a categoryId (from list_service_categories) to narrow down to one category. Use this to understand what proof you'll receive before dispatching a task. No authentication required. Next: dispatch_physical_task.

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• get_execution_trace

  governance-platform

  Run validation and return the detailed execution trace. Shows the exact sequence of validation nodes that ran, whether each was deterministic, and the runtime of each node. Use for debugging, compliance audits, or understanding exactly what the platform checked. Different from validate: validate returns the verdict (PASS / FAIL / REVIEW) and the state vector summary. get_execution_trace returns everything validate does PLUS the per-node trace records. Use validate for normal operation; use get_execution_trace when you need to see inside the pipeline (debugging, audit prep, latency analysis). The trace is the same whether validation passes or fails — every node that ran is recorded with its inputs, outputs, and timing. Args: api_key: GeodesicAI API key (starts with gai_) structured_data: The data to trace validation for blueprint: Blueprint to validate against. Caller must own the Blueprint. Returns: status: "PASS" / "FAIL" / "REVIEW" / "ERROR" determinism_hash: cryptographic hash of inputs + rules trace: ordered list of node records, each with: node_name, node_type, deterministic (bool), runtime_ms, inputs, outputs node_count: number of nodes in the trace deterministic_count: how many nodes were deterministic state_vector: same state_vector validate returns

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• add_service_interest

  Molt2Meet

  Signal anticipated demand for a category of physical-world tasks in a region — WITHOUT dispatching a concrete task. Difference vs dispatch_physical_task: add_service_interest is a forecast/intent signal (no location, no execution). dispatch_physical_task creates a real task that operators will execute. Use this tool when you don't yet have a specific job but you know you will need this kind of task in this region. Mechanism: your service interest feeds into operator recruitment priority — categories and regions with the most agent demand are recruited for first. Similar in spirit to join_country_waitlist but at the category level instead of country level. Use cases: long-term planning (e.g. 'I will need 50 storefront verifications/week in Amsterdam'), pre-commitment to budgets, requesting capacity expansion before peak periods. Requires: API key from register_agent. Optional: use a serviceCategoryId from list_service_categories. Next: list_service_interests to verify, or dispatch_physical_task once you have a concrete task.

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• read_guides

  Arcadia Finance

  Get Arcadia workflow guides and reference documentation. Call this before multi-step workflows (opening LP positions, enabling automation, closing positions) or when you need contract addresses, asset manager addresses, or strategy parameters. Topics: overview (addresses + tool catalog), automation (rebalancer/compounder setup), strategies (step-by-step templates), selection (how to evaluate and parameterize strategies).

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• google_ads_render_search_terms_analysis

  paid-ads

  Preferred user-facing Google Ads search-terms analysis tool. Renders the search-terms analysis dashboard and can either take analysisPayload from google_ads_analyze_search_terms or fetch the analysis directly when called with search-term-analysis arguments.

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• search_medical

  paper-mcp

  Evidence-graded MEDICAL literature search (PubMed + Europe PMC). Unlike search_all (generic, ranks high-cited reviews/guidelines above trials), this filters by research type via PubMed Publication-Type tags and re-ranks by the evidence pyramid (meta-analysis / systematic review > RCT > cohort > ...), so the actual clinical trials surface first. Open-access full text is pulled from Europe PMC by PMID. `query` should be English keyword/boolean text (PubMed maps it); do natural-language/multilingual understanding upstream. Returns hits with pmid/doi/study_type/evidence_level/citations/abstract and, when open-access, fulltext.

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• read_strategy_list

  Arcadia Finance

  Get Arcadia LP strategies. Use featured_only=true for curated top strategies (recommended first call). Returns a paginated list with 7d avg APY for each strategy's default range. Increase limit or use offset for pagination. All APY values are decimal fractions (1.0 = 100%, 0.05 = 5%). For full detail on a specific strategy (APY per range width), use read_strategy_info.

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• get_trident_spec

  trident

  Returns the complete Trident 2D specification including grammar, syntax rules, coordinate system, containers, nodes, connections, shapes, and icon reference. Use this when you need deep understanding of the Trident DSL.

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• working_capital_fx_hedge_optimizer

  gapup-mcp

  For CFOs managing multinational working capital, this tool analyzes real-time ECB and FRED foreign exchange rates to recommend optimal hedging strategies. Input base currency, target currencies, and working capital amounts to receive forward contract suggestions, natural hedge opportunities, and cost-benefit analysis of various hedging instruments (forwards, options, swaps). Outputs include hedge ratios, estimated cost savings, and risk reduction metrics.

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• tascan_list_issues

  TaScan

  List all issues for a task list (event). Returns open, acknowledged, and resolved issues with severity, type, and category. Use this to discover issues that need AI analysis via tascan_analyze_issue.

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• get_tool_guide

  FundingLandscape

  Get comprehensive usage guide for FundingLandscape tools. Call this FIRST to understand optimal workflows, parameter usage, and best practices. Returns detailed documentation for search tools, filters, and token optimization strategies.

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• get_top_trading_strategies

  Helium MCP Server - News, Markets & AI

  Get the top-ranked short volatility and long volatility option trading strategies. Returns two ranked lists — short_volatility (sell premium / theta strategies) and long_volatility (buy premium / gamma strategies) — each containing up to `limit` tickers. Each entry has the same fields as get_ticker: - ticker, name, latest_price, page_url - bullish_case, bearish_case, potential_outcomes, takeaway, analysis_date (AI-generated, when available) - price_forecast_days, price_forecast_percent, price_forecast_lower/upper_bound_percent (when available) - iv_rank_percentile (0-100, IV rank over past year, when available) - short_vol_call, short_vol_put: best short volatility option packs (when available) - long_vol_call, long_vol_put: best long volatility option packs (when available) Sort options: - "helium_rank" (default): Helium AI edge score — best overall expected value - "odds_of_profit": Highest probability of profit - "historical_performance": Best annualized historical P&L across backtested trades - "reward_to_risk": Best reward-to-risk ratio - "smallest_max_loss": Strategies with the smallest maximum possible loss Args: sort: Ranking method (default "helium_rank"). One of: 'helium_rank', 'odds_of_profit', 'historical_performance', 'reward_to_risk', 'smallest_max_loss'. limit: Number of results per strategy type (1-20, default 5).

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• x711_hive_consensus

  x711 — Universal Agent Gas Station

  Swarm truth engine — query collective agent agreement on any thesis. Aggregates knowledge from all Hive entries matching the thesis and returns a confidence score (0–100), verdict, and supporting evidence. Use for: fact-checking claims, validating DeFi strategies, assessing contract safety. Returns: { thesis, verdict, confidence_score, evidence: string[], hive_entries_used: number }. Requires API key.

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