pskoett-ai-skills

In the author's own words, from each skill's SKILL.md — showing the first 21 of 56 files.

• context-surfing

  Monitors context window health during large, long-running, multi-session, or explicitly context-sensitive work. Uses bounded external anchors, one cold-context review when self-recovery is uncertain, and a clean handoff on real drift. Do not auto-activate merely because a medium task has an intent frame and plan.

  skills/context-surfing/SKILL.md on GitHub (opens in a new tab)

• control-session-orchestrator

  Control-plane workflow for coordinating multi-agent, multi-session project work from a single Codex, GitHub Copilot, or agent-app control session. Use this skill whenever the user asks to orchestrate agents, create or steer worker sessions, run a workflow-like effort, fan out audits/research/migrations, coordinate parallel implementation streams, monitor other project sessions, or compare this co…

  skills/control-session-orchestrator/SKILL.md on GitHub (opens in a new tab)

• eval-creator-ci

  [Beta] CI-only eval regression runner using gh-aw (GitHub Agentic Workflows). Runs all eval cases in .evals/ on a schedule or per-PR, reports pass/fail results, and can block merges on regressions. Also creates new eval cases from promoted patterns flagged by learning-aggregator-ci. Use when: you want automated regression testing of promoted rules in CI/headless pipelines. For interactive eval cr…

  skills/eval-creator-ci/SKILL.md on GitHub (opens in a new tab)

• eval-creator

  [Beta] Creates permanent eval cases from promoted learnings and runs regression checks against them. Turns failures into test cases that prevent silent regression. This is the outer loop's regress-test step. Use when a learning is promoted and has a clear pass/fail condition, or on cadence to verify promoted rules still hold.

  skills/eval-creator/SKILL.md on GitHub (opens in a new tab)

• intent-framed-agent

  Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.

  skills/intent-framed-agent/SKILL.md on GitHub (opens in a new tab)

• learning-aggregator-ci

  [Beta] CI-only learning aggregation workflow using gh-aw (GitHub Agentic Workflows). Scans .learnings/ files on a schedule, groups entries by pattern_key, identifies promotion-ready patterns, and posts a gap report as a PR or issue comment. Use when: you want automated cross-session pattern detection in CI/headless pipelines without interactive prompts. For interactive use, use learning-aggregato…

  skills/learning-aggregator-ci/SKILL.md on GitHub (opens in a new tab)

• learning-aggregator

  [Beta] Cross-session analysis of accumulated .learnings/ files. Reads all entries, groups by pattern_key, computes recurrence across sessions, and outputs ranked promotion candidates. This is the outer loop's inspect step — it turns raw learning data into actionable gap reports. Use on a regular cadence (weekly, before major tasks, or at session start for critical projects). Can be invoked manual…

  skills/learning-aggregator/SKILL.md on GitHub (opens in a new tab)

• plan-interview

  Ensures alignment between user and Claude during feature/spec planning through a structured interview process. Use this skill when the user invokes /plan-interview before implementing a new feature, refactoring, or any non-trivial implementation task. The skill runs an upfront interview to gather requirements across technical constraints, scope boundaries, risk tolerance, and success criteria bef…

  skills/plan-interview/SKILL.md on GitHub (opens in a new tab)

• pre-flight-check

  [Beta] Session-start scan that surfaces relevant learnings, recent errors, and eval status before work begins. Bridges the outer loop back into the inner loop by making accumulated knowledge visible at task start. Activated via SessionStart hook or manually before major tasks.

  skills/pre-flight-check/SKILL.md on GitHub (opens in a new tab)

• self-healing-ci

  CI-only self-healing workflow using gh-aw (GitHub Agentic Workflows) for active runtime recovery on pull requests and scheduled runs. When a CI check fails (test, build, lint, deploy, scan), this skill diagnoses the failure from CI logs, proposes a verified patch as a PR comment or follow-up commit, and commits a HEAL entry to `.learnings/HEALS.md`. Verify-before-persist discipline preserved: a H…

  skills/self-healing-ci/SKILL.md on GitHub (opens in a new tab)

• self-healing

  Active runtime recovery for coding agents: when something breaks mid-task, diagnose the root cause, write a fix, VERIFY by re-running the broken thing, then file a `HEAL-` entry to `.learnings/HEALS.md` with proof. Use whenever a command, test, build, or lint fails or exits non-zero; on missing tooling, dependency/lockfile mismatch, wrong runtime version, venv or permission errors, port conflicts…

  skills/self-healing/SKILL.md on GitHub (opens in a new tab)

• self-improvement-ci

  CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.

  skills/self-improvement-ci/SKILL.md on GitHub (opens in a new tab)

• self-improvement

  Captures learnings, errors, corrections, and feature requests to enable continuous improvement. Use when: (1) User corrects Claude ('No, that's wrong...', 'Actually...'), (2) User requests a capability that doesn't exist, (3) Claude realizes its knowledge is outdated or incorrect, (4) A better approach is discovered for a recurring task, (5) Receiving a Handoff block from self-healing (a recurrin…

  skills/self-improvement/SKILL.md on GitHub (opens in a new tab)

• simplify-and-harden-ci

  CI-only Simplify & Harden workflow for pull requests using gh-aw (GitHub Agentic Workflows). Runs headless scan-and-report checks for simplify/harden/document, posts structured findings, and can block merges on critical or advisory classes. Use when: you want automated quality/security review in CI without interactive approvals.

  skills/simplify-and-harden-ci/SKILL.md on GitHub (opens in a new tab)

• simplify-and-harden

  Post-completion self-review for coding agents that runs simplify, harden, re-verification, and micro-documentation passes on non-trivial code or high-impact configuration changes. Use when a task is complete in a general agent session and you want a bounded quality and security sweep before signaling done. For CI pipeline execution, use simplify-and-harden-ci.

  skills/simplify-and-harden/SKILL.md on GitHub (opens in a new tab)

• skill-pipeline

  Pipeline orchestrator that classifies incoming coding tasks and routes them through the correct combination of skills at the right depth. Implements two feedback loops: the inner loop (detect, verify, recover) runs within a session via plan-interview, intent-framed-agent, context-surfing, verify-gate, self-healing (active recovery on failure), simplify-and-harden, and self-improvement. The outer…

  skills/skill-pipeline/SKILL.md on GitHub (opens in a new tab)

• skill-tester-ci

  Validates all CI skills in this repo. Checks Agent Skills spec compliance, gh-aw workflow compilation, permission correctness, and structural conventions. Use when CI skills have been added or modified and you want to verify they compile and conform before committing.

  skills/skill-tester-ci/SKILL.md on GitHub (opens in a new tab)

• skill-tester

  Validates all interactive skills in this repo against the Agent Skills spec, project conventions, and structural requirements. Runs quick_validate.py, checks line limits, verifies cross-references, and tests hook scripts. Use when skills have been added or modified and you want to verify everything passes before committing or submitting.

  skills/skill-tester/SKILL.md on GitHub (opens in a new tab)

• verify-gate

  Runs project compile, test, and lint commands between implementation and quality review. Gates simplify-and-harden behind machine verification. If checks fail, routes back to implementation with diagnostics for a fix loop. If checks pass, signals ready for the quality pass. Use after any implementation work completes and before simplify-and-harden. Essential for the inner loop's verify step.

  skills/verify-gate/SKILL.md on GitHub (opens in a new tab)

• mcp-builder

  Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

  .agents/skills/mcp-builder/SKILL.md on GitHub (opens in a new tab)

• skill-creator

  Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

  .agents/skills/skill-creator/SKILL.md on GitHub (opens in a new tab)

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