Edge Hint Extractor
Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection.
MCP get_skill({ skillId: "edge-hint-extractor-178c82ed" })Use this skill with your agent
Create a free account and connect via MCP
# Edge Hint Extractor ## Overview Convert raw observation signals (`market_summary`, `anomalies`, `news reactions`) into structured edge hints. This skill is the first stage in the split workflow: `observe -> abstract -> design -> pipeline`. ## When to Use - You want to turn daily market observations into reusable hint objects. - You want LLM-generated ideas constrained by current anomalies/news context. - You need a clean `hints.yaml` input for concept synthesis or auto detection. ## Prerequisites - Python 3.9+ - `PyYAML` - Optional inputs from detector run: - `market_summary.json` - `anomalies.json` - `news_reactions.csv` or `news_reactions.json` ## Output - `hints.yaml` containing: - `hints` list - generation metadata - rule/LLM hint counts ## Workflow 1. Gather observation files (`market_summary`, `anomalies`, optional news reactions). 2. Run `scripts/build_hints.py` to generate deterministic hints. 3. Optionally augment hints with LLM ideas via one of two methods: - a. `--llm-ideas-cmd` — pipe data to an external LLM CLI (subprocess). - b. `--llm-ideas-file PATH` — load pre-written hints from a YAML file (for Claude Code workflows where Claude generates hints itself). 4. Pass `hints.yaml` into concept synthesis or auto detection. Note: `--llm-ideas-cmd` and `--llm-ideas-file` are mutually exclusive. ## Quick Commands Rule-based only (default output to `reports/edge_hint_extractor/hints.yaml`): ```bash python3 skills/edge-hint-extractor/scripts/build_hints.py \ --market-summary /tmp/edge-auto/market_summary.json \ --anomalies /tmp/edge-auto/anomalies.json \ --news-reactions /tmp/news_reactions.csv \ --as-of 2026-02-20 \ --output-dir reports/ ``` Rule + LLM augmentation (external CLI): ```bash python3 skills/edge-hint-extractor/scripts/build_hints.py \ --market-summary /tmp/edge-auto/market_summary.json \ --anomalies /tmp/edge-auto/anomalies.json \ --llm-ideas-cmd "python3 /path/to/llm_ideas_cli.py" \ --output-dir reports/ ``` Rule + LLM augmentation (pre-written file, for Claude Code): ```bash python3 skills/edge-hint-extractor/scripts/build_hints.py \ --market-summary /tmp/edge-auto/market_summary.json \ --anomalies /tmp/edge-auto/anomalies.json \ --llm-ideas-file /tmp/llm_hints.yaml \ --output-dir reports/ ``` ## Resources - `skills/edge-hint-extractor/scripts/build_hints.py` - `references/hints_schema.md`
Related Skills
More skills in Data, AI & Research
Ablation Planner
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
Ablation Planner
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
About
Provides information about the bitwize-music plugin, its version, and its creator. Use when the user asks about the plugin, its purpose, version, or capabilities.
Ab Test Analysis
Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
Academic Search
Search and analyze academic literature. Find papers, understand research methodologies, and synthesize academic findings for research projects.
Adaptyv
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
Explore Other Categories
Skills from other categories with shared topics
Dividend Growth Pullback Screener
Use this skill to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI ≤40). This skill combines fundamental dividend analysis with technical timing indicators to identify buying opportunities in strong dividend growers during short-term weakness.
Downtrend Duration Analyzer
Analyze historical downtrend durations and generate interactive HTML histograms showing typical correction lengths by sector and market cap.
Dual Axis Skill Reviewer
Review skills in any project using a dual-axis method: (1) deterministic code-based checks (structure, scripts, tests, execution safety) and (2) LLM deep review findings. Use when you need reproducible quality scoring for `skills/*/SKILL.md`, want to gate merges with a score threshold (for example 90+), or need concrete improvement items for low-scoring skills. Works across projects via --project-root.