--- name: er title: AI4L - Main Skill for Evidence Review Creation and Auditing using @AGENTS description: AI4L - Main Skill for Evidence Review Creation and Auditing using @AGENTS author: forever-healthy author_url: https://github.com/forever-healthy/AI4L/tree/main/.claude/skills/er license: MIT version: 0.1.0 execution_mode: open jurisdiction: general practice: litigation language: en --- # AI4L - Main Skill for Evidence Review Creation and Auditing using @AGENTS ## General Rules * Parse the user's input to determine which sub-command to execute * Set [args] to $ARGUMENTS * Note the [start_time] when beginning any command, and report the [time_taken] when done * All generated results go in [creation_dir] as .md files * Do not edit or modify any files outside [creation_dir] * Full lines formatted as `line` comments must be ignored when processing commands. ## COMMAND: create {topic} `Create an evidence review (ER) using the @er-creator agent.` * If no [args] are given { * Report: `usage: /er create {topic}` * exit } otherwise { set [topic] to [args] } * Report: `create: [topic]` * @er-creator: `[topic]` * Wait until the agent finishes * Report: `filename: [filename]` ## COMMAND: audit {er} `Audit an ER using the @er-auditor agent.` * If no [args] are given { * Set [target_er] to the newest ER in [creation_dir] } else { * Set [target_er] to [args] } * Report: `audit: [target_er]` * @er-auditor: `[target_er]` * Wait until the agent finishes and returns the result * Report: `target_er: [target_er]` * Report: `pass_rate: [pass_rate]` ## COMMAND: fix {er} `Audit and fix an ER using the @er-fixer agent.` * If no [args] are given { * Set [target_er] to the newest ER in [creation_dir] } else { * Set [target_er] to [args] } * Report: `fix: [target_er]` * @er-fixer: `[target_er]` * Wait until the agent finishes and returns the result * Report: `target_er: [target_er]` * Report: `pass_rate: [pass_rate]` ## COMMAND: combine {er} `Create a final QA file from all audits` * If no [args] are given { * Set [target_er] to the newest ER in [creation_dir] } else { * Set [target_er] to [args] } * Report: `combine: [target_er]` * @er-combiner: `[target_er]` * Wait until the agent finishes and returns the result * Report `QA file: [new_qa_filename]` ## COMMAND: iterate {er} `Loops audit/fix cycles up to [max_audits] times until [needed_passes] show 100% pass rate.` * If no [args] are given { * Set [target_er] to the newest ER in [creation_dir] } else { * Set [target_er] to [args] } * Report: `iterate: [target_er]` Initialize { * Set [iteration] = 0, [consecutive_passes] = 0 } Loop while [iteration] < [max_audits] and [consecutive_passes] < [needed_passes] { * @er-fixer: `[target_er]` * Wait until the agent finishes and returns the result * If the [pass_rate] is 100%, increment [consecutive_passes]; otherwise reset to 0 * Increment [iteration] * Report: "Iteration [iteration]: Pass rate = [pass_rate]% ([consecutive_passes]/[needed_passes] consecutive passes needed)" } * @er-combiner: `[target_er]` If [iteration] < [max_audits] { * Return: `status: success` } else { * Return: `status: failed` } * Return: `target_er: [target_er]` * Return: `iterations: [iteration]` ## COMMAND: full {er} `A create and multi-pass audit workflow.` * Execute the "create" command * Execute the "iterate" command ## COMMAND: compare {intervention} `Compares all ERs for a given intervention, typically from different AI models or versions, to determine which is strongest based on content quality and the latest QA audit results.` * If no [args] are given { * Set [intervention] to intervention in the frontmatter of the newest ER in [creation_dir] } else { * Set [intervention] to [args] } * Report: `compare: [intervention]` * Compare all ERs in [creation_dir] with a similar [intervention] in their frontmatter * Compare the quality of the content * Be detailed * Take into account the latest "QA.md" for each. * Present a clear recommendation of which ER is strongest and why.