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Evaluates and sharpens content hooks using The Hook Stack™ framework. Use when scoring headlines, refining hooks for video/social/newsletter, or when asked to "evaluate this hook", "run through hook stack", or "score my headline".
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Evaluate, compare, and manage vendor relationships. Trigger with "evaluate this vendor", "compare vendors", "vendor review", "should we renew", "RFP", or when the user is making procurement or vendor decisions.
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Evaluate a single retort experiment run. Score the generated code against the task's TASK.md requirements, run its build and tests, compute metrics, and emit a structured evaluation report plus a machine-readable findings file.
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Determine technologies needed to build the product, making build/buy/integrate decisions during PRD v0.5 Red Team Review. Handles both greenfield and brownfield contexts. Triggers on requests to select tech stack, evaluate technologies, make build vs. buy decisions, discover existing assets, or when user asks "what technologies?", "select tech stack", "build or buy?", "what do we reuse?", "existing stack", "technical decisions", "what tools do we need?", "evaluate solutions". Consumes FEA- (features), SCR- (screens), RISK- (constraints). Outputs TECH- entries with decisions, rationale, and trade-offs. Feeds v0.6 Architecture Design.
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Influencer Discovery workflow skill. Use this skill when the user needs Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Influencer Discovery workflow skill. Use this skill when the user needs Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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This skill channels the reasoning of Walter C. Willett, nutrition epidemiologist at Harvard University. Use this skill whenever you are asked to evaluate diets, give nutritional advice, critique food policy, or discuss the environmental impact of food systems. Trigger this skill for topics like macronutrient quality (fats vs. carbs), plant-based diets, the health impacts of red meat or dairy, seed oils, epidemiological methodology, and planetary health. Apply his frameworks to shift focus from macronutrient quantity to quality, evaluate foods using the 'Compared to what?' rule, and prioritize public health over personalized nutrition fads.
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Objectively evaluate a UI/web design against the pols.dev anti-slop design law: detect catalogued slop tells with cited evidence, score 8 weighted axes (color, type, components, layout, motion, execution, signature, cohesion), and emit a Slop Report with a 0–100 Slop Index and grade. Use when the user asks to "evaluate design slop", "slop report", "is this design AI slop", "audit this landing page design", "de-slop review", or wants an objective score of how generic/machine-made a design looks. To fix text (not design), use human-ai or humanizar skills instead.
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Run scored behavioral evaluations and repair gaps. Use when the user says "evaluate this agent" or "I want proof this behaves correctly"
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Evaluate technologies and competitive developments against Genesis architecture
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Evaluate content for personal relevance to the user using the user model
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Internal Harness instruction source for evaluate. Route through visible Harness aliases instead of invoking directly.
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Use when comparing two or more code implementations against a spec or requirements doc. Triggers on "which repo is better", "compare these implementations", "evaluate both solutions", "rank these codebases", or "judge which approach wins". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality — use code review skills instead. Does NOT evaluate strategy docs — use strategy-review. Requires a spec file and 2+ repo paths.
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Analyze agricultural climate risk systems for weather impact modeling, crop insurance, drought/flood prediction, soil moisture, and carbon tracking. Use when: 'assess crop climate risk', 'evaluate weather yield models', 'review crop insurance integration', 'audit drought prediction', 'check carbon sequestration tracking', 'analyze farm adaptation planning', 'evaluate DSSAT or APSIM models'.
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Evaluate model performance — check for accuracy drops, data drift, and error patterns. Use when asked about "model accuracy dropped", "evaluate the model", "check for drift", or "model performance".
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Evaluate and iterate on the SDLC Layer Separation Architecture implementation. Runs validation checks (cross-references, doc completeness, layer metadata, integration points), produces a findings report, and supports iterative fixes. Use when validating first-pass implementation, before claiming layer work is complete, or when improving layer docs/schema.
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Evaluate a codebase for agent-friendliness based on autonomous agent best practices. Use when asked to "evaluate for agents", "check agent readiness", "audit for autonomous execution", "assess agent-friendliness", or when reviewing infrastructure for unattended agent operation. Also use when asked about making a codebase more suitable for AI agents or autonomous workflows.
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Evaluate alternatives through a weighted multi-criteria decision matrix. Use when the user calls for the *evaluation* of *alternatives*, wants to *compare* things, or asks what the best is from a list of choices.
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Evaluate whether an OSS repo is worth long-term investment before committing time. Assesses project health, governance, community, bus factor, and trajectory. Use when deciding whether to contribute to a specific repo, choosing between multiple repos, or evaluating a project's sustainability. Not for checking if a repo accepts contributions — use oss-find-issue for that.
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Use Google Agent Development Kit to define, test, evaluate, and deploy code-first Python agents with tools, sessions, HITL confirmation, and multi-agent orchestration.
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Scaffold, run, inspect, and evaluate model-agnostic agents that connect to MCP servers, skills, shell tools, and workflow packs.
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Rates any SKILL.md on a 0-100 scale across 10 dimensions with a SHIP / REWORK / SCRAP verdict. Evaluates trigger precision, instruction clarity, output predictability, edge case coverage, anti-hallucination guardrails, developer experience, composability, open-source readiness, wow factor, and real-world utility. No flattery — calibrated against Anthropic's own skill-creator rubric. Use this skill whenever someone says "score this skill", "rate my skill", "is this skill good", "skill review", "skill audit", "roast my SKILL.md", "grade this", "will this skill work", "evaluate my skill", "how good is this", or pastes a SKILL.md and asks for feedback. Also trigger when comparing two skills, benchmarking a skill collection, or asking "what's wrong with this skill" — even without the word "score".
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Evaluate tabulated subcontractor bids against specs and drawings — scope gap analysis, exclusion risk scoring, award recommendation. Triggers: 'evaluate bids', 'bid evaluation', 'lowest responsible bidder'.
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Evaluate and compare levitation mechanisms for a given application through a structured trade study. Covers magnetic (passive diamagnetic, active feedback, superconducting), acoustic (standing wave, phased array), aerodynamic (hovercraft, air bearings, Coanda effect), and electrostatic (Coulomb suspension, ion traps) mechanisms. Use when selecting the most appropriate levitation approach for transport, sample handling, display, bearings, or precision measurement applications.
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