ash1794

Performs a fast 6-point quality check for technical documents (specs, design docs, READMEs). Use after editing any specification or design document.

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Closes a large backlog of findings (a gap analysis, an audit, or 10+ bugs) in prioritized waves. Loops through triage, dependency analysis, parallel fix streams, a test gate, and re-audit until the target is met. Use after a gap analysis, audit, or review produces 10+ findings, or to burn down a large bug or tech-debt backlog.

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Writes a handover document so another person, another agent, or a different tool can pick up multi-session work cold. Use when handing work to someone else, switching tools, or pausing work that will not resume in the same session.

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Validates PRD, user stories, or feature requirements against SMART criteria. Use when reviewing requirements to catch vagueness before it causes expensive rework.

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Implements snapshot/golden file tests with temporal normalization so tests don't break daily. Use when implementing tests that compare output against expected snapshots.

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Generates fuzz test scaffolding for parsers handling external input (YAML, JSON, config files, user input). Seeds corpus from existing fixtures and runs initial pass. Use when implementing or changing a parser, or any code that ingests user input, webhook payloads, API responses, or file formats.

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Validates completed work against defined acceptance criteria. Use after completing a task that has specific success criteria defined in issues, specs, or task descriptions.

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Routes to the right vibe-engineering skill for the current task and lists the full catalog. Use when the user asks which skill to use, asks what vibe-engineering can do, or is unsure how to approach a task.

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Runs the Implement→Review→Test→Fix cycle until the work is actually clean, with evidence. Use after any non-trivial implementation and before claiming it is done.

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Generates edge case, failure mode, and spec-driven test cases. Covers boundary values, nil inputs, concurrency, resource exhaustion, malformed data, and requirement-linked traceability tests. Use after happy-path tests exist and before claiming coverage is complete, when requirements lack tests, or before a security review.

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Catches shortcuts and reward hacking — weakening or deleting tests to make them pass, hard-coding expected outputs, silently dropping requirements, or claiming work is done without running it. Use before declaring a task complete and whenever a test or requirement feels like it's in the way.

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Safely integrates commits from parallel agent branches using sequential cherry-pick. Use after parallel work completes in isolated branches or worktrees.

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Audits tests for concurrency safety — race conditions, shared mock state, cleanup ordering. Use when writing tests that involve goroutines, async operations, or shared mutable state.

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Enforces tiered test coverage standards with three dimensions — line coverage by tier, spec-to-test traceability, and spec-to-code implementation mapping. Use before claiming code is complete.

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Extracts and records architectural decisions from diffs, conversation context, and explicit choices. Supports automatic extraction from staged changes, deduplication against prior decisions, and persistent ADR-format logging with spec traceability. Use after a significant design or architecture choice, before committing a diff that embeds implicit decisions, or when the same question keeps resurfacing.

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Challenges a recommendation, design, large change, or any artifact submitted for hard review (spec, proposal, policy, plan) across 5 dimensions (consistency, completeness, actionability, alignment, risk), from the standards of a named senior expert in the artifact's domain and ideally from a fresh context or a different model. Searches assuming defects exist and reports only those that survive evidence. Panel mode runs several independent lenses in parallel on a release candidate, verifies every finding against the current head, and routes confirmed ones to file owners. Use before shipping a significant recommendation, design, large branch, or multi-agent release, or when asked to tear something apart, be brutally honest, or poke holes in it.

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Refuses "flaky" as a diagnosis. Turns an intermittent failure into a reproduction by isolating it from the environment, naming the variable that controls it, forcing that variable, and measuring before and after with enough runs to count. Separates real defects from environment contention with evidence, and never retries to green or widens a threshold. Use when a test, performance check, or deploy step fails intermittently or passes on rerun.

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Assesses production readiness or audits a codebase against its specs. Supports quick static mode, deep 17-dimension audit, or single-dimension focus. Use before a production launch, after a major refactor, when inheriting a codebase, or when someone asks how done the project is.

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Performs end-of-iteration review with quality grading, metrics, and trend analysis. Use at the end of each development iteration or sprint.

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Scans staged changes for secrets, debug statements, TODOs without references, and other common commit mistakes. Use before creating any commit.

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Keeps private and unapproved material out of a public build. Scans the built output (HTML, serialized component payloads, client JS and CSS chunks, static data routes, public files) against a private tier that always applies and a draft tier that applies in production. Gates work-in-progress so it shows in preview and is absent from production, and keeps sign-off in a ledger only the human writes. Use when a site or app publishes content that agents drafted or that came from private sources.

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Captures reusable knowledge after work is done — learnings from feedback or failures, resolved bugs (symptom, root cause, prevention), and recurring code patterns — into the project's persistent memory file. Use after feedback, a non-trivial bug fix, a failed attempt, or the third repetition of a pattern.

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Researches real projects, papers, and documented failures before proposing a new feature, architecture, or technology choice. Use for design decisions with multiple valid approaches, not for implementing an existing spec or fixing a known bug.

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Generates a behavioral scenario acceptance matrix for comprehensive test coverage planning. Maps user scenarios to acceptance criteria with stable IDs. Use when planning test coverage for a complex feature, before a release or milestone review, or when someone asks what is tested.

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