ABVX Agent Skills

ABVX Agent Skills logo

Small, reviewable, validation-gated agent skills for Codex-style project work.

Validate Security Audit PyPI version Catalog live gh skill ready

ABVX Agent Skills is a small, auditable skillpack for coding agents that helps them write smaller diffs, debug from evidence, compact noisy shell output, and verify work before saying done. The proof-first pack keeps release, browser, locale, visual, device-boundary, and human-gated claims separate so an agent does not turn partial evidence into a confident public status.

These are not prompt dumps. They are compact SKILL.md workflows with clear triggers, attribution, risk notes, and validation. They are portable, versioned agent capabilities meant to be previewed, inspected, and loaded on demand through the Agent Skills progressive-disclosure model.

They also are not a replacement for MCP or CLI tools. In the ABVX stack, MCP is the access layer for external services, CLI is the execution layer for deterministic work, and skills are the discipline layer: they decide when to use MCP, when to use CLI, which checks are mandatory, and when a repeated workflow should become a reusable gate.

Try One Skill In 2 Minutes

Preview before installing:

gh skill preview markoblogo/abvx-agent-skills minimal-diff-builder

Install one skill:

gh skill install markoblogo/abvx-agent-skills minimal-diff-builder --agent codex --scope user

Then ask your coding agent:

Use minimal-diff-builder. Implement the smallest correct fix for this issue.

Three Measured Demos

Job Skill Evidence
Keep a bug fix small minimal-diff-builder Correctness and changed lines
Control exploration cost token-efficient-execution Token usage and correct answers
Check whether a release is proven public-release-verification Missing evidence and false live claims

These are small paired experiments, not promises of universal improvement. Read the method and captured results before interpreting a number. Structural validation, fixture checks, rollout observations, and held-out validation are different evidence tiers.

Catalog

Browse the searchable catalog at lab.abvx.xyz/tools/abvx-agent-skills/. The page is powered by the generated catalog data in docs/catalog.json, so the repository remains the source of truth while the published catalog lives on ABVX Lab.

If you want a scan-friendly text catalog for browsing or indexing, use CATALOG.md.

Companion contracts

Some useful repo surfaces are companion contracts rather than installable skill entries.

Start With One Job

Job Install Use when
Write smaller patches minimal-diff-builder The agent keeps refactoring too much, widening blast radius, or adding abstractions you did not ask for.
Debug from evidence diagnose The agent keeps guessing fixes without reproducing the failure and verifying the result.
Prove a regression fix bug-evidence-protocol A diagnosed bug needs captured same-command red/green evidence, broader checks, Git identity, and an honest fix status.
Harden repeated runtime sprints loop-hardening-contract Cardputer, browser, CI, or production work needs measured harness stripping, immutable runtime-path predicates, and broken-window revalidation without automatic revert.
Review plans before work assumption-excavation, pipeline-readiness-gate A plan, SET bundle, or spec sounds plausible but may hide assumptions or missing gates.
Coordinate reviewed multi-agent work bounded-orchestration-contract A non-trivial task benefits from Planner/Reviewer approval, stable findings, disjoint executor ownership, explicit route evidence, and root verification.
Preserve typed project truth git-native-context-contract Decisions, rules, specs, plans, bounded research, or recurring incident lessons need a minimal Git-reviewed lifecycle and relation contract.
Run reversible agent work reversible-agent-task A task should produce retained output first, then move through inspect -> select/apply/discard before touching the target workspace.
Check ship confidence confidence-fragility-review, delivery-baseline-audit A release, README, generated plan, or PR sounds done but evidence may be thin.
Choose the right delivery lane before shipping docs/ship-router-contract.md Work may need direct, review_first, bounded_loop, or human_gate routing before implementation widens or a ship claim is made.
Save tokens in shell-heavy work rtk-assisted-shell, shell-output-compaction, token-efficient-execution Logs, diffs, tests, and command output are burning context and hiding the real signal.
Verify frontend work browser-verification, design-critique-polish, motion-review-gate, fluid-interaction-review for drag/swipe physics The agent says "done" without checking real browser behavior, layout, states, motion, gesture continuity, or console errors.
Govern named agents, long operations, and durable decisions agent-operations-contract, agent-tool-contract-review, loop-readiness-review Agent configuration, schedules, memory, providers, operation status, or decision records are mistaken for authority or verified outcomes.

LoopOps

LoopOps is the framework layer in this repo: it decides when a repeated prompt should remain a prompt and when it should become a checklist, skill, script, or bounded loop.

See:

The next LoopOps layer is bounded skill evolution: see docs/skill-evolution-roadmap.md and the manual-pilot manifest in benchmarks/skill-evolution/manifest.json. Start with one or two repeated skills, treat the skill as a versioned artifact, capture rollout evidence, keep edits bounded, validate against held-out or independent cases, retain rejected proposals as negative feedback, and export best_skill.md only after maintainer acceptance.

For the public pack and searchable catalog, also keep catalog text source-linked, concise, and drift-checked against real skill files. See docs/quality-eval-and-catalog-hygiene-contract.md. Use docs/catalog-schema-hardening.md, docs/catalog-eval-tiers.md, and docs/catalog-drift-and-distribution.md for the follow-up rules. For delivery-lane choice before a ship claim, use docs/ship-router-contract.md.

LoopOps promotion ladder from prompt to checklist, skill, script, or bounded loop

Choose A Workflow

Start with one skill. Use the selection guide when your task needs a broader workflow.

Skills

These skills are grouped by the job they do. The token-economy layer is intentionally visible first: for many teams, the easiest win is not “a smarter prompt”, but less wasted context.

Token Economy & Context Control

Skill What It Does
rtk-assisted-shell Routes noisy shell workflows through RTK-style filtering. Measure command-output reduction on your own tasks; it is not a claim about total session cost.
shell-output-compaction Shrinks logs, diffs, and repo search output into counts, slices, and error-first excerpts. Usually the fastest way to turn multi-screen stdout into a small, usable artifact.
graph-guided-code-reading Replaces broad repo reading with entrypoints, symbols, dependencies, and blast radius. On large codebases this can turn “read everything” into a much smaller focus set.
context-degradation-review Reviews context poisoning, lost-in-the-middle failures, distraction, context clash, and stale carryover before they degrade agent behavior.
token-efficient-execution Cuts waste from repeated reads, broad rewrites, and low-value narration. Best for long coding sessions where the loop, not the final answer, is burning the budget.
token-frugal-mode Compresses final answers without dropping the decisive technical signal. Useful when the session is tight and you want shorter replies without caveman-style degradation.
lean-context-layout Shrinks always-loaded agent docs into a compact startup core and pushes the rest on demand. Best for bloated AGENTS.md, CLAUDE.md, and repo runbooks.
compaction-survival Preserves the high-value working state before long sessions collapse into compaction. Saves the turns you would otherwise spend reconstructing “what were we doing?”.
token-usage-audit Diagnoses where the budget is really going: startup bloat, shell noise, repeated reads, oversized summaries, or compaction loss. Use this before over-optimizing the wrong layer.

Coding, Debugging & Architecture

Skill What It Does
diagnose Runs a disciplined debugging loop around one reproducible signal, ranked hypotheses, and narrow verification.
bug-evidence-protocol Captures same-command red/green evidence, broader checks, Git/environment identity, route state, and an honest fix classification after diagnosis.
agent-tool-contract-review Reviews MCP tools, CLI commands, SET inputs, AGENTS.md generator outputs, and external-skill adaptation deltas as agent-facing contracts with explicit authority and output boundaries.
repo-debugging-ledger Keeps a checked-location ledger so debugging does not keep reopening the same code and repeating the same dead ends.
complexity-optimizer Finds safe complexity and performance simplifications without turning the codebase into a refactor festival.
minimal-diff-builder Builds the smallest correct implementation path using a YAGNI, stdlib-first, native-first, minimal-diff ladder with explicit safety exceptions.
overengineering-review Reviews code specifically for needless abstractions, replaceable dependencies, dead flexibility, and wrappers over stdlib or platform behavior.
architecture-deepening-review Reviews deeper module seams, coupling, change surfaces, and testability, not just top-level architecture slogans. Pair with html-diagram-artifact or html-brief-artifact when the output should be a browser-readable architecture report.
test-driven-execution Builds features and fixes through one-behavior-at-a-time red-green-refactor loops instead of broad speculative implementation.
system-zoom-out Pulls a local code area back into its wider system map so you can reason about callers, modules, boundaries, and blast radius.
local-inference-tuning Selects and tunes local LLM engines around hardware, model fit, cache policy, KV cache, batching, and OpenAI-compatible endpoints.
agents-best-practices Hardens agent harnesses around permissions, context shape, safety, and evaluation discipline.
skillopt-evolve-skills Improves agent instructions and skills from real task evidence rather than from theory alone.

Frontend, UX & Product Surfaces

Skill What It Does
design-register-bootstrap Establishes compact design context before implementation: brand vs product register, audience, creator intent, preserve-theirs constraints, anti-references, color strategy, and PRODUCT.md / DESIGN.md direction.
frontend-taste-layer Sets and reviews marketing/editorial visual direction through a design read, creator-intent check, relative composition/motion/density, preservation-first redesign, layout rhythm, and browser evidence; product UI routes to Lazyweb and UX review.
fluid-interaction-review Reviews direct-manipulation physics: 1:1 tracking and grab offset, pointer capture, current-value interruption, velocity handoff, momentum projection, hysteresis, soft boundaries, spatial continuity, and independent motion/transparency/contrast fallbacks.
anti-slop-review Reviews implemented UI and public prose for hard defects, incoherence, template risk, and AI-writing tells with stable evidence-backed findings instead of blanket aesthetic or voice bans.
design-critique-polish Runs a focused critique-and-polish pass to rank frontend issues, identify ship blockers, and tighten hierarchy, typography, color, and states.
frontend-product-builder Builds usable frontends, landing pages, pitch pages, dashboards, and prototypes with a product-first interaction model.
lottie-motion-builder Builds small production-ready Lottie assets from SVGs, logos, loaders, and UI states with a local preview harness and output verification.
motion-review-gate Reviews frontend motion before shipping: purpose, frequency, easing, duration, origin, interruptibility, GPU-safe properties, and reduced-motion support.
designmd-brand-kit Turns a website or brand surface into an agent-usable design system: structure, identity, and reusable UI cues.
browser-verification Verifies real browser rendering, responsive layout, and interaction behavior instead of trusting static code inspection.
web-quality-audit Audits accessibility, performance, UX, privacy, and browser security as one practical web quality pass.
prototype-lab Rapid throwaway builds for testing interaction, logic, and product direction before committing to heavier implementation.

HTML Artifacts & Visual Deliverables

Skill What It Does
html-diagram-artifact Creates standalone HTML/SVG diagrams for architecture, request paths, component relationships, and system explainers with minimal prose and browser-verifiable dark mode.
html-brief-artifact Creates standalone HTML briefs for plans, status updates, PR summaries, incident notes, and research explainers without drifting into a full frontend build.

Project Context & Onboarding

For design-heavy repos, pair this section with design-register-bootstrap from the frontend section.

Skill What It Does
project-context-bootstrap Detects the stack, asks the right project questions, and turns a weakly documented repo into a compact, agent-usable context surface.
filesystem-context-discipline Uses typed files for scratchpads, plans, evidence, retained outputs, and handoffs without polluting always-loaded prompt context.
rabbithole-doc-exploration Opens AGENTS.md, skill docs, SET plans, repomaps, or seed docs in an optional local Rabbithole canvas for human-selected branch questions.
durable-context-maintenance Keeps repo-local context current after architecture, workflow, and test-flow changes so agents stop rediscovering the same facts.
personal-workspace-router Creates a local root router with isolated domain folders, user-triggered memory, decision logs, and routing corrections for multi-project operator work.

Discovery, Planning & Delivery

Skill What It Does
rapid-grilling Quickly sharpens vague ideas through one-question-at-a-time alignment before heavier planning starts.
doc-grounded-grilling Stress-tests a plan against repo docs, ADRs, design assets, and domain language so discovery stays grounded in reality.
assumption-excavation Surfaces hidden environment, dependency, behavioral, temporal, and success assumptions in plans, docs, skills, and SET bundles.
spec-to-prd Turns clarified context into a durable PRD for product, client, and internal roadmap work.
plan-to-issues Breaks PRDs and plans into thin end-to-end slices that agents or humans can actually pick up.
repo-issue-triage Moves bugs and enhancements through a compact state machine so backlog items become actionable instead of vague.

Research, Knowledge & Reusable Methods

Skill What It Does
bounded-evaluation Designs small eval gates with fixtures, rubrics, pairwise checks, position-bias mitigation, and explicit accept/reject/revise decisions.
evidence-ledger-research Keeps claims, sources, calculations, and open questions in a disciplined evidence ledger.
hypothesis-diversification Generates diverse hypotheses, explanations, or bounded proposals before evidence review and adversarial validation.
social-publishing-gate Gates social posts, replies, scheduling, and monitoring through draft, audit, approval, publish, and monitor steps.
loopops-protocol Chooses when repeated agent work should stay a prompt or be promoted into a skill, checklist, script, workflow, or cost-bounded loop.
agent-learning-layer-triage Routes agent lessons into the right auditable layer: prompt, memory, durable docs, checklist, skill, script, eval, or rejected buffer.
book-to-skill Converts books, papers, and long documents into reusable, progressive-disclosure agent skills.
doc-to-lora-evaluator Evaluates whether document-to-adapter memory is worth a proof-of-concept before building a Doc-to-LoRA plugin or pipeline.
goal-loop-designer Compiles raw agent goals into bounded loop harnesses with stop rules, rubric, judge prompt, budgets, and portable artifacts.
role-skill-pack-design Designs compact role/workflow skill packs with base layers, difference layers, boundaries, and rollout order.
workflow-policy-layering Separates workflow from authority, escalation, forbidden actions, and validation so assistant specs stop contradicting themselves.
brief-first-execution Starts non-trivial work with one live brief for scope, non-goals, risks, verification, and done criteria.
private-vs-publishable-skill-audit Audits private skill packs before publication and extracts only the reusable layer.
agent-friction-ledger Captures repeated agent blockers, doc gaps, tool incompatibilities, and workarounds as local, privacy-safe reports that can feed docs, skills, scripts, or evals.
knowledge-base-enrichment Enriches Markdown notes and wikis with provenance while preserving raw sources and review boundaries.
git-native-context-contract Keeps typed project truth, decisions, and incident lessons reviewable through a human-gated Git lifecycle.
skill-health-audit Audits trigger fit, evidence depth, drift, overhead, safety, and evaluation readiness without editing the audited skill.

Product Context & Responsible Growth

Skill What It Does
product-context Builds a compact, evidence-backed product context with audience, conversion, proof, language, and claim boundaries before go-to-market work.
bounded-growth-loop Designs recurring content, SEO, analytics, or product-review loops with durable state, verification, stop rules, and approval-gated outputs.

Workflow, Handoffs & Multi-Track Work

Skill What It Does
dynamic-workflow-packets Orchestrates large coding, research, audit, harness, or client-search tracks without losing verification, budgets, integration, and risk gates.
loop-readiness-review Checks whether a recurring agent loop has cadence, state, isolation, verifier, budget, run log, rollback, and human gate before it runs.
loop-hardening-contract Adds measured harness stripping, immutable runtime-path sprint packets, and broken-window revalidation without automatic revert.
pipeline-readiness-gate Selects a compact pre-implementation, post-implementation, or ship gate without adopting a heavy multi-agent pipeline runtime.
reversible-agent-task Runs risky or multi-file agent work as retained output, then requires inspect -> select/apply/discard before target workspace mutation.
handoff Produces compact continuation briefs for long-running work, agent resumes, and human handoffs.
agent-operations-contract Governs named agents, operation receipts, decisions, memory, provider evidence, and approval boundaries.
bounded-orchestration-contract Coordinates reviewed Planner/Reviewer/Executor work with stable findings, disjoint ownership, and root verification.

Long-Run Delivery Control

Skill What It Does
idea-to-ship-gates Routes ideas through intent, spec, slices, architecture, proof, convergence, and release gates.
delivery-preflight-gate Runs the minimum useful baseline checks before a long implementation loop or PR publication, so pre-existing breakage and noisy branches do not poison later verification.
phase-spec-execution Breaks larger delivery into explicit phases with acceptance criteria, verification commands, and lightweight state updates.
recovery-loop-3strike Bounds execution failure handling to one evidence-bearing retry, one focused fix-spec, and then an honest blocker handoff.
confidence-fragility-review Checks whether confident claims in plans, docs, releases, or workflow contracts are backed by evidence.
delivery-baseline-audit Re-checks declared deliverables and final verification against the starting baseline and full working tree before calling the task complete.
public-release-verification Proves release status across package, deploy, HTTP, browser, locale, visual, and human approval gates.

Security & Defensive Review

Skill What It Does
authorized-security-router Routes authorized defensive security and reverse-analysis tasks by scope, target type, intent, toolchain, and blocked-action gates.

Structured Data & Spreadsheet Work

Skill What It Does
spreadsheet-workbook-forensics Repairs and edits spreadsheets where workbook structure, formulas, and cell-level verification matter.

Install

Install the three-skill starter set:

pip install abvx-agent-skills
abvx-skills install minimal-diff-builder diagnose token-efficient-execution

If PyPI is temporarily unavailable, use GitVerse's PyPI mirror for that install command only:

python -m pip install abvx-agent-skills --index-url https://pypi-mirror.gitverse.ru/simple/

Install with GitHub CLI agent-skills support:

gh skill install markoblogo/abvx-agent-skills minimal-diff-builder

Target a specific host or scope when needed:

gh skill install markoblogo/abvx-agent-skills minimal-diff-builder --agent codex --scope user
gh skill install markoblogo/abvx-agent-skills diagnose --agent cursor --scope project

gh skill is currently a GitHub CLI preview feature. Use GitHub CLI v2.90.0+. The command set and flags are documented in the official gh skill manual and the GitHub changelog announcement for GitHub CLI agent skills.

Published package pages:

Current distribution channels:

Distribution boundaries for repo, Lab, and package surfaces are summarized in docs/catalog-drift-and-distribution.md.

Install the packaged CLI from PyPI:

uv tool install abvx-agent-skills

Install one skill into Codex:

git clone https://github.com/markoblogo/abvx-agent-skills
cp -R abvx-agent-skills/skills/dynamic-workflow-packets ~/.codex/skills/

Install all skills:

git clone https://github.com/markoblogo/abvx-agent-skills
cp -R abvx-agent-skills/skills/* ~/.codex/skills/

Start a new agent session after installation so the skill descriptions are discovered.

Install one packaged skill into Codex:

abvx-skills install dynamic-workflow-packets

Install to a custom destination:

abvx-skills install --destination ./tmp-skills

Smoke-test the published package from PyPI:

python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install abvx-agent-skills
abvx-skills list
abvx-skills validate

Safety And Auditability

Before installing a skill, inspect it:

gh skill preview markoblogo/abvx-agent-skills minimal-diff-builder

Validate local or packaged skills:

abvx-skills validate
gh skill publish --dry-run

Run the static security audit:

abvx-skills audit-security ./skills --no-llm

This repository is intentionally optimized for inspection before trust: compact skill files, reviewable metadata, structural validation, and a publish dry-run that catches naming and metadata drift before release.

Onboarding Paths

Demos

Distribution

If you are listing the repo in curated skill directories, agent catalogs, or install surfaces, use docs/outreach/submission-kit.md for positioning and docs/outreach/targets.md for target tracking.

Catalog and publish discipline for the pack itself lives in docs/quality-eval-and-catalog-hygiene-contract.md. Schema expectations, eval tiers, and drift/distribution rules live in docs/catalog-schema-hardening.md, docs/catalog-eval-tiers.md, and docs/catalog-drift-and-distribution.md.

For the current first-wave outreach set, use docs/outreach/first-wave-submissions.md.

Repository Profile

Each public skill includes:

  • SKILL.md - executable agent instructions
  • SKILL_CARD.md - intended use, attribution, risks, evaluation, and version
  • agents/openai.yaml - Codex UI metadata

The project follows the open Agent Skills shape: SKILL.md plus optional scripts/, references/, and assets/. For Codex compatibility, top-level frontmatter is kept conservative: name, description, license, metadata, and supported fields only.

The HTML artifact skills intentionally keep their deliverables single-file and dependency-light. Use them for explainers and briefs, not as substitutes for production frontend implementation.

Contribute

How To Contribute Your Own Skills

Use this repo when a workflow has repeated often enough that it deserves a sharper portable behavior layer, not when you just have a long prompt.

Contribution path:

  • Submit your own skill: draft it against docs/abvx-skillpack-profile.md, mirror the shape of an existing skill, and open a PR with the smallest useful slice.
  • Request a missing skill: open a Skill Request when the repeated workflow is real but the right skill does not exist yet.
  • Autopsy a broken skill: open a Skill Autopsy when an internal or external skill added noise, abstractions, or fake process and should be reduced into something stronger.

Good submissions usually have:

  • a narrow trigger, not a vague domain
  • one clear behavior change
  • explicit anti-patterns or stop conditions
  • honest verification instead of broad motivational prose

Use docs/solo-dev-quickstart.md and docs/team-rollout-playbook.md as examples of opinionated packaging aimed at real adoption paths rather than generic documentation.

Validate

python scripts/validate.py

Or validate the packaged skills through the CLI:

abvx-skills validate

Run a static security audit with SkillSpector:

pip install git+https://github.com/NVIDIA/SkillSpector.git
abvx-skills audit-security ./skills --no-llm

Evaluate reports against the repo policy and baseline:

python scripts/evaluate_skillspector.py \
  --reports-dir artifacts/skillspector \
  --policy .abvx/skillspector-policy.yaml \
  --baseline .abvx/skillspector-baseline.json

Validate a local skills directory:

abvx-skills validate ~/.codex/skills

Structural validation and security audit are separate gates. The validator checks required files, frontmatter, directory/name alignment, TODO placeholders, cards, UI metadata, and basic secret patterns.

Benchmarks

The measured demos retain paired runs, fixtures, raw traces, and deterministic checks for three skills. They are small single-model pilots; broader effectiveness and held-out validation remain unproven.

Release

Build and check the package locally:

python -m pip install --upgrade build twine
python -m build
python -m twine check dist/*

Publish flow:

  • Run the publish GitHub Actions workflow with repository=testpypi for a dry run against TestPyPI.
  • Create a GitHub release, or run the same workflow with repository=pypi, to publish to PyPI.
  • Configure trusted publishing for both pypi and testpypi environments in the package index before the first release.
  • Keep the released version aligned with pyproject.toml and the skill inventory documented above.

Philosophy

  • Keep always-loaded context small.
  • Prefer procedural rules over vague advice.
  • Make skills easy to audit in diffs.
  • Attribute upstream inspiration.
  • Pair useful automation with risk gates and verification.

See docs/abvx-skillpack-profile.md for the repository standard.

Attribution

Several skills are inspired by public work from the broader agent tooling ecosystem. See ATTRIBUTION.md.

License

MIT. See LICENSE.

Project links

Data verified by PyPI on Sep 7, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
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  • Released:
Newer release available (0.15.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for markoblogo from gravatar.com markoblogo

Credits

Author: markoblogo

GitHub Statistics

Data verified by PyPI on Sep 7, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.10

Tags

agents codex llm prompts skills

Classifiers

Report project as malware

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