Emit Postgres.sql and SQLite.sql from a single schema spec so tools work across both drivers without duplicating DDL by hand. Use when designing a schema that needs to support both shared Postgres deployments and zero-config SQLite. Reduces two-file sync burden to a single source edit.
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Package conversation research into a GSD-ready mission package. Produces a three-stage Vision → Research → Mission pipeline as a LaTeX PDF following GSD/NASA SE methodology, designed to be handed to gsd-skill-creator for execution. Use this skill when the user has been discussing, researching, or brainstorming a topic and then asks to turn it into a research mission, research pack, mission package, or says 'package this as a mission', 'make this a research pack', 'turn this into a mission for skill-creator', 'create a research mission from this', or 'use the research mission skill'. The skill harvests findings, sources, and structure from the current conversation and any prior research, then produces the complete pipeline document. Also trigger if the user asks to 'create a research mission on [topic]' cold — in that case, conduct web research first, then package.
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Security hygiene for GSD's self-modifying skill and agent system. Use this skill whenever: creating, editing, or deleting skill files (.claude/skills/, .claude/commands/), modifying agent definitions (.claude/agents/), working with YAML configuration or chipset files, handling JSONL observation data (.planning/patterns/), processing community-contributed skills or chipsets, any file path operations that could involve user input, or when installing/updating project-claude configuration. Also activates for discussions about skill-creator security, trust models, or content hygiene.
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Use when parallel agents in a convoy or across git worktrees hit a write conflict on shared state — a git tree, a config, or a shared document — and you must decide whether the conflict is semantically real. Classifies each conflicting hunk as independent (keep both), redundant (pick one), or a genuine clash (escalate), instead of blind locks, abort-and-retry, or escalate-everything. Sits ABOVE refinery-merge and NEVER blind auto-merges: it wraps an LLM judgment, defaults to escalate on any uncertainty, and unconditionally escalates any hunk touching .planning/, config, credentials, or safety-critical paths. Backed by CoAgent (arxiv 2606.15376v1). Triggers on write conflicts between parallel agents on shared repo state.
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Conversational guide for using tools/session-retro/observe.mjs to capture friction, wins, corrections, decisions, gaps, tool-use, and checkpoints as they happen during a session. Use at session start (to kick off the log), at inflection points (to record events), and at session end (to archive and feed the retrospective generator).
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Audit a skill by running a paired probe — the same task once with the skill loaded and once without — segment both traces into goal-directed phases, align phases, and emit a SIP report (surface anchoring, template copy, excess planning, task recovery, off-task artifact). Use whenever a skill is created, modified, or proposed for retirement. Pass-rate is BLIND to most skill effects: CTA (arxiv 2605.11946v1) shows a single skill can produce 522 measurable behavioural changes across 49 tasks while pass-rate moves only +0.3%. Triggers: "audit this skill", "is this skill helping", "retire skill", "before shipping skill", "behavioural impact of skill X", or any skill review event.
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Use when reviewing, shipping, or regression-testing a SKILL.md and you hold one or more captured trajectories where that skill was actually loaded. Translates the skill's instructions into behavior constraints, then reports which were EXERCISED (coverage) versus untested, and flags any that were in-scope but VIOLATED (compliance) — a cheap single-trajectory test-adequacy gate. It surfaces untested instructions rather than auto-blocking, and escalates fail-closed only when a violation touches shared repo state, never-surface memory, or self-modification. Complements skill-counterfactual-audit (which measures EFFECT) and skill-causal-curation (which measures contribution); this one asks ADEQUACY. Backed by the agent-skill-coverage metric (arxiv 2606.20659v2). Triggers on skill review, ship gating, and regression-testing a skill against its trajectories.
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Use when the user asks to forge, scaffold, author, or ship a new skill or agent — the skill-creator's own namesake artifacts. Drives the skill-forge loop (create → fill → validate → critique → ship → publish) via the skill-creator CLI.
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Manages skill-creator integration with GSD workflows including skill loading, session observation, bounded learning guardrails, and pattern detection. Use this skill whenever: executing any GSD phase (to ensure relevant skills are loaded first), starting or resuming a work session (to check for pending suggestions), the user asks about skills, patterns, or skill-creator status, performing code changes that might represent repeating patterns, the user corrects Claude's output (highest-signal observation), or when skill refinement, creation, or suggestion review is discussed. Critical for maintaining the adaptive learning layer.
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Instruction dispatch pipeline for routing work items to available agents. Implements a 7-stage fetch-allocate-prepare-hook-store-launch-confirm pipeline with batch convoy mode, formula expansion, idempotent dispatch, and crash recovery.
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Generates test cases for functions and components. Use when writing tests or creating test suites.
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Use when you have captured session evidence — session-retro / session- observatory-live traces in .planning/patterns/, tool logs, correction records — and want to induce a reusable skill from it. Segments the traces into candidate skill units (an LLM judgment, not a deterministic parse) and decomposes each candidate into a four-part structured spec: workflow structure, execution semantics, and runtime attachments (verification, safety, rollback, state). It emits a spec object, NOT a finished SKILL.md, and hands that spec to skill-forge. It sits between skill-integration (upstream frequency detector) and skill-forge (downstream author). Backed by Agent-Trace-to-Skill Induction (arxiv 2606.06893v1). Triggers on inducing a skill from captured traces, turning a repeated pattern into a skill spec, and preparing evidence for skill-forge.
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TypeScript best practices and patterns. Use when writing TypeScript, fixing type errors, or working with generics.
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Practical naked-eye and binocular sky observing. Covers dark adaptation, limiting magnitude, constellation recognition, star hopping, the messier and Caldwell catalogs accessible without a telescope, the Moon, planets, meteor showers, aurorae, and the ethics and habits of observing under light-polluted and dark skies. Use when teaching someone to find their way around the sky, planning a naked-eye session, or choosing a first binocular tour.
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OpenStack security operations skill for hardening, certificate management, and security posture assessment of cloud infrastructure. Covers TLS certificate lifecycle (generation, deployment, rotation, expiry monitoring), security group management (default deny, minimum required openings), RBAC policy customization (per-service policy.yaml), network segmentation (management vs tenant vs external), audit logging (Keystone CADF events), vulnerability assessment procedures, compliance auditing, intrusion detection patterns, incident response procedures (credential compromise, instance compromise), password rotation, and API rate limiting. Use when hardening OpenStack, managing certificates, auditing security posture, or responding to security incidents.
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REST API design best practices. Use when designing APIs, choosing status codes, or creating endpoints.
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Use when the user asks to forge, scaffold, or author a new cartridge — content cartridge, department cartridge, or chipset bundle. Drives the cartridge-forge loop (scaffold → fill → gate checks → commit) via the skill-creator cartridge CLI.
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Pure mathematical structure. Sets, groups, rings, fields, topology — the formal bedrock everything else rests on.
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NASA Systems Engineering methodology mapped to cloud operations. Use when planning, executing, verifying, or documenting OpenStack cloud infrastructure following NASA SP-6105 and NPR 7123.1 processes. Provides phase gate criteria, document templates, and cross-references for all 7 SE lifecycle phases applied to cloud deployment and operations.
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Guidance for verifying documentation accuracy against running OpenStack infrastructure. Use when detecting documentation drift, validating operations procedures against live systems, or confirming that runbooks produce expected results on the deployed cloud. Implements NASA Product Verification (SP-6105 SS 5.3) applied to documentation artifacts.
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Deterministic git operations with state verification for skill-creator managed repos. Use when managing repos, branches, worktrees, or contribution workflows.
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Electronics Educational Pack — routes queries to 15 modules covering Ohm's law through PCB design
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Electrical power distribution design for infrastructure: load calculations (NEC 220), conductor sizing (NEC 310.16), transformer/UPS/PDU selection, redundancy architectures (N through 2N+1), DC distribution, and voltage classes 120V-480V. Activates for electrical load calculations, conductor sizing, power equipment selection, data center power design, and redundancy architecture planning.
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Generates simulation inputs across fidelity levels — OpenFOAM CFD cases, ngspice netlists, interactive React artifacts, and FreeCAD FEM setups — from verified engineering calculations.
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